The following is a listing of seminars/lectures that have been given in the past on topics of interest to the ECMWF scientific community.

## 2020

17 December
at 14:00

Virtual

Intrinsic Uncertainty in the Euro-Atlantic Response to the MJO heating in boreal winter: Results from ECMWF Re-Forecasts

Speaker: David Straus (George Mason University and COLA)

### Abstract

While the Euro-Atlantic response to the MJO has been well studied in reanalysis and a hierarchy of models, a factor that is often overlooked is the uncertainty in the response due to the intrinsic variability in the full diabatic heating during even a single phase of the MJO.

We examine the heating variability within large ensembles of boreal winter reforecasts from the ECMWF model, focusing on forecasts initialized in phases 2 and 3 of the MJO (with heating anomalies located over the Indian Ocean). Results will be shown from the METIS project reforecasts (using three different resolutions) as well as from new experimental reforecasts in which the only difference between ensemble members is the application of stochastic physics in the target Indian Ocean region.

The resulting uncertainty (ensemble spread) in the Euro-Atlantic response during the first few weeks of the forecasts is also examined, as well as some discussion of ongoing work to link the response uncertainties to those in the heating.

3 December
at 14:30

Virtual

Beyond Forcing Scenarios: Predicting Climate Change through Response Operators in a Coupled General Circulation Model

### Abstract

Global Climate Models are key tools for predicting the future response of the climate system to a variety of natural and anthropogenic forcings. Here we show how to use statistical mechanics to construct operators able to flexibly predict climate change in a hierarchy of climate models. Here we concentrate on the results obtained using a CMIP6-class GCM, the MPI-ESM v.1.2. For the first time we prove the effectiveness of response theory in predicting future climate response to CO2 increase on a vast range of temporal scales, from inter-annual to centennial, and for very diverse climatic variables. We investigate within a unified perspective the transient climate response and the equilibrium climate sensitivity, and assess the role of fast and slow processes. The prediction of the ocean heat uptake highlights the very slow relaxation to a newly established steady state. The change in the Atlantic Meridional Overturning Circulation (AMOC) and of the Antarctic Circumpolar Current (ACC) is accurately predicted. The AMOC strength is initially reduced and then undergoes a slow and partial recovery. The ACC strength initially increases due to changes in the wind stress, then undergoes a slowdown, followed by a recovery leading to a overshoot with respect to the initial value. Finally, we are able to predict accurately the temperature change in the North Atlantic. We propose this methodology as an extremely efficient way to explore future climate change pathways and to test test the safe operating space of our planet.

Refs.:
V. Lembo, V. Lucarini, F. Ragone, Beyond Forcing Scenarios: Predicting Climate Change through Response Operators in a Coupled General Circulation Model. Sci Rep 10, 8668 (2020)
M. Ghil, V. Lucarini, The Physics of Climate Variability and Climate, Rev. Modern Physics, 92, 035002 (2020)
V. Lucarini, F. Lunkeit, F. Ragone, Predicting Climate Change Using Response Theory: Global Averages and Spatial Patterns, J. Stat. Phys. 166, 1036 (2017)

26 November
at 14:30

Virtual

https://Recording_Kelder

Exploiting SEAS5 (re-)forecasts to assess and anticipate climate extremes beyond the observed record (UNSEEN)

Speaker: Timo Kelder (Loughborough University)

Timo Kelder is a PhD student in climate science at Loughborough University, with visiting status at Oxford University and ECMWF. Supervised by Prof. Rob Wilby, Dr Tim Marjoribanks, Dr Louise Slater and Prof. Christel Prudhomme, he analyses large-ensemble climate model simulations to quantify climate extremes and explain their non-stationary behaviour beyond what is possible from observed records.

### Abstract

Climate extreme events are causing high socio-economic impact. We can prepare and adapt to extreme events by learning from past extreme events. However, what about events that we have not yet seen?

To assess what kind of extreme events we could expect beyond what we can see in the observed records, the UNprecedented Simulated Extreme ENsemble (UNSEEN) approach might be used. Instead of the 'single realization' of reality, ensemble approaches can be exploited to better assess the likelihood of infrequent events, which only have a limited chance of occurring in observed records.

In this talk, we will explain how the ECMWF seasonal prediction system SEAS5 can be used to generate an UNSEEN ensemble. Through various examples, we will discuss the necessity of thoroughly evaluating UNSEEN extremes. We provide a framework to evaluate the independence, stability, and fidelity of SEAS5 and we introduce an open and transferable UNSEEN workflow developed during the ECMWF summer of weather code 2020. We will show that the increased sample size helps in risk estimates, detecting trends in 100-year extremes as well as explaining drivers of extreme events that could not be explained from the observed record alone.

23 November
at 11:00

Virtual

https://Recording_Jonathan Day

Measuring the impact of a new snow model using surface energy budget process relationships

Speaker: Jonathan Day

### Abstract

Energy exchange at the snow‐atmosphere interface in winter is important for the evolution of temperature at the surface and within the snow, preconditioning the snowpack for melt during spring. This study illustrates a set of diagnostic tools that are useful for evaluating the energy exchange at the Earth’s surface in an Earth System Model, from a process‐based perspective, using in‐situ observations. In particular, a new way to measure model improvement using the response of the surface temperature and other surface energy budget (SEB) terms to radiative forcing is presented. These process‐oriented diagnostics also provide a measure of the coupling strength between the incoming radiation and the various terms in the SEB, which can be used to ensure that improvements in predictions of user relevant properties, such as 2m temperature, are happening for the right reasons. Correctly capturing such process relationships is a necessary step towards achieving more skilful weather forecasts and climate projections.

These diagnostic techniques are applied to assess the impact of a new multi‐layer snow scheme in the European Centre for Medium‐Range Weather Forecasts’‐Integrated Forecast System at two high‐Arctic sites (Summit, Greenland and Sodankylä, Finland). A previous study showed that it will enhance 2m temperature forecast skill across the northern hemisphere in boreal winter compared to forecasts with the single layer model, reducing a warm bias. In this study we use the diagnostics to show that the bias is improved for the right reasons.

20 October
at 11:00

Virtual

Classification and dynamical precursors of extreme precipitation events over Northern Italy

Speaker: Federico Grazzini

### Abstract

In this work, we investigate a vast number of extreme precipitation events (EPEs) occurring between 1979 and 2015 in northern-central Italy. Through the optimal blending of ERA5 dataset and high resolution gridded daily precipitation observational analysis (ARCIS), we classify, via a simple machine learning approach, EPEs into three categories (Cat1, Cat2, Cat3) according to thermo-dynamic conditions over the affected region. The three categories do not only differ locally but also in the evolution of precursor Rossby wave packet (RWP) associated with the trough responsible for the precipitation. The apparent seasonality of the flow cannot solely explain these differences; therefore, the relevant physical processes in the RWP propagation of each case are further investigated. In particular, we show that RWPs associated with the strongest EPEs, namely the ones falling in Cat2, undergo a substantial amplification over the western N. Atlantic due to anomalous ridge-building two days before the event; arguably due to diabatic heating sources. A greater understanding of flow dynamics and water vapour transport pathways leading to EPEs not only helps evaluate the predictability of regional precipitation extremes but could also clarify the response of local hydrogeological cycle to a warming climate.

30 September at 14:15

Using the power of data assimilation to model the COVID-19 pandemic

Speaker: Geir Evensen (NORCE and NERSC Bergen)

### Abstract

The onset of the SARS-COV-2 Pandemic led to a complete lockdown of society in many countries. So here I was, an applied mathematician, in confinement, following the news coverage of extreme situations at hospitals in Italy and New York, and at the same time hearing confusing and contradictory statements from politicians and leaders in various countries. This situation motivated me to contribute with knowledge-based information to support decision-makers. So, in my home office, I started developing an epidemic model and gather data on the COVID-19 decease and related hospitalizations and deaths in Norway. I coupled the model to my data-assimilation library, and end of March, after about two weeks of work, I was able to model and predict the SARS-COV-2 pandemic evolution in Norway.  I used the data-assimilation system to calibrate model parameters, including the time-dependent effective-reproductive-number, R. I then provided reports with model predictions to the Norwegian authorities to explain the unstable situation and the pandemic's dependency on R.

On April 10th, I invited an international group of colleagues working in data assimilation to use the model system on data from their respective countries. Nearly everyone jumped at the opportunity, and from then, we have worked together as an international team.  We modeled the SARS-COV-2 pandemic in the four European countries Norway, England, The Netherlands, and France; the province of Quebec in Canada; the South American countries Argentina and Brazil; and the four US states Alabama, North Carolina, California, and New York. These countries and states all have vastly different developments of the epidemic, and we could accurately model the SARS-CoV-2 outbreak in all of them.

The joint work led to significant learnings regarding the use of data assimilation in epidemic modeling. We compiled the results into a large manuscript and submitted it to the journal "Fundamentals of Data Science," where we are currently finalizing the revisions.  We also made the paper available from MedRxiv

In this seminar, I will present results from this paper. I will introduce and justify the choice of model used, i.e., an SEIR model with age-classes and compartments of sick, hospitalized, and dead. I will introduce and demonstrate the ESMDA data-assimilation technique used, and I will discuss some of the benefits of using this system.

This work demonstrates how it is possible to use iterative ensemble smoothers to estimate an SEIR model's parameters. The data assimilated are the daily numbers of accumulated deaths and the number of hospitalized. Also, it is possible to condition on the number of cases obtained from testing.

We start from a wide prior distribution representing the model parameters; then, the ensemble conditioning leads to a posterior ensemble of estimated parameters leading to model predictions in close agreement with the observations. The updated ensemble of model simulations has predictive capabilities and include uncertainty estimates.

We estimate the effective-reproductive-number as a function of time, and we can assess the impact of different intervention measures. By starting from the updated set of model parameters, we can make accurate short-term predictions of the epidemic development given knowledge of the future effective-reproductive-number. Also, the model system allows for the computation of long-term scenarios of the epidemic under different assumptions.

The model system is freely available from Github (https://github.com/geirev/EnKF_seir).

We realize that more complex models, e.g., with regional compartments, may be desirable, and we suggest that the approach used here should be applicable also for these models. I have recently upgraded the model system to include multiple regions or countries with specified interactions between them. This new model formulation allows for simulating the pandemic development for, e.g., the countries in Europe or the states in the US.

29 September
at 14:00

VIRTUAL

Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere

Speaker: Damien Weidmann (Rutherford Appleton Laboratory, UK)

### Abstract

Earth is changing at an unprecedented pace. Understanding and quantifying the processes driving the change and particularly the role played by the atmosphere is necessary, and the CubeMAP mission has been designed to address this need. The CubeMAP mission has been selected as a finalist for the new ESA SCOUT mission programme. It consists of a constellation of three identical CubeSats, each equipped with three high resolution spectrometers and one hyperspectral solar disk imager. The overall mission goal is to study, understand, and quantify processes in the tropical Upper Troposphere and Stratosphere (UTS), study its variability, and contribute to trends analysis in its composition and its effects on climate and vice-versa. The UTS composition plays a significant role in controlling the Earth’s climate, with still poorly explored feedbacks within the Earth System. This region of the atmosphere is coupled to the surface and the free troposphere both dynamically and radiatively. Its composition is determined by anthropogenic emissions of greenhouse gases and pollution precursors and is subject to changes via radiative, dynamical, and chemical processes. The ultra-miniature, while high spectral resolution, spectrometers selected for the payload are integrated thermal infrared laser heterodyne spectro-radiometer probing narrow spectral windows in limb solar occultation. For aerosol and oxygen measurements, an innovative, co-registered, solar disk imager using a multispectral CMOS sensor ensures both pointing knowledge accuracy and a large spectral channel diversity in the visible and near infrared, together with a small form factor. The platform selected for the mission is based on the GomSpace 12U CubeSat form factor which can accommodate the payloads while also keeping volume, mass and cost at a manageable level. The system design is to a high degree based on proven GomSpace COTS products with demonstrable flight heritage, hence lowering the mission risk. The mission contributes to developing a novel observation model: it offers a high level of deployment flexibility and system modularity, as well as economy of scale, through the use of identical payloads and platforms functionalized to specific Earth observation goals. The constellation approach also obviates the traditional limited coverage of limb solar occultation mission, whilst benefiting from the high accuracy this sounding mode brings. CubeMAP is also highly complementary to the nadir sounding infrastructure and contributes to enhancing its outputs and exploitation. It also addresses the forthcoming gap in solar occultation sounding capabilities.

24 September
at 10:00

VIRTUAL

Joint ECMWF/UoR seminar on GloFAS-ERA5 river discharge trends

Speaker: Ervin Zsoter

### Abstract

The main objective of this study is to analyse the GloFAS-ERA5 river discharge reanalysis for any noticeable change (including gradual trends or discontinuities) in the annual mean time series across the 1979-2018 (40-year) period, and to evaluate how realistic these are compared with available observed river discharge time series.

These variabilities are quantified by linear regression in order to highlight any concerning features in the GloFAS-ERA5 time series.

This work is particularly important for GloFAS, as large trends, discontinuities or other similar features could have a major consequence on the GloFAS flood thresholds in around 50% of catchments, which are based on GloFAS-ERA5, and thus subsequently on the issuing of flood warnings.

In addition, this study also contributes to the understanding of the water cycle variable behaviour in ERA5 (driver of GloFAS-ERA5) and ERA5-Land (higher resolution land reanalysis forced by ERA5, produced offline) by exploring the linear trends in river discharge and related hydrological variables. In exploring the stability of the time series in ERA5, we seek to trigger potential further discussions and research studies, which subsequently should help with the planning and development for the next generation ECMWF reanalysis, ERA6.

18 June
at 10:30

VIRTUAL

“ecPoint” - a Post-processing Tool that improves Forecasts and highlights Systematic Model Errors

Speaker: Timothy Hewson

### Abstract

In April 2019 ECMWF introduced a new, experimental, “point rainfall” forecast product onto its ecCharts web display platform, based on the post-processing package “ecPoint”, to give site-specific forecasts for everywhere in the world up to day 10. Prior to this development forecasters had access to just raw ensemble output in ecCharts, which provides gridbox average totals. ecPoint aims to incorporate probabilistically the expected sub-grid variability, and simultaneously apply gridscale bias corrections. Both these adjustments depend critically on “gridbox-weather-type”.

This presentation will describe the meteorology-based calibration rationale that underpins ecPoint, how this is different to pre-existing post-processing methods, and how it can also be applied to other surface variables such as 2m temperature. Numerous benefits will be highlighted.

The conditional verification concepts underpinning the calibration allow one to identify weather-situation-dependent gridscale biases. Examples will illustrate the diagnostic power of this approach, showing where and when rainfall is typically under- and over-forecast, providing pointers for future model improvements. And using an open source GUI one can apply the calibration code to data from other models, and thereby intercompare performance in different weather situations.

The forecast improvements that then arise will be discussed, using both long term global verification up to day 10, and illustrative case studies, with a focus on how extreme localised rainfall, that might lead to flash floods, is better handled. It will be shown how the post-processing can usefully shift the emphasis for warning issue from one region to another, when one compares with raw ensemble output.

There will be brief reference, from collaborative work, to how ecPoint output seems to compare favorably with the post-processed output of convection-resolving limited area ensembles.

The talk will conclude by discussing, in the context of ongoing and potential projects, numerous future applications of ecPoint, such as bias-corrected inputs to hydrological models, point rainfall re-analyses and tests of theories such as city impact on rainfall. Avenues for improving the methodology will also be highlighted.

28 April
at 10:00

VIRTUAL

Can approximations of the CRPS help us better understand why the skill changes?

Martin Leutbecher and Thomas Haiden

### Abstract

Ensemble verification of scalar variables often involves the use of the continuous ranked probability score (CRPS). The talk looks at a Gaussian approximation of the CRPS with the aim to improve our understanding of score changes. The approximation permits to express the CRPS of an ensemble as a function of the variance of the error of the ensemble mean, the mean error of the ensemble mean and the ensemble variance. The methodology will be applied to direct model output from medium-range ensemble forecasts as well as postprocessed ensemble forecasts. We will examine how well this approximation works and whether it might be suitable to complement information we see for instance in scorecards.

14 February
at 10:30

Room: LT

Aircraft Weather Observations and their Use (current and future)

Speaker: Steve Stringer (Met Office and EUMETNET) and Siebren de Haan/Jan Sondij (KNMI and EMADDC)

### Abstract

Aircraft based weather observations (ABO) have increasingly become a very valuable input into the global weather forecasting process, with some independent assessments showing their impact on NWP to be second only to that of satellite data. An international workshop on Aircraft Based-Observations (ABO) is to be hosted at ECMWF, 12th/13th February 2020, bringing together ABO data users and ABO data providers to share their experience of aircraft data use and to recommend any necessary changes to procedures in the provision or use of aircraft data in the future. The seminar will provide an overview of the current status ABO data provision, plans for the future, together with outcomes and recommendations from the ABO Workshop. An overview of European plans to implement an operational centre and service for the  delivery of quality controlled Mode-S derived aircraft observations will be also included.  (Mode-S reports are derived from air traffic management messages and provide very high resolution data, particularly winds, over parts of Europe and potentially elsewhere.  They are not yet processed at ECMWF.)

11 February
at 14:00

Room: LT

The relationship between the circumglobal teleconnection, the Indian monsoon and European summer weather

Speaker: Jonathan Beverley (University of Reading, University of Exeter)

### Abstract

Recent research has led to improvements in European winter seasonal forecasts, however summer forecast skill remains relatively low. One potential source of predictability for Europe is the Indian summer monsoon, which can influence the weather across many parts of the northern hemisphere via a global wave train known as the “circumglobal teleconnection” (CGT). Here I assess the ability of the ECMWF coupled seasonal forecast model to represent this teleconnection mechanism. To understand how errors in its representation are related to errors in summer forecast skill over Europe, results from relaxation and thermal forcing experiments, as well as barotropic model experiments, will be presented. These experiments were designed to identify possible causes of errors in the teleconnection pathway, and to explore the impact of improving the representation of the CGT on European summer forecast skill.

23 January
at 14:00

Room: LT

Can GNSS Polarimetric Radio Occultations (GNSS  PRO) contribute to better understanding, monitoring or predicting extreme events?

Speaker: Estel Cardellach (ICE-CSIC/IEEC, Spain)

### Abstract

The GNSS Polarimetric Radio Occultations (GNSS PRO) is a new measurement concept being proved aboard the PAZ satellite, operating since May 2018. The technique is based on the 'traditional' GNSS Radio Occultations (GNSS RO), widely used for atmospheric profiling of thermodynamic parameters and assimilated in operational NWP. Adding polarimetric capabilities to the RO system enables to sense hydrometeors, especially big rain droplets in heavy rain, and frozen particles. The system, thus, is the first technique with joint and synchronous sensitivity to both types of parameters: thermodynamic and hydrometeor profiling. Whereas the geophysical content of the GNSS RO signals to infer the 'traditional' products lays on the bending of the signal propagation (atmosphere acting as a lens because of its vertical gradients in T, p and q), the physical principle to sense hydrometeors is the excess propagation delay of the horizontally polarized signal with respect to the vertically polarized one. These are two independent sensing principles obtained from a single set of data.

Can GNSS PRO contribute to better understanding, monitoring or predicting extreme events? We are not ready to provide a full answer to this question, yet. But the seminar will present the technique, the facts demonstrated during the PAZ mission so far, the current identified limitations, and potential areas of interest and opportunities for scientists at ECMWF working on precipitation, micro-physics modeling and large scale convective systems -- elements towards improved understanding, monitoring and prediction of some extreme events.

## 2019

11 December at 10:30

Room: LT

Decadal variations in seasonal teleconnection patterns

Speaker: Tim Palmer (University of Oxford)

### Abstract

The seminal Horel and Wallace (1981) paper set out the way in which El Nino variability is teleconnected to midlatitudes. Now we have considerably more observational data than Horel and Wallace had, we can ask whether these teleconnections exhibit significant decadal variations. They do, and this variability can help us understand a range of issues in seasonal prediction, from the role of the stratosphere to the signal-to-noise paradox.

29 November
at 10:30

Data assimilation and post-processing for large-scale Nordic hydrology

Speaker: Marie-Amelie Boucher (Sherbrooke University)

### Abstract

Hydrological forecasting is now increasingly conceived as a global issue that transcends catchment boundaries and should be studied from a larger perspective. In addition, while the number of gauging stations is decreasing, potential new sources of meteorological and hydrological data are appearing, including the contribution of citizen scientists. It is likely that in the coming years, many other regions of the world will face a situation of co-existing local and global hydrological forecasting systems. How could we make the most out of both the local and global information? One idea would be to use the global ensemble forecasts as an initial field, and then to use the local forecast as additional information to refine the forecasts locally. Another element of interest in the context of global hydrology is the increasing availability of data from citizen science programs. This is a potentially rich source of information that could complement more « traditional » data. Can this data be assimilated in hydrological models? Is there any gain to assimilate data from citizen scientists in addition to traditional data? I would like to discuss these questions and many others, especially in the context of using machine learning tools to assimilate observations into hydrological models. Hopefully, this seminar will lead to fruitful discussions in preparation for my sabbatical (Sept 2020-August 2021), which I intend to spend mostly at the ECMWF.

12 November
at 10:30

Lecture Theatre

The Bureau of Meteorology's use of NWP for the prediction of lightning and severe convective hazards

Speaker: Harald Richter (BOM)

### Abstract

Over the last three years the Bureau's operational modelling suites have begun to incorporate a global design ensemble and convection-allowing models (CAMs). These systems, largely based on the UKMO's Unified Model, are now capable of meaningful predictions that relate to a range of convective hazards such large hail, damaging winds and lightning itself.

I will first introduce the current and planned modelling systems at the Bureau of Meteorology, before moving into aspects of the post-processing approaches taken and planned. While the UKMO's IMPROVER framework is intended to provide the bulk of the post-processing capability, the prediction of convective hazards is achieved through a range of different individual algorithms such as Calibrated Thunder for the prediction of cloud-to-ground lightning or storm attributes such as updraft helicity for the prediction of severe convective storms. The focus of my presentation will be on these convectively focused post-processing approaches.

Harald's scientific interests
------------------------------------

Harald is a senior scientist in the Science to Services program of the Australian Bureau of Meteorology. His main focus is the diagnosis and prediction of deep extratropical convection and the associated hazards such as large hail, damaging winds and tornadoes. Over the past seven years his particular interest has been the use of large-scale and convection allowing models to predict thunderstorms and their hazards.

In a previous life, Harald was responsible for training the Bureau's forecasters in the diagnosis, nowcasting and forecasting of severe thunderstorms based on observational systems and NWP which has set up a strongly operational perspective for his research to follow.

Harald also leads a cross-agency project on physical impact prediction which quantitatively combines exposure and vulnerability information with NWP-based wind predictions. Occasionally he has been called upon to act in more managerial roles, which allowed him to adopt a slightly wider view of the Bureau's research and development activities.

6 November
at 10:30

Clouds, Weather and Climate: From the Southern Ocean to Climate Strikes

Speaker: Dr Andrew Gettelman ((NCAR and visiting scientist at the University of Oxford and ECMWF)

### Abstract

Clouds are critical for forecasting weather and climate. This presentation will provide an overview of how critical cloud processes affect weather and climate prediction, and how we simulate them in models. Critical cloud processes often not considered include supercooled liquid clouds, shallow clouds over the ocean, and cloud interactions with aerosols in the atmosphere. Interestingly, supercooled liquid clouds are not only important for extreme weather, they are also important for climate. Recent observations and modeling work, taking us literally to the ends of the Earth, is leading to a better understanding of clouds, aerosols and climate, with possible improvements in weather prediction and some surprising and not fully understood implications for future climate change.

30 October
at 14:00-15:00

Room: LCR

Connecting the dots in hydrological ensemble prediction

Speaker: Maria-Helena Ramos (Irstea, France)

### Abstract

Connecting people, disciplines and efficient techniques is crucial to develop hydrological ensemble prediction systems and foster partnerships. Probabilistic and scenario-based forecasts are recognized as essential to quantify uncertainties and support decision making in flood forecasting, drought management and water resources planning. Many successful cases have already been implemented, but still more must be done to bridge knowledge gaps, facilitate operational implementations and raise awareness among decision makers of the value of reliable predictions. This presentation will show some examples of work carried out at Irstea in France to connect different aspects of the hydrometeorological forecasting chain.

29 October
at 15:30

Room: LT

Impact of land temperature analysis in NWP and other recent developments in LSDA at the Met Office

Speaker: Breogan Gomez (UKMO)

### Abstract

The Met Office Global Land Surface Data Assimilation (LSDA) system consists of a suite of schemes that give the initialisation fields for various variables. Over the last year, the Met Office has developed a system that creates soil moisture and land temperature analyses using the Simplified Extended Kalman Filter (SEKF) with the aim of having consistent analysis increments across all land variables. Our tests at N320 showed a positive impact in all regions and at all lead times when verifying against screen temperature and relative humidity. Applying the same methodology to the regional NWP model, UKV, yields some positive results. In recent years, a substantial effort has been made to improve the land initialisation in the UK regional NWP system. We have developed a soil moisture analysis using the same methodology as the global model with SEKF and a snow amount analysis using an optimal interpolation algorithm. The former has shown a neutral impact in the screen verification, but it has significantly improved the river flow predictions. The latter provides a much better snow cover estimation when compared to independent satellite products.

17 October
at 10:30

Room: Council

Post-processing at the Australian Bureau of Meteorology: precipitation results and IMPROVER collaboration

Speaker: Tom Gale (BMRC)

### Abstract

Post-processing of rainfall is a priority for the Australian Bureau of Meteorology, due to the Australian climate and impacts on a range of industries, particularly agriculture. Significant advances have been made in the last few years, such as 2-3 lead days skill improvement since 2016 for 1mm/day rain amount. The result is better forecasts for the general public and specialised users, and reduced need for meteorologist intervention in forecast production. This talk will cover the changes made to rainfall post-processing over the last few years, and verification results from our 3 hourly rainfall post-processing which became operational in August 2019.

The Australian Bureau of Meteorology is collaborating with the UK Met Office on development of the new IMPROVER post-processing system. IMPROVER focuses on using the outputs from ensemble and convection permitting NWP models, is fully probabilistic, allows for verification of each processing step and is seamless from 15 minutes to 15 days. This talk will cover the differences between expected IMPROVER configuration in the UK and Australia, and work to provide compatible software environments at the Met Office and BoM.

30 September  at 10:30

Room: LT

Historical images of Earth from space: IFS versus observations (an informal talk)

Speaker: Philippe Lopez

### Abstract

As a follow-up to my improvised (virtual) trip to the Mo on back in July, I have extended my comparison of our model with various historical views of the Earth from space and I thought it would be worth giving an informal presentation about its outcome. Do not expect any slides full of groundbreaking equations. On the other hand, if you just wish to escape from our crazy world for a moment by looking at some nice images of our planet from far (far) away in space and time, please feel free to come.

13 September
at 11:30

Room: LT

Exascale resilience strategies for time-dependent solvers

Speaker: Chris Cantwell (Imperial College)

### Abstract

Time-dependent partial differential equations (PDEs) arise in a wide range of application areas, for example in fluid dynamics. The high-fidelity resolution of complex flows often requires large-scale computational resources and is one of the drivers towards exascale computing. Energy usage is a major concern for these systems. The power overhead necessary to implement traditional hardware resilience to combat failures at exascale is likely to be substantial. The usefulness and energy efficiency of our computational tools might therefore be more effectively maintained by making the software more tolerant of the frequent hardware failures anticipated to occur on future large-scale systems.
In this talk I will highlight the case for resilience in software and present our latest efforts to address this challenge in the context of time-dependent PDE solvers. We combine user-level failure mitigation (ULFM), a proposed extension to the MPI 4.0 standard, with remote in-memory check-pointing in a minimally intrusive way, in order to augment existing software tools with scalable fault tolerance capabilities. Our resilience approach improves forward-path performance over conventional techniques by avoiding the parallel file system completely, and allows one or more concurrently failed ranks to be rebuilt with spare ranks on-the-fly and independently of other non-failed processes. I will describe the algorithms, implementation and their performance characteristics, and illustrate their application through examples using the Nektar++ spectral/hp element framework.

20 August
at 10:30

Room: LT

Forecast Evaluation of Set-Valued Properties

Speaker: Tobias Fissler (Imperial College, London)

### Abstract

In forecast evaluation, one distinguishes two major tasks: forecast validation (or verification) and forecast comparison. While the former one is commonly performed with identification functions (for point forecasts) or other diagnostic tools of calibrations such as the Probability Integral Transform (for probabilistic forecasts), the latter task utilises scoring functions in the case of point forecasts and scoring rules for probabilistic forecasts. It is a widely accepted paradigm that these scoring functions (rules) should be consistent (proper) in that they honour correctly specified forecasts, thus incentivising truthful reporting under risk-neutrality.

The statistical, climatological and financial literature has seen remarkable contributions to the evaluation of real- or vector-valued properties as well as predictive distributions for real- and vector-valued quantities. On the other hand, the case of set-valued properties has received considerably less attention.

Acknowledging the spatial structure of many climatological and meteorological phenomena of interest, we introduce a theoretical framework for sound forecast evaluation of set-valued quantities such as the expected area of precipitation or confidence regions for floods. To this end, we suggest the formal distinction between a selective notion, where forecasters are content with specifying a single point in the set of interest, and an exhaustive notion, where forecasters are far more ambitious and aim at correctly specifying the entire set of interest. We unveil a stark dichotomy between these two notions: A functional can be either selectively or exhaustively elicitable.

We discuss implications of this mutual exclusivity for best practice in forecast evaluation of set-valued quantities, putting an emphasis on applications in meteorology and climatology.

This talk is based on joint work with Jana Hlavinová and Birgit Rudloff.

13 August
at 10:30

Room: LCR

Trends and Challenges in TC NWP for the 2020s

Speaker: M Fiorino (University of Colorado (USA)

### Abstract

Perhaps the greatest success story in the history of Numerical Weather Prediction (NWP) is the 90% improvement1 in tropical cyclone (TC) track forecasts from the 1980s to 2018. This dramatic improvement was made possible by the high-resolution, high-quality global modeling of the leading operational centers ECMWF and the UKMO.
The talk firsts reviews the history of TC NWP – from the early days at Penn State where we made the first TC NWP forecast with operational analyses in a ‘full physics’ model (MM0 – the predecessor to WRF) in the late 1970s – to the 2000s, when global models became the clear ‘go-to’ aid for human forecasters. During the 2000s I was the NWP officer at both the Joint Typhoon Warning Center (JTWC) and the National Hurricane Center (NHC) where my main task was to bring good modeling into the human forecast process. It was during my time at NHC that I demonstrated how the deterministic ECMWF HRES forecasts were often superior to the best forecast aid (consensus) and how this significant advance was not because of a horizontal resolution increase but because of (subtle) changes in the physics (see Fiorino 2009: https://www.ecmwf.int/en/elibrary/17493-record-setting-performance-ecmwf...).
More recently, the limited-area model HWRF, during its 12 years in NCEP operations (2007-2018), has failed to add value to the much lower resolution GFS host global model at the medium range (72 h mean position error). Further, the inability of HWRF to make superior short-range track forecast (12- and 24-h) vis-à-vis ECMWF, despite near ‘perfect’ HWRF initial position error, challenges conventional thinking on the way forward in TC NWP.
This review of TC NWP and the current performance of HWRF/GFS suggest some next steps/challenges for the 2020s: 1) vortex analysis – can model forecasts be improved by a more accurate analysis of the TC vortex? e.g., by assimilation of the truly unique and special observation of the TC forecast centers – ‘TC vitals’; and 2) “completing the forecast” by predicting both TC genesis and dissipation. Metrics is common problem for both vortex initialization and genesis. The talk will conclude with a TC ‘forecast error’ metric proposal, that is more consistent with warnings and TC impacts, and some recent work on deterministic TC genesis verification.

31 July at 11:00

Room: CC

Recent trends and future projections of Meteorological droughts

Speaker: Sergio M Vicente-Serrano (Spanish National Research Council)

### Abstract

Drought is one of the most difficult hydroclimatic hazards to quantify and monitor, which has lead to strong scientific debate on the temporal behaviour of drought trends over the last decades and possible future projections. Here the different perspectives considered to identify recent drought trends are shown and discussed, focusing on the different role of both precipitation and atmospheric evaporative demand. The role of the statistical properties of drought (mostly their autoregressive character) and land/atmosphere feedbacks related to plant physiology and CO2 fertilization are also a determining factor to understand droughts under future climate scenarios.

31 July
at 10:30

Room: LT

Efforts on Scaling and Optimizing Climate and Weather Forecasting Programs on Sunway TaihuLight

Speakers: Haohuan Fu (Tsinghua University, China) and Wei Xue (High Performance Computing Institute, Tsinghua, China)

### Abstract

The Sunway TaihuLight supercomputer is the world's first system with a peak performance greater than 100 PFlops, and a parallel scale of over 10 million cores. In contrast with other existing heterogeneous supercomputers, which include both CPU processors and PCIe-connected many-core accelerators (NVIDIA GPU or Intel MIC), the computing power of TaihuLight is provided by a homegrown many-core SW26010 CPU that includes both the management processing elements (MPEs) and computing processing elements (CPEs) in one chip. This talk reports our efforts on refactoring and optimizing the climate and weather forecasting programs on Sunway TaihuLight. To map the large code base of CAM and WRF to the millions of cores on the Sunway system, we take OpenACC-based refactoring as the major approach, and apply source-to-source translator tools to exploit the most suitable parallelism for the CPE cluster, and to fit the intermediate variable into the limited on-chip fast buffer. For individual kernels, when comparing the original ported version using only MPEs and the refactored version using both the MPE and CPE clusters, we achieve up to 22x speedup for the compute-intensive kernels. For the 25km resolution CAM global model, we manage to scale to 24,000 MPEs, and 1,536,000 CPEs, and achieve a simulation speed of 2.81 model years per day.

Haohuan Fu is a professor in the Ministry of Education Key Laboratory for Earth System Modeling, and Department of Earth System Science in Tsinghua University, where he leads the research group of High Performance Geo-Computing (HPGC). He is also the deputy director of the National Supercomputing Center in Wuxi, leading the research and development division. Fu has a PhD in computing from Imperial College London. His research work focuses on providing both the most efficient simulation platforms and the most intelligent data management and analysis platforms for geoscience applications, leading to two consecutive winning of the ACM Gordon Bell Prizes (nonhydrostatic atmospheric dynamic solver in 2016, and nonlinear earthquake simulation in 2017).

10 July

at 11.00

Room: CC

London as a laboratory to explore the health effects of air pollution

Speaker: Ian Mudway (Kings College, London)

### Biography

Dr Ian Mudway is a  senior lecture at the School of Population Health and Environmental Sciences at King's College London and a member of the MRC-PHE Centre for Environment and Health; MRC & Asthma UK Centre in Allergic Mechanisms of Asthma and NIHR-PHE Health Protection Research Unit in Health Impact of Environmental Hazards. He has over 20 years of experience researching the impacts of air pollution on human health and in the development of assays to quantify the toxicity of the chemical cocktails that pollute the air we breathe. Over this period Dr Mudway has published over 100 research papers, reports and book chapters on these topics, as well as providing advice the local, national and international governments and NGOs. Dr Mudway is passionate about the communication of science to lay audiences and has worked extensively with artists and educationalist to promote the public understanding of the risks associated with environmental pollutants. Currently his work is focused on understanding early life impacts of pollutants on the development of the lung and cognitive function in children living within urban populations.

28 June
at 11:00

Room: LT

Towards an unbiased stratospheric analysis

Speaker: Patrick Laloyaux (ECMWF)

### Abstract

A set of newly developed diagnostics based on GPS-RO observations has revealed the presence of systematic large-scale errors in the stratospheric temperature of the IFS model. Interestingly, the amplitude of this bias has increased over the past few years in conjunction with the last horizontal resolution upgrade and the revision of the radiative scheme.

To take into account model biases, a weak-constraint 4D-Var formulation has been developed where a model-error forcing term is explicitly estimated inside the 4D-Var minimisation. This approach is able to reduce by up to 50% the bias in the analysis departures of all observations sensitive to stratospheric temperature. The importance of anchoring data (accurate observations that do not require bias correction) such as GPS-RO is apparent to ensure the good performance of the method. Weak-constraint 4D-Var also allows to have a more consistent way to treat the source of the different biases, ensuring that the Variational Bias Correction (VarBC) corrects only systematic errors from data and observation operators. In this talk, we will also start exploring the potential of the new weak-constraint 4D-Var to correct for model biases in medium-range weather forecasting and climate reanalyses.

19 June
at 15:30

Room: LT

Introduction to the New York State Mesonet

Speaker: Chris Thorncroft (University at Albany)

### Abstract

The New York State Mesonet (NYSM) is a comprehensive network of 126 environmental monitoring stations deployed statewide with an average spacing of 27 km.  The primary goal of the NYSM is to provide high quality weather data at high spatial and temporal scales to improve atmospheric  monitoring and prediction, especially for extreme weather events.  Completed in spring 2018, each station is equipped with  a standard suite of atmospheric and soil sensors.  Collectively, the network is comprised of 1,825 sensors with approximately 907,200 observations collected per day.  Unique aspects of the NYSM include its measurement of snow depth,  soil moisture and temperature, and its collection of camera images at  every site.  The NYSM also pioneered the building of three additional  sub-networks to collect vertical profile, surface energy budget, and  snow water equivalent measurements at a select number of sites across  the state.  The location of each station was carefully selected based upon WMO siting criteria and local requirements.  Extensive metadata are made available online.  All data are collected, quality-controlled, archived, and disseminated every 5 minutes.  Real-time data are displayed on the web for public use, and archived data are available for download.  Data are now utilized by a variety of sectors including emergency  management, transportation, utilities, agriculture and education.  Recent examples of the utility of the data will be shared.

18 June
at 10:30
Room: LT

NOAA-CIRES-DOE 20th Century reanalysis version “3” (1836-2015) and Prospects for 200 years of reanalysis

Speaker: Gil Compo

### Abstract

The new historical reanalysis dataset generated by the Physical Sciences Division of NOAA’s Earth System Research Laboratory and the University of Colorado CIRES, the Twentieth Century Reanalysis version 3 (20CRv3), is a comprehensive global atmospheric circulation dataset spanning 1836 to present, assimilating only surface pressure and using monthly Hadley Centre sea ice distributions (HadISST2.3) and an ensemble of daily Simple Ocean Data Assimilation with Sparse Input (SODAsi.3) sea surface temperatures.  SODAsi.3 was forced with a previous version of 20CR that itself was forced with a previous SODAsi, allowing these “iteratively-coupled” boundary conditions to be more consistent with the atmospheric reanalysis.  20CRv3 has been made possible with supercomputing resources of the U.S. Department of Energy and a collaboration with GCOS, WCRP, and the ACRE initiative. It is chiefly motivated by a need to provide an observational validation dataset, with quantified uncertainties, for assessments of climate model simulations of the 19th to 21st centuries, with emphasis on the statistics of daily weather. It uses, together with the NCEP global forecast system (GFS) numerical weather prediction (NWP) land/atmosphere model to provide background "first guess" fields, an Ensemble Kalman Filter (EnKF) data assimilation method. This yields a global analysis every 3 hours as the most likely state of the atmosphere, and also yields the uncertainty of that analysis.

20CRv3 has several improvements compared to the previous version 2c. The analysis and the 80 member ensemble are generated with the NCEP GFS at T254 resolution (about 0.75 degrees latitude by longitude) with 64 levels in the vertical, compared to T62 (about 2 degrees latitude by longitude) and 28 vertical levels in the 20CRv2c 56 member ensemble. This gives an improved representation of extreme events, such as hurricanes. Implementation of a “relaxation to prior” covariance inflation algorithm, combined with stochastic parameterizations in the GFS, provides quantitatively better uncertainty estimates than the previous additive inflation of 20CRv2c. An adaptive localization helps to keep the analysis from over-fitting the observations. A variational quality control system retains more observations. An incremental analysis update procedure produces a temporally smoother analysis without spurious spin-up trends seen in 20CRv2c. Millions of additional pressure observations contained in the new International Surface Pressure Databank version 4.7, such as from the citizen science Oldweather.org project, also improve the analyses. These improvements result in 20CR version “3” having comparable or better analyses to version 2c, as suggested by improved 6 hour forecast skill, more realistic uncertainty in near-surface air temperature, and a reduction in spurious centennial trends in the tropical and polar regions.  Possibilities for 200 years of reanalysis are also discussed in light of results of test reanalyses of the 1816 “Year without a Summer”.

Gilbert P. Compo1,2, Laura Slivinski1,2, Jeffrey S. Whitaker2, Prashant D. Sardeshmukh1,2, Benjamin S. Giese3, Philip Brohan4, Rob Allan4

1CIRES, University of Colorado, USA, compo@colorado.edu,  2Physical Sciences Division, Earth System Research Laboratory, NOAA, USA., 3Department of Oceanography, Texas A&M University , USA, 4Met Office Hadley Centre, Exeter, UK

14 June
at 10:30

Room: LT

Ocean Waves as a Missing Link Between Atmosphere and Ocean

Speaker: Alex Babanin (University of Melbourne, Australia)

### Abstract

Role of the waves as a link between the ocean and atmosphere will be discussed. It is rapidly becoming clear that many large-scale geophysical processes are essentially coupled with the surface waves, and those include weather, tropical cyclones, ice cover in both Hemispheres, climate and other phenomena in the atmosphere, at air/sea, sea/ice and sea/land interface, and many issues of the upper-ocean mixing below the surface. Besides, the wind-wave climate itself experiences large-scale trends and fluctuations, and can serve as an indicator for changes in the weather climate.  In the presentation, we will discuss wave influences at scales from turbulence to climate, on the atmospheric and oceanic sides.

At the atmospheric side of the interface, the air-sea coupling is usually described by means of the drag coefficient Cd, which represents the momentum flux in terms of the wind speed, but the scatter of experimental data with respect to such dependences is very significant and has not improved noticeably over some 40 years. It is argued that the scatter is due to multiple mechanisms which contribute into the sea drag, many of them are due to surface waves and cannot be accounted for unless the waves are explicitly known. We also argue that separation of the momentum flux for the components which go to the waves and to the current, is not trivial and depends on a numbers of factors such as sea state, but also on the measurement setup. In this presentation, field data, both at moderate winds and in Tropical Cyclones, and a WBL model are used to investigate such biases. It is shown that near the surface the turbulent fluxes are less than those obtained by extrapolation using the logarithmic-layer assumption, and the mean wind speeds very near the surface are larger.

Among wave-induced influences at the ocean side, the ocean mixing is most important. Until recently, turbulence produced by the orbital motion of surface waves was not accounted for, and this fact limits performance of the models for the upper-ocean circulation and ultimately large-scale air-sea interactions. Theory and practical applications for the wave-induced turbulence will be reviewed in the presentation. These include viscous and instability theories of wave turbulence, direct numerical simulations and laboratory experiments, field and remote sensing observations and validations, and finally implementations in ocean, Tropical Cyclone, ocean and ice models.

14 June
at 13:00

Room: LT

The Bureau of Meteorology Research Program

Speaker: Peter May (BOM, Australia)

### Abstract

An overview of the Australian Bureau of Meteorology's research program will be presented.  This will include our plans focusing on high resolution numerical prediction, multi-week and seasonal modelling, advanced post processing, climate science and our work to address some fundamental science and societal challenges.  For example our work on fire weather ranging from the changing fire risk in Australia, our current and future guidance and work on firestorms including fully coupled fire -high resolution simulations.   Finally I will discuss our future plans in the context of a fundamental transformation of the Bureau and the way we will be providing weather and climate services.

30 May
at 10:30

Room: LT

The atmospheric response to increased ocean model resolution in the ECMWF Integrated Forecasting System: a seamless approach

Speaker: Chris Roberts

### Abstract

This study uses initialized forecasts and climate integrations to evaluate the wintertime North Atlantic response to an increase of ocean model resolution from ∼100 km (LRO) to ∼25 km (HRO) in the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS). The presented analysis considers the atmospheric response at lead times of weeks to decades and assesses mean biases, variability, and subseasonal predictability. Importantly, the simulated impacts are highly dependent on lead time such that impacts seen at climate timescales cannot be generalized to initialized forecasts. At subseasonal lead times (weeks 1-4), sea surface temperature (SST) biases in LRO and HRO configurations are similar and partly inherited from ocean initial conditions. At multidecadal timescales, mean differences are dominated by biases in the LRO configuration, which include a North Atlantic cold bias and a breakdown in the

29 May
at 10:00

Room: LT

The axes of the Météo-France scientific strategy

Speaker: Marc Pontaud (Meteo-France)

### Abstract

Make progress in the knowledge and anticipation of extreme phenomena and their impacts, in a context of climate change

Anticipating extreme or high-stakes phenomena and their impacts, in metropolitan France and overseas, is a strong societal expectation addressed to Météo-France. Progress in this area is largely based on improvements made to our numerical weather prediction systems, particularly regional ones, which remain a priority research objective at Météo-France. Progress will come from several areas.

A first source of progress will be the assimilation of an increasing number of observations from new meteorological satellites launched during the period, but also through access to new data sources or through better use of existing sources such as meteorological radars. It will also be a question of optimizing the information provided by these data. This will require the development of a new generation of data assimilation algorithms. The realization of forecasts in the form of sets will be generalized in order to improve by a few hours the anticipation of the occurrence of a meteorological hazard, to better predict its intensity and consequences and to be able to offer new services based on a greater capacity to adapt the forecasts to the expectations of users taking into account their challenges.

Improving the prediction of extreme or high-stakes weather phenomena and their impacts also requires progress in understanding the processes at work and in their modelling at different scales. Research investigation resources (measurement campaigns, instrumented sites, meter-scale modelling, etc.) will be oriented and developed as a priority to meet these objectives. It will also evaluate the contribution of very high resolution modelling, i.e. a few hundred metres grid, to the prediction of meteorological hazards on sites or during events with stakes.

For the very short time frames (0-3h), the contribution of artificial intelligence (AI) and other signal processing techniques to the extrapolation of observations and their fusion with numerical forecasts will be explored.

Moreover, knowledge at the regional level of the evolution of the frequency and intensity of extreme events with climate change is essential for adapting to climate change and strengthening territorial resilience measures. Météo-France will contribute to the scientific response to these issues, identified in the French Adaptation Program, by interpreting recent climate trends through the use of observations and climate model results. The aim will be to carry out simulations of past and future climate, in particular with the fine-scale forecasting model, capable of representing the evolution of Mediterranean episodes, tropical cyclones and the urban heat island during heat waves.

Continue the transition to integrated environmental modelling systems shared between forecasting and climate

Operational weather prediction, seasonal climate prediction and climate study require modelling not only the behaviour of the atmosphere but also that of other interacting components of the Earth system (continental surfaces, ocean, waves, cryosphere, chemical composition of the atmosphere) and anthropogenic factors (urbanization, irrigation, dams, anthropogenic emissions, etc.). This evolution towards environmental modelling will result in the construction and experimentation of a regional "Earth system" composite model with kilometric resolution, with the assistance of partners mastering certain components, such as the ocean or sea ice. This regional modelling system will be modular to allow different configurations and coupling levels depending on the forecast or application objectives.

This work will continue to be part of a single modelling system logic, from the global to the local scale, with tools shared between weather forecasting and climate modelling activities.

For numerical weather prediction, including the chemical composition of the atmosphere, a new research axis will be opened, that of data assimilation coupled between the different components (atmosphere, continental surfaces, aerosols and atmospheric chemistry, ocean, sea states), with the prospect of taking better advantage of certain observations at the interfaces and the exploitation of a greater number of data.

Adapt modeling tools to operational requirements on tomorrow's computing architectures

The operational use of the tools developed by the research is at the heart of the institution's strategy. On the one hand, it allows a rapid transfer of innovations from research to all the institution's activities and, on the other hand, a daily comparison of scientific work with reality, thus allowing researchers to benefit from regular feedback on the quality of their models. This community of tools between scientific and operational activities also imposes constraints that must be integrated by research teams (speed of code execution, compatibility of algorithms with computing infrastructures, etc.). In close collaboration with the meteorological services community, the establishment will carry out the scientific work necessary to prepare for future technological developments in intensive computing, including the development of graphics processors or other new or emerging architectures that will have a profound impact on the structure of digital codes.

Enhance weather and climate forecasts in response to the expectations of internal and external beneficiaries

Météo-France's research must also contribute to the promotion of its innovations, both to internal users (particularly forecasters) and to external users.

In particular, the enhancement of modeling data, which is increasingly accurate and informative but also more numerous, rich and complex, will be a major focus of research. This includes supporting the use of ensemble forecasts by defining methods for statistical extraction of relevant signals and post-processing adapted to this new type of data. To cover the needs in this area, scientific expertise in the field of AI will be strengthened. In a logic of support for end-users, the emphasis will be placed on innovation, the transfer of research results to the operational level and the orientation of scientific activities towards the needs of Météo-France's operational departments.

Strengthen the dynamics of national and international cooperation

The orientation of Météo-France's research activities towards environmental modelling on a regional scale will be accompanied by a strengthening and broadening of cooperation with the French academic and scientific community, such as the CNRS, the academic world and major national research organisations, and with international actors engaged in this same path.

The evolution of numerical weather prediction systems towards coupled systems and the consideration of future supercomputer architectures lead to increased cooperation with the meteorological services community with which the modelling tools are co-developed (European consortia Aladin and Hirlam, ECMWF). To be fully effective, this collaboration between meteorological services will have to be based on better shared tools and software convergence with the ECMWF is a reaffirmed priority for the Establishment.

In the field of space observation of the Earth, Météo-France will consolidate its status as a privileged interlocutor with space agencies for meteorological and climate applications, and more broadly environmental applications. This approach will be based on the close relations established with CNES in France, Eumetsat and ESA in Europe as well as with certain international space agencies.

28 May
at 10:30

Room: LT

Improving atmospheric reanalyses for historical extreme events by rescuing lost weather observations

Speaker: Ed Hawkins (University of Reading)

### Abstract

Our understanding of past changes in weather and climate rely on the availability of observations made over many decades. However, billions of historical weather observations are effectively lost to science as they are still only available in their original paper form in various archives around the world. The large-scale digitisation of these observations would substantially improve atmospheric reanalyses back to the 1850s. Recently, volunteer citizen scientists have been assisting with the rescue of millions of these lost observations taken across western Europe over a hundred years ago. The value of these data for understanding many notable and extreme weather events will be demonstrated.

16 May
at 11:15

Room: Council

Are seasonal forecasts useful to improve operational decisions for water supply in the UK?

Speakers: Francesca Pianosi and Andres Peñuela (Bristol University)

### Abstract

Improved skill of seasonal predictions for the North Atlantic circulation and Northern Europe are motivating an increasing effort towards developing seasonal hydrological forecasting systems, such as the Copernicus Climate Change Service (C3S). Among other purposes, such forecasting systems are expected to deliver better-informed water management decisions. Using a pumped-storage reservoir system in the UK as a pilot application, we investigate the potential for using seasonal weather forecasts to simultaneously increase supply reliability and reduce pumping costs. To this end, we develop a Real-Time Optimisation System (RTOS) that uses C3S seasonal weather forecasts to generate hydrological forecasts, and combine them with a reservoir simulation model and an evolutionary optimisation algorithm, to generate release and pumping decisions.

We evaluate the performances of the RTOS over historical periods and compare it to several benchmarks, including a simplified operation scheme that mimic the current operational procedures, and a RTOS that uses Ensemble Streamflow Predictions (ESP) in place of C3S seasonal forecasts. We also attempt at linking the improvement of system performances to the characteristic of hydrological conditions and forecasts properties. Ultimately, we aim at addressing key questions such as ‘To what extent improving forecast skill translates into an increase of the forecast value for water supply decisions?’ and ‘Does accounting for forecast uncertainty in optimization improve decisions?’.

16 May
at 10:15

Room: LT

Understanding the intraseasonal variability over Indian region and development of an operational extended range prediction system

Speaker: Dr Sahai (ITM, India)

### Abstract

Extended range forecast of sub seasonal variability beyond weather scale is a critical component in climate forecast applications over Indian region. The sub-seasonal to seasonal (s2s) project, undertaken by WCRP, started in 2013 to improve the forecast beyond weather scale which is a challenging gap area in research and operational forecast domain. The primary objective of this s2s project is to provide the sub-seasonal to seasonal forecast in various lead times.

The prediction of weather and climate in the extended range (i.e. 2-3 weeks in advance) is much in demand in the sectors depending on water resources, city planning, dam management, health management (e.g. protection against heat death) etc. This demand has grown up manifold in the last five years with the experimental implementation of dynamical extended range prediction system (ERPS) by Indian Institute of Tropical Meteorology (IITM), Pune. At the heart of ERPS is a forecast system based on the NCEP-CFSv2 Ocean-Atmosphere coupled dynamical model (hereafter CFS), which is configured to run in two resolutions (T382 and T126) and an atmospheric only version (hereafter GFS) configured to run with CFS sea surface temperature (SST) boundary condition that is bias corrected with observations. The initial conditions to run the model are generated through an in-house developed perturbation technique using NCMRWF(atmospheric) and INCOIS(ocean) data assimilation system. From every initial condition the model is run for the next 28 days and a multi ensemble forecast run is created. Forecast product variables are then separated for sector specific application with suitable post processing and downscaling based on advanced statistical techniques. The application of this forecast can be made in several allied fields like agro-meteorology, hydrometeorology, health sector etc. My talk will provide a brief overview of ERPS keeping the focus on few sector specific  applications.

15 May
at 10:30

Room: LT

Parallel in Time Integration Using PFASST

Speaker: Michael Minion (Lawrence Berkeley National Laboratory)

### Abstract

The Parallel Full Approximation Scheme in Space and Time (PFASST) is an iterative approach to parallelization for the integration of ODEs and PDEs in the time direction.  I will give an overview of the PFASST algorithm, discuss the advantages and disadvantages of PFASST compared to other popular parallel in time (PinT) approaches, and show some examples of PFASST in applications.  I will also explain the construction of a new class of PinT integrators that combine properties of exponential integrators and PFASST, including some preliminary results on the accuracy and parallel performance of the
algorithm.

13 May
at 11:00

Room: LT

Flood Forecasting and Inundation Mapping using the US National Water Model

Speaker: David R Maidment (University of Texas at Austin)

### Abstract

The US National Water Model forecasts flows on 5.2 million km of streams and rivers in the continental United States, divided into 2.7 million forecast reaches.  A Medium Range Forecast from this model for Hurricane Harvey prepared 3 days before the hurricane made landfall successfully predicted the spatial pattern of inland flooding in Texas.  A continental scale inundation map has been developed using the Height Above Nearest Drainage (HAND) method, and an associated cell phone app called Pin2Flood built that enables flood emergency responders to create their own flood inundation maps using the same HAND map base, thus connecting predictive and observational flood inundation mapping.

About the Presenter: David R Maidment is the Hussein M Alharthy Centennial Chair in Civil Engineering at the University of Texas at Austin, where he has served on the faculty since 1981.  He received his BE degree from the University of Canterbury in Christchurch, New Zealand, and his MS and PhD degrees from the University of Illinois.  In 2016, he was elected to the US National Academy of Engineering for application of geographic information systems to hydrologic processes.

21 March
at 10:30

Room: LT

Constraining Stochastic Parametrization Schemes using High-Resolution Model Simulations

Speaker: Hannah Christensen (Oxford University)

### Abstract

Stochastic parametrizations are used in weather and climate models to represent model error. Designing new stochastic schemes has been the target of much innovative research over the last decade, with a focus on developing physically motivated approaches. We present a technique for systematically deriving new stochastic parametrizations or for constraining existing stochastic parametrizations. We take a high-resolution model simulation and coarse-grain it to the desired forecast model resolution. This provides the initial conditions and forcing data needed to drive a Single Column Model (SCM). By comparing the SCM parametrized tendencies with the evolution of the high-resolution model, we can measure the ‘error’ in the SCM tendencies. As a case study, we use this approach to assess the physical basis of the widely used ‘Stochastically Perturbed Parametrization Tendencies’ (SPPT) scheme using the IFS SCM. We provide justification for the multiplicative nature of SPPT, and for the large temporal and spatial scales used in the stochastic perturbations. However, we also identify issues with the SPPT scheme and motivate improvements. In particular, our results indicate that independently perturbing the tendencies associated with different parametrization schemes is justifiable, but that an alternative approach is needed to represent uncertainty in the convection scheme. It is hoped this new coarse-graining technique will improve both holistic and process-based approaches to stochastic parametrization.

20 March
at 10:30

Room: LT

About novel time integration methods for weather and climate simulations

Speaker: Martin Schreiber (Tech University of Munich)

### Abstract

Weather and climate simulations face new challenges due to changes in computer architectures caused by physical limitations. From a pure computing perspective, algorithms are required to cope with stagnating or even decreasing per-core speed and increasing on-chip parallelism. Although this leads to an increase in the overall on-chip compute performance, data movement is increasingly becoming the most critical limiting factor. All in all, these trends will continue and already led to research on partly disruptive mathematical and algorithmic reformulations of dynamic cores, e.g. using (additional) parallelism in the time dimension.

This presentation provides an overview and introduction to the variety of newly developed and evaluated time integration methods for dynamical cores, all aimed at improving the ratio of wall clock time to error:

First, I will begin with rational approximations of exponential integrator methods in their various forms: Terry Haut's rational approach of exponential integrators (T-REXI), Cauchy contour integral methods (CI-REXI) on the complex plane and their relationship to Laplace transformations, and diagonalized Butcher's Tableau (B-REXI).

Second, Semi-Lagrangian (SL) methods are often used to overcome limitations on stable time step sizes induced by nonlinear advection. These methods show superior properties in terms of dispersion accuracy, and we have used this property with the Parareal parallel-in-time algorithm. In addition, a combination of SL with REXI is discussed, including the challenges of such a formulation due to Lagrangian formulation.

Third, the multi-level time integration of spectral deferred correction (ML-SDC) will be discussed, focusing on the multi-level induced truncation of nonlinear interactions and the importance of viscosity in this context. Based on this, the "Parallel Full Approximation Scheme in Space and Time" (PFASST) adds a time parallelism that allows even higher accelerations on the time-to-solution compared to ML-SDC and traditional time integration methods.

All studies were mainly conducted based on the shallow water equations (SWE) on the f-plane and the rotating sphere to investigate horizontal aspects of dynamical cores for weather and climate simulation. Overall, our results motivate further investigation and combination of these methods for operational weather/climate systems.

(With contributions and more from Jed Brown, Francois Hamon, Richard Loft, Michael Minion, Matthew Normile, Nathanaël Schaeffer, Andreas Schmitt, Pedro S Peixoto).

12 March
at 11:15

Room: CC

Running serverless HPC workloads on top of Kubernetes and Jupyter notebooks

Speaker: Christopher Woods (University of Bristol)

6 March
at 10:30

Room: LT

Trends in data technology: opportunities and challenges for Earth system simulation and analysis

Speaker: V Balaji (Princeton Uni and NOAA/GFDL)

### Abstract

Earth system modeling, since its origin at the dawn of modern computing, has operated at the very limits of technological possibility. This has led to tremendous advances in weather forecasting, and the use of models to project climate change both for understanding the Earth system, and in service of downstream science and policy. In this talk, we examine changes in underlying technology, including the physical limits of miniaturization, the emergence of a deep memory-strategy hierarchy, which make "business as usual" approaches to simulation and analysis appear somewhat risky. We look simultaneously at trends in Earth system modeling, in terms of the evolution of globally coordinated climate science experiments (CMIP-IPCC) and the emergence of "seamless prediction", blurring the boundaries between weather and climate. Together, these point to new directions of research and development in data software and data science. Innovative and nimble approaches to analysis will be needed. Yesterday's talk examines this in the context of computational science and software, but it seems apparent that computation and data are inseparable problems, and a unified approach is indicated.

6 March
at 14:00

Room: LT

Statistics for Natural science in the age of Supercomputers

Speaker: Dutta Ritabrata (Warwick University)

### Abstract:

To explain the fascinating phenomenons of nature, natural scientists develop complex models which can simulate these phenomenons almost close to reality. But the hard question is how to calibrate these models given the real world observations. Traditional statistical methods are handicapped in this setup as we can not evaluate the likelihood functions of parameters of this models. In last decades or so, that statisticians answer to these questions has been approximate Bayesian computation (ABC), where the parameters are calibrated by comparing simulated and observed data set in a rigorous manner. Though it only became possible to apply ABC for realistic and hence complex models when it was efficiently combined with High Performance Computing (HPC). In this work, we will focus on this aspect of ABC, by showing how it was able to calibrate expensive models of epidemics on networks, of molecular dynamics, of platelets deposition in blood-vessels, of passenger queue in airports or volcanic eruption. This was achieved using standard MPI parallelization, nested MPI parallelization or nested CUDA parallelization inside MPI. Finally, we want to raise and discuss the open-questions regarding how to evolve and strengthen this inferential methods when each model simulation takes a full day or a resource equivalent to the best supercomputers of today.

5 March
at 10:30

Room: LT

Machine learning and the post-Dennard era of climate simulation

Speaker: V Balaji (Princeton Uni and NOAA/GFDL

### Abstract

In this talk, we examine approaches to Earth system modeling in the post-Dennard era, inspired by the industry trend toward machine learning (ML). ML presents a number of promising pathways, but there remain challenges specific to introducing ML into multi-phase multi-physics modeling. A particular aspect of such 'multi-scale multi-physics' models that is under-appreciated is that they are built using a combination of local process-level and global system-level observational constraints, for which the calibration process itself remains a substantial computational challenge. These include, among others: the non-stationary and chaotic nature of climate time series; the presence of climate subsystems where the underlying physical laws are not completely known; and the imperfect calibration process alluded to above. The talk will present ideas and challenges and the future of Earth system models as we prepare for a post-Dennard future, where learning methods are poised to play an increasingly important role.

21 January
at 11:00

Room: LT

ESSPE: Ensemble-based Simultaneous State and Parameter Estimation for Earth System Data-Model Integration and Uncertainty Quantification

Speaker: Fuqing Zhang (Pennsylvania State University)

### Abstract

Building on advanced data assimilation techniques, we advocate to develop and apply a generalized data assimilation software framework on Ensemble-based Simultaneous State and Parameter Estimation (ESSPE) that will facilitate data-model integration and uncertainty quantification for the broad earth and environmental science communities. This include, but not limited to, atmospheric composition and chemistry, land surface, hydrology, and  biogeochemistry, for which many of the physical and chemical processes in their respective dynamic system models rely heavily on parametrizations. Through augmenting uncertain model parameters as part of the state vector, the ESSPE framework will allow for simultaneous state and parameter estimation through assimilating in-situ measurements such as those from the critical-zone ground-based observational  networks and/or remotely sensed observations such as those from radars and satellites. Beyond data model integration and uncertainty quantification, through systematically designed ensemble sensitivity analysis, examples will be given to the application of the ESSPE framework to: (1) identify key physical processes and their significance/impacts and to better represent and parameterize these processes in dynamical models of various earth systems; (2) design better observation strategies in locating the optimum sensitive regions, periods and variables to be measured, and the minimum accuracies and frequencies of these measurements that are required to quantify the physical processes of interest; explore the impacts of heterogeneity and equifinality; (3) understand predictability and nonlinearity of these processes, and parameter identifiability; and (4) facilitate upscale cascading of knowledge from smaller-scale process understanding to larger-scale simplified representation and parametrization. I will end the presentation with an introduction on the preliminary findings from our ongoing collaborations with ECMWF on using the data assimilation methodology to identify potential deficiencies in the convective gravity drag parametrization that led to  stratospheric temperature biases in the operational model, and the potential pathways for using SSPE to improve model physics in the future.

25 January
at 10:30

Room: LT

Windstorm and Cyclone Events: Atmospheric Drivers, Long-term Variability and Skill of current Seasonal Forecasts

Speaker: Daniel J Befort (University of Oxford)

### Abstract

In this study, observed long-term variability of wind storm events is analysed using two state-of-the-art 20th century reanalyses called ERA-20C and NOAA-20CR. Long-term trends partly differ drastically between both datasets. These differences are largest for the early 20th century, with a higher agreement for the past 30 years. However, short-term variability on sub-decadal time-scales is in much better agreement especially over parts of the northern hemisphere. This suggests that these datasets are useful to analyse drivers of interannual variability of windstorm events  as these simulations allow to extend the time-period covered by common reanalyses as e.g. ERA-Interim.

ERA-20C is used to analyse the relationship between atmospheric and oceanic conditions on windstorm frequency over the European continent. It is found that large parts of their interannual variability can be explained by few atmospheric patterns, including the North Atlantic Oscillation (NAO) and the Scandinavian pattern. This suggests that it is crucial to capture these atmospheric modes of variability e.g. in seasonal forecast systems to reasonably represent windstorm variability over Europe.

The skill in windstorms and cyclones is analysed for three modern seasonal forecast systems: ECMWF-S3, ECMWF-S4 and GloSea5. Whereas skill for cyclones is generally small, significant positive skill of ECMWF-S4 and GloSea5 is found for windstorms over the eastern North Atlantic/western Europe. Further to analysing skill in windstorms using a dedicated tracking algorithm, it is also tested in how far the NAO can be used as a predictor for their variability. Results suggest that using the NAO adds some skill over northern Europe, however, using the whole model information by tracking windstorm events is superior over large parts over the eastern Atlantic and western Europe.

7 January
at 10:30

Room: LT

When fossil fuel emissions are no longer perfect in atmospheric inversion systems

Speaker: Thomas Lauvaux (LSCE, Saclay, France)

### Abstract

The biogenic component of greenhouse gas fluxes remains the primary source of uncertainties in global and regional inversion systems. But recent results suggest that anthropogenic greenhouse gas emissions from fossil fuel use, so far assumed perfect at all scales, represent a larger fraction of the uncertainties in these systems, and can no longer be ignored. Inversion systems capable of reducing fossil fuel uncertainties are discussed in parallel with planned observing systems deployed across the world and in space. The remaining challenges and recent advances are presented to not only infer fossil fuel emissions but to provide support to climate policy makers at national and local scales.

Uncertainty quantification of pollutant source retrieval: comparison of Bayesian methods with application to the Chernobyl and Fukushima Daiichi accidental releases of radionuclides

Speaker: M Bocquet (CEREA, France)

### Abstract

Inverse modeling of the emissions of atmospheric species and pollutants has significantly progressed over the past fifteen years.  However, in spite of seemingly reliable estimates, the retrievals are rarely accompanied with an objective estimate of their uncertainty, except when Gaussian statistics are assumed for the errors which is often unrealistic.  I will describe rigorous techniques meant to compute this uncertainty in the context of the inverse modeling of the time emission rates -- the so-called source term -- of a point-wise atmospheric tracer.  Lognormal statistics are used for the positive source term prior and possibly the observation errors, which precludes simple Gaussian statistics-based solutions.

Firstly, through the so-called empirical Bayesian approach, parameters of the error statistics -- the hyperparameters -- are estimated by maximizing the observation likelihood via an expectation-maximization algorithm. This enables the estimation of an objective source term.  Then, the uncertainties attached to the total mass estimate and the source rates are estimated using four Monte Carlo techniques: (i) an importance sampling based on a Laplace proposal, (ii) a naive randomize-then-optimize (RTO) sampling approach, (iii) an unbiased RTO sampling approach, (iv) a basic Markov chain Monte Carlo (MCMC) simulation. Secondly, these methods are compared to a full Bayesian hierarchical approach, using an MCMC based on a transdimensional representation of the source term to reduce the computational cost.

I will apply those methods, and improvements thereof, to the estimation of the atmospheric cesium-137 source terms from the Chernobyl nuclear power plant accident in April/May 1986 and Fukushima Daiichi nuclear power plant accident in March 2011.

## 2018

1 February
at 13:30

Room: LT

Using All-Sky Satellite Infrared Brightness Temperatures for Model Verification and in Ensemble Data Assimilation Systems

Speaker: Jason Otkin (Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison, USA)

### Abstract

Infrared sensors onboard geostationary satellites provide detailed information about the cloud and water vapor fields with high spatial and temporal resolutions that make them very useful for model verification and within data assimilation systems. In the first part of this talk, results will be shown from several recent studies that used GOES infrared brightness temperatures to assess the accuracy of cloud and water vapor forecasts generated by the High Resolution Rapid Refresh (HRRR) model in real-time and as part of longer-term verification studies. The real-time GOES-based verification system provides operational forecasters objective tools to quickly assess the accuracy of current and prior HRRR model forecasts when they are creating or updating their short-range forecasts. For long-term verification, the forecast accuracy is assessed using a variety of statistical methods ranging from standard grid point metrics to neighborhood-based methods such as the Fractions Skill Score to more sophisticated object-based verification tools. Overall, the results show that the simulated brightness temperatures are too warm during the first hour of the forecast, indicating that the HRRR model initialization is deficient in upper-level clouds. This warm bias, however, is quickly replaced by a large cold bias due to the rapid generation of upper-level clouds with the negative bias often lasting for several hours before the excess cloud cover dissipates. The object-based analysis showed that the HRRR initialization contains too many small cloud objects; however, the number of cloud objects becomes too low by forecast hour 2. This behavior is consistent with the changes in the simulated brightness temperatures and indicates that the forecast cloud objects become too large after a few hours.

In the second part of this talk, output from a high-resolution ensemble data assimilation system (KENDA) is used to assess the ability of a nonlinear bias correction (NBC) method that uses a Taylor series polynomial expansion of the observation-minus-background departures to remove linear and nonlinear conditional biases from all-sky SEVIRI infrared brightness temperatures. Univariate and multivariate NBC experiments were performed in which the satellite zenith angle and variables sensitive to clouds and water vapor were used as the bias correction predictors. The results showed that even though the bias of the entire error distribution is equal to zero regardless of the order of the Taylor series expansion, that there are often large conditional biases that vary as a nonlinear function of the predictor value. The linear 1st order Taylor series term had the largest impact on the entire distribution as measured by reductions in the variance; however, large conditional biases often remained across the distribution. These conditional biases were typically reduced to near zero after the nonlinear 2nd (quadratic) and 3rd (cubic) order terms were used. The results showed that variables sensitive to cloud top height are effective bias predictors especially when higher order Taylor series terms are used. Comparison of statistics compiled for clear-sky and cloudy-sky matched observations revealed that nonlinear bias corrections are more important for cloudy-sky observations as signified by the much larger impact of the 2nd and 3rd order terms on the conditional biases.

8 February
at 10:30

Room: LT

The potential of satellites and assimilation to quantify climate forcing, feedbacks and prediction in the Earth System: application to atmospheric chemistry and the carbon cycle

Speaker: Kevin Bowman (JPL, Pasadena, USA)

### Abstract

Anthropogenic activities since the industrial revolution have led to profound changes in atmospheric composition (e.g., carbon dioxide, methane and tropospheric ozone) and consequently the trajectory of our climate. However, the coupling of these constituents must be quantified in order to assess the efficacy of climate mitigation strategies against the backdrop of natural variability and climate feedbacks. The last decade has witnessed the launch of satellite constellations that measure Earth’s atmosphere, land, and oceans with a concomitant advance in data assimilation approaches to link these data to Earth System processes.

Using these approaches, we have attributed ozone and methane radiative forcing to global emissions at large urban scales. By incorporating both methane emissions and chemical losses, we show that the top 10% of locations with positive net methane RF are responsible for 50% of the global positive RF and the top 10% of locations with negative RF cause 60% of the global negative RF based upon an RCP 6.0 trajectory through 2050.

To understand the role of the carbon cycle in controlling the most important greenhouse gas, the NASA Carbon Monitoring System Flux (CMS-Flux) project was initiated as a coordinated effort between land surface, ocean, fossil fuel, and atmospheric scientists to develop a comprehensive a carbon cycle data assimilation system. Based upon this system, we attribute the historic atmospheric CO2 growth rate during the 2015 El Nino to spatially-resolved fluxes.  We show how tropical productivity and respiration processes related to anomalously high climate variability, i.e., “extreme” events, are responsible for this growth rate and their implications for carbon-climate feedbacks.

Emergent constraints have been become an active area of research that use contemporary observations to constrain climate projections.  We have developed a Bayesian formulation of this approach that explicitly accounts for the uncertainty in observations and the uncertainty between the future and present state. We explore the potential of this framework for tropospheric ozone radiative forcing and the carbon cycle.

Taken together, these advances in observations, modeling, and the methodologies to link them point to a scientifically rigorous and policy-relevant framework critically needed for the international community to address climate change.

Dr Kevin Bowman is the Principal Investigator of the EOS Aura Tropospheric Emission Spectrometer and the NASA Carbon Monitoring System (CMS-Flux) project.  He received a BEE from Auburn University in 1991, a Diplôme de Spécialisation en Traitement et Transmission des Informations at L'Ecole Supérieure d'Electricité (SUPELEC), Metz, FRANCE in 1993, and a Phd in Electrical Engineering from the Georgia Institute of Technology in 1996. He subsequently continued his career at the Jet Propulsion Laboratory in 1997.  His research is centered on understanding the processes controlling atmospheric composition and their impact on climate using satellite observations, modeling, and data assimilation techniques.  Dr Bowman's broad interests have led to publications in diverse fields including air quality, carbon cycle, chemistry-climate, atmospheric hydrology, and remote sensing science.  An avid musician and guitarist, Dr Bowman is a founding member of the JPL Jazz Propulsion Band.

22 February
at 11:00

Room: Council

Forecasting health hazards linked to heatwaves

Speaker:  Claudia di Napoli (Reading University)

### Abstract

In recent years severe and prolonged episodes of summer heat such as the 2003 European heatwave proved that extreme high temperatures are responsible for excessed mortality in affected areas, and Heat Health Warning Systems (HHWSs) need to be put in place to mitigate the negative impacts caused by hot weather extremes on human health.

A heatwave-associated HHSW is being developed as part of the pan-European multi-hazard early warning system constructed within the HORIZON2020 ANYWHERE project (EnhANcing emergencY management and response to extreme WeatHER and climate Events). The ANYWHERE HHSW is
based on the forecast of the Universal Thermal Climate Index (UTCI), a state-of-the-art biometeorological index representing the heat stress induced by the atmospheric environment on the human body. Using air temperature, humidity, wind and radiation from ECMWF high-resolution and ensemble prediction models, 10-day UTCI forecasts are computed daily via an operational procedure.

In this seminar the potential of UTCI forecast as a tool to predict heat-related health hazard will be explored. Heat stress conditions across Europe will be presented via UTCI maps computed from 38 years of ERA-Interim data. The association between the UTCI and summer mortality data from 17 European countries will be also discussed, and the UTCI’s ability to represent mortality patterns demonstrated for the 2003 European heatwave.

26 February
at 11:00

Room: LT

The Joint Effort for Data assimilation Integration

Speaker: Yannick Tremolet (JCSDA, USA)

### Abstract

The Joint Effort for Data assimilation Integration (JEDI) aims at providing a unified data assimilation framework for all partners of the Joint Center for Satellite Data Assimilation (JCSDA) and the data assimilation community in general. The long term objective is to provide a unified framework for research and operational use, for different components of the Earth system, and for different applications, with the objective of reducing or avoiding redundant work within the community and increasing efficiency of research and of the transition from development teams to operations.

One area where this is particularly important is the use of observations. As Earth observing systems are constantly evolving and new systems launched, continuous scientific developments for exploiting the full potential of the data are necessary. Given the cost of new observing systems and their limited lifetime, it is important that this process happens quickly. Reducing duplication of work and increasing collaboration between agencies in this domain can be achieved through Unified Forward Operators (UFO) and a common Interface for Observation Data Access (IODA).

Over the last decade or two, software development technology has advanced significantly, making routine the use of complex software in everyday life. The key concept in modern software development for complex systems is the separation of concerns. In a well-designed architecture, teams can develop different aspects in parallel without interfering with other teams’ work and without breaking the components they are not working on. Scientists can be more efficient focusing on their area of expertise without having to understand all aspects of the system. This is similar to the concept of modularity.  However, modern techniques (such as Object Oriented programming) extend this concept and, just as importantly, help enforce it uniformly throughout a code.

JEDI is based on the Object Oriented Prediction System (OOPS), encapsulating models and observations, which will be briefly described. Extensions towards sharing observations operators and observation related operations such as quality control across models using the UFO will also be described.

JEDI is a collaborative project with developers distributed across agencies and in several locations in different time zones. In order to facilitate collaborative work, modern software development tools are used. These tools include version control, bug and feature development tracking, automated regression testing and provide utilities for exchanging this information. The collaborative development process in JEDI will be presented before concluding with the status of the project.

14 March
at 10:30

Room: MZ

Global Surface Observations of Air Quality

Speaker: Martin G Schultz (Jülich Supercomputing Centre, Forschungszentrum Jülich)

### Abstract

The Tropospheric Ozone Assessment Report (TOAR) is an international effort to summarise the scientific knowledge on the distribution, trends and impacts of tropospheric ozone. TOAR has generated global metrics for assessing the impact of tropospheric ozone on climate change, human health and crop/ecosystems. To do this required collating ozone measurements from multiple locations, culminating in the largest database of surface ozone measurements. Martin will talk about the challenges in constructing the database, its use in quantifying ozone impacts, as well as future opportunities for Earth system science (e.g. TOAR-II) and information/data science.

20 March
at 10:30

Room: LT

Dynamics and predictability of sudden stratospheric warmings

Speaker: Thomas Birner (LMU)

### Abstract

Abrupt breakdowns of the polar winter stratospheric circulation such as sudden stratospheric warmings (SSWs) are a manifestation of strong two-way interactions between upward propagating planetary waves and the mean flow. The importance of sufficient upward wave activity fluxes from the troposphere and the preceding state of the stratospheric circulation in forcing SSW-like events have long been recognized. Past research based on idealized numerical simulations has suggested that the state of the stratosphere may be more important in generating extreme stratospheric events than anomalous upward wave fluxes from the troposphere. Other studies have emphasized the role of tropospheric precursor events.

In this talk we will first discuss the sensitivity of SSWs to stratospheric conditions prior to the event based on specifically designed hindcast experiments of selected SSWs modeled by a comprehensive climate model. It is found that a given tropospheric evolution concomitant with the development of an SSW does not uniquely determine the occurrence of an event and that the stratospheric conditions are relevant to the subsequent evolution of the stratospheric flow toward an SSW, even for a fixed tropospheric evolution. We will then discuss results based on reanalysis data, which are used to define events of extreme stratospheric mean flow deceleration (SSWs being a subset) and events of extreme lower tropospheric upward planetary wave activity flux. While the wave fluxes leading to SSW-like events ultimately originate near the surface, the anomalous upward wave activity fluxes associated with these events primarily occur within the stratosphere. The crucial dynamics for forcing SSW-like events appear to take place in the communication layer just above the tropopause. Anomalous upward wave fluxes from the lower troposphere may play a role for some events, but seem less important for the majority of them.

20 March
at 14:00

Room: LT

On the dynamical mechanisms governing El Nino-Southern Oscillation regularity

Speaker: Judith Berner (NCAR, USA)

### Abstract

This study investigates the mechanisms by which short timescale perturbations to atmospheric processes can affect El Nino-Southern Oscillation (ENSO) in climate models. To this end a control simulation of NCAR's Community Climate System Model is compared to a simulation in which the model's atmospheric diabatic tendencies are perturbed every time step using a Stochastically Perturbed Parametrized Tendencies (SPPT) scheme. The SPPT simulation compares better with the ERA20C reanalysis in having lower inter-annual sea surface temperature (SST) variability, shorter memory, and more irregular transitions between El Nino and La Nina states than the control simulation.

Reduced-order linear inverse models (LIMs) derived from the 1-month lag covariances of selected tropical variables yield good representations of tropical interannual variability in the two simulations. In particular, the basic features of ENSO are captured by the LIM's least-damped oscillatory eigenmode. The impact of SPPT is consistent with perturbations to the frequency of this eigenmode, causing a noise-induced stabilization. This reduces the mode's damping timescale from 21 to 15 months, in better agreement with the 8 months obtained from the reanalysis. The stabilization also explains the reduced SST variance and broader SST spectrum (that is, greater ENSO irregularity) obtained in the SPPT simulation.

Although the improvement in ENSO shown here was achieved through stochastic physics parametrizations, it is possible that similar improvements could be realized through changes in deterministic parametrizations or higher numerical resolution. It is suggested LIMs could provide useful insight into model sensitivities, uncertainties, and biases also in those cases.

22 March
at 13:00

Room: MR2

City-scale real-time surface water flood nowcasting/forecasting for enhanced emergency response

Speaker: Dapeng Yu & R Wilby (Loughborough University, UK)

### Abstract

Emergency services (such as Fire & Rescue, and Ambulance) often face the challenging tasks of having to respond to and operate under extreme and fast changing weather conditions, including surface water flooding. UK-wide, return period based surface water flood risk mapping undertaken by the Environment Agency provides useful information about areas at risks. Although these maps are useful for planning purposes for emergency responders, their utility for operational response during flood emergencies can be limited.

A high-resolution (street-level), real-time, surface water flood nowcasting/forecasting system, has been established for 33 cities/regions (and growing) around the world, including 30 in the UK, New York City, Houston and Shanghai, readily adoptable by any city/region. Precipitation nowcasting/forecasting products over 7- and 36-hour horizons are used as inputs to the system. A hydro-inundation model (FloodMap) is used to simulate urban surface water flood inundation at various scales, with varying spatial resolutions between 2-50 m, and a 15-minute temporal resolution.

Based on the system developed, we are able to evaluate the direct and indirect impacts of surface water flooding on emergency responses in cities, including: (i) identifying vulnerable population groups (e.g. care homes and schools) directly at risk; and (ii) generating novel metrics of accessibility (e.g. travel time from service stations to vulnerable sites; spatial coverage with certain legislative timeframes) in real-time (work in progress). The system allows real-time, actionable flood impact nowcasting/forecasting (both direct and indirect) to be communicated to emergency responders and city managers, thereby improving their operational resilience.

6 April
at 11:00

Room: MR1

Towards seamless water forecasting in Australia

Speaker: Narendra Kumar Tuteja (Bureau of Meteorology, Australia)

### Abstract

Australia has experienced marked climate extremes over the first decade of the 21st century. Its streamflow regime can go through prolonged periods of droughts such as the “Millennium drought” that occurred between 1997 and 2009 across eastern Australia. This extreme dry period was followed by back-to-back La Niña years during 2010-11 and 2011-12, when Australia experienced severe flood events. This variability in extremes has a profound impact on the management of water resources in Australia, key drivers being managing community safety from floods on the one hand and managing water scarcity from droughts on the other hand to minimise the risks related to water supply for urban, irrigation and environmental needs. The Bureau is working actively and cooperatively with all key stakeholders and end users to develop, implement and deliver end-to-end seamless water forecasting services to minimise the impacts of climate variability.

The Bureau’s Flood Forecasting and Warning service provides forecasts of expected river heights across Australia. Under the Water Act (2007), the Bureau is working with water managers across Australia to deliver timely, accurate and reliable seamless water availability forecasts across Australia at seven day and seasonal time scales (http://www.bom.gov.au/water/7daystreamflow; http://www.bom.gov.au/water/ssf). A new service for streamflow, sediment and pollutant fluxes to the Great Barrier Reef is currently under development (http://ereefs.org.au/ereefs).

In this seminar the rationale, progress-to-date and challenges involved in developing and delivering operational water forecasts for Australia will be discussed.

Biographical information

Dr Narendra Kumar Tuteja is manager of the Water Forecasting Services at the Bureau of Meteorology in Australia. He is responsible for development and delivery of the water availability forecast services for Australia, delivering 7 day and seasonal streamflow forecasts as well as long-term water availability trends. His work has supported development of policies and decision making in the water sector. He obtained his PhD from the National University of Ireland in 1996. He is the Advisory Working Group member of the World Meteorological Organisation (WMO) Commission for Hydrology. He is involved in many significant water resources information and management projects across industry and academia in Australia and overseas.

10 April
at 10:30

Room: Council

Supercooled liquid clouds over the Southern Ocean: From processes to cloud feedback

Speaker: Andrew Gettelman (NCAR)

### Abstract

The Southern Ocean Clouds Radiation Aerosol Transport Experimental Study (SOCRATES) is measuring from Hobart to the south with a combination of aircraft, ship and station data from Hobart in January and February 2018. One of the major goals of SOCRATES is to understand S. Ocean supercooled liquid and mixed phase clouds. These clouds are important for climate, and may also change as the structure of the atmosphere over the S. Ocean evolves due to climate change. Global models have traditionally struggled to represent these clouds. This talk with show some preliminary SOCRATES data from flights over the S. Ocean, and show how we will link it to global model simulations of cloud microphysical processes, mean climate, and even cloud feedbacks over the S. Ocean. Preliminary implications for how we can modify global model cloud microphysics will be discussed.

12 April
at 10:30

Room: LT

Speaker: Bruce Ingleby (ECMWF)

### Abstract

A brief introduction to radiosondes will cover the measurement techniques, processing and their uncertainties.  One significant daytime uncertainty is the effect of solar radiation on measured stratospheric temperatures, well documented by Dirksen et al. (2014).

There is a migration underway from alphanumeric TEMP reports to binary BUFR reports.  BUFR allows for the reporting of high vertical resolution data and the position of each level (currently available from over 30% of global radiosonde stations).  Accounting for the radiosonde drift in NWP systems improves the upper level fit between radiosondes and model fields and also the forecasts.  This will become operational at ECMWF in June 2018.

Recent work at ECMWF looking at observation-minus-background (O-B) statistics has shown some variations in quality between different radiosonde types (manufacturers), more for temperature and humidity than wind, and this is reflected in new observation uncertainties introduced operationally at ECMWF.
There are also clear variations of O-B statistics with latitude, with larger differences in the tropical stratosphere probably related to gravity wave activity.

In the EU Horizon 2020 GAIA-CLIM project ECMWF and the Met Office looked at the use of radiosonde data as a reference - for both Numerical Weather Prediction systems and satellite sounding data.  Biases (in both the observations and models) will be briefly discussed and also recent vertical correlation results derived using the Desroziers et al (2005) technique.

24 May
at 13:30

Room: LT

Possible future ensemble configurations

Speakers: M Leutbecher and F Vitart (ECMWF)

### Abstract

Both spatial resolution and ensemble size are main factors determining the cost of operational forecasts. Should ECMWF reduce the ensemble size to achieve the ambitious strategic goal of a medium-range ensemble with 5-kilometre horizontal resolution by 2025? Fewer members will imply reduced skill. Will the resolution increase be able to compensate for that? The combination of subsequent ensemble forecasts, i.e. lagged ensembles, has been proposed to mitigate the impact of reducing ensemble size.  In addition, the combination of ensembles with different horizontal resolutions is explored.  Initial work has looked at dual-resolution configurations with a mix of higher-resolution members and lower-resolution members. What is the optimum mix of higher and lower-resolution members for the probabilistic skill when the computational cost is constrained? The optimum mix of higher-resolution and lower-resolution members is studied for direct combination of raw forecasts, for combinations with optimum weights and for calibrated ensembles using quantile mapping as well as ensembles calibrated with EMOS. Multi-resolution approaches are also starting to be explored in the context of the initialisation of the ensemble. The first talk gives an overview of on-going work with a focus on the medium-range.

ECMWF extended-range forecasts are currently issued in burst mode from a 51-member ensemble which is integrated for 46 days twice a week (every Monday and Thursday).  This methodology is not optimal for users who need extended range forecasts on other days than Mondays and Thursdays.  Another approach, operational at NCEP, UKMO and CMA, consists in running smaller ensembles every day and issuing the forecasts in lag mode by combining the most recent forecasts with forecasts produced the preceding days. The second talk will discuss the advantages and disadvantages of both methods (lag vs burst ensemble) for extended range forecasts and will estimate what would be the minimum daily ensemble size and optimal lag window in order to obtain a lag ensemble as skilful as the current 51-member ensemble on Mondays and Thursdays. Following this estimation, several possible configurations of the real-time extended-range forecast ensemble will be proposed for the next HPC in Bologna. Other possible changes to the extended range configuration could include running extended-range forecasts separately from medium-range at legB resolution from step 0 (as before 2008), changing the frequency and ensemble size of the re-forecasts.

20 June
at 10:30

Room: LT

A turbulence scheme with two prognostic turbulence energies

Speaker: Ivan Bastak Duran (Goethe University, Frankfurt)

### Abstract

A new turbulence scheme with prognostic equations for two turbulence energies is presented.  The scheme is an extension of a Turbulence Kinetic Energy (TKE) scheme with an additional prognostic energy, which represents the effects of  temperature and moisture variances in compact form. The extension is inspired by the ideas of Zilitinkevich et al (2013), but the two-energies turbulence scheme is valid for the whole stability range and includes the influence of moisture. The additional turbulence prognostic energy is used only for the calculation of the stability parameter. Thus the two-energies scheme is similar to a standard TKE scheme in that the turbulent fluxes are down-gradient and proportional to the local gradients of the diffused variables. However, the energy-dependent stability parameter is not anymore strictly local and obtains a prognostic character. These characteristics enable the scheme to model both turbulence and clouds in the Planetary Boundary Layer (PBL).

The two-energies scheme was implemented in the Integrated Forecast System (IFS) model developed at the European Centre for Medium-Range Weather Forecasts (ECMWF). The scheme was tested in idealized Single Column Model (SCM) simulations and long-term three-dimensional global simulations. Overall, the scheme performs better than the standard TKE schemes and is able to model both turbulence and shallow convection in the PBL. Long-term three-dimensional global simulations show that the turbulence scheme behaves reasonably well in a full atmospheric model. Compared to the operational turbulence and shallow convection parametrization in IFS, the two-energies scheme shows a more continuous behaviour in time and space, but tends to overestimate cloud cover, especially at low levels.

2 July
at 13:30

Room: LT

Ocean data assimilation challenges for both reanalysis and regional operational applications

Speaker: Andrea Storto (CMRE, Italy)

### Abstract

We review in this presentation a few aspects of ocean data assimilation emerging from both global reanalysis and regional operational oceanographic applications.

First, we present current challenges in ocean reanalyses and propose methods to overcome them, looking in particular at methods to limit model drifts, enhance global budget consistency and introduce flow-dependent aspects in data assimilation.

In addition, we show the added value of the ensemble spread in the multi-system reanalysis ensemble from the Copernicus Marine Service to quantify the ocean uncertainty and feed an hybrid ensemble-variational analysis scheme.

Second, we introduce sea-trial activities conducted at CMRE and the related modeling and data assimilation activities, focusing in particular on the challenges of high-resolution ocean data assimilation. Preliminary results from ensemble variational data assimilation with a newly developed stochastic physics package and multi-scale data assimilation will be shown and discussed.

10 July
at 11:30

Room: MZ

Hydrometeorological applications in poorly observed regions and tropical basins : combining satellite observations and complementary techniques using the telecommunication network - examples in Central and West Africa with a focus on the Niger   river basin

Speaker: Marielle Gosset (IRD, GET, France)

### Abstract

As floods  are becoming more frequent  in many African cities and  rural areas, the impact of these events on population and  socio-economical activities is a growing concern. To monitor and predict such intense   hydrometeorological events, access to quantitative information on rainfall down to the convective scales is a key - especially to analyse the impact  of these events on cities. IRD, CNES and local partners are developing pilot studies on hydrometeorological monitoring/prediction combining satellite information, hydrological modeling and also integrating the use of commercial microwave links  (CMLs) from mobile telecommunication networks for high resolution rain estimation. The quantitative results obtained in several countries in west/central Africa  using this technique  will be presented and further development and possible collaboration on this topic in link with ECMWF activities will be discussed.

19 July
at 14:00

Room: MR1

Model biases and seasonal forecasting

Speaker: Tim Woollings (Oxford University)

### Abstract

It is hoped that improvements in models will lead to reduced biases compared to observations, and that this will follow on to enhance the skill of seasonal forecasting systems. This talk will give an overview of some model biases relevant to the midlatitude jets and investigate how these biases might be affecting seasonal forecast skill, with examples from both winter and summer hindcasts.

23 July
at 10:30

Room: LT

Speakers: T Kubota, K Furukawa (JAXA, Japan), Y Ikuta (JMA), A Geer (ECMWF)

### Abstract

1. Overview of JAXA satellite missions

This talk will provide overview of the Japan Aerospace Exploration Agency (JAXA) satellite missions, such as the "SHIZUKU" (GCOM-W) satellite carrying the AMSR2 instrument, Greenhouse gases observing satellite GOSAT "IBUKI", in addition to the Global Precipitation Measurement (GPM) mission. Recently, "SHIKISAI" (GCOM-C) satellite carrying the SGLI instrument was launched on Dec. 2017, and its data will be open to the public soon. Furthermore, the GOSAT-2 mission and EarthCARE with the ESA are planned to be launched in future. Here, various datasets from the JAXA satellite missions will be introduced briefly.

2. GPM/DPR utilization overview

The Global Precipitation Measurement (GPM) mission is an international collaboration to achieve highly accurate and highly frequent global precipitation observations. The GPM mission is composed of a Tropical Rainfall Measuring Mission (TRMM)-like non-sun-synchronous orbit satellite (GPM Core Observatory) jointly developed by U.S. and Japan and constellation of satellites carrying microwave radiometer instruments provided by the GPM partner agencies. The GPM Core Observatory, launched on February 2014, carries the Dual-frequency Precipitation Radar (DPR) by the Japan. The DPR consists of two radars; Ku-band precipitation radar (KuPR) and Ka-band radar (KaPR), and is expected to advance precipitation science by expanding the coverage of observations to higher latitudes than those of the TRMM Precipitation Radar (PR), measuring snow and light rain by the KaPR, and providing drop size distribution information based on the differential attenuation of echoes at two frequencies. This talk will provide recent results of the GPM/DPR utilization.

3. DPR assimilation at JMA

The GPM/DPR can observe three dimensional distribution of reflectivity all over the earth. In numerical weather prediction (NWP) system, a skillful assimilation of such observation data provides improvement of precipitation forecast. Therefore, the Japan Meteorological Agency (JMA) has been developing the space-born radar assimilation, introducing GPM/DPR in the operational regional NWP system in March 2016 as its first operational assimilation of space-borne radar data. In the GPM/DPR assimilation, vertical humidity profiles are retrieved from the DPR reflectivity profiles using Bayesian theory. Then, the 1-dimensional (1D) relative humidity profiles thus obtained are assimilated in 4-dimensional variational (4DVAR) data assimilation system. This method called 1D+4DVAR is also used for assimilation of ground-based weather radar at JMA. In the performance evaluation tests of the GPM/DPR assimilation, improvement of typhoon and precipitation forecast was demonstrated. These results of performance evaluation test and future plans of development for GPM/DPR assimilation will be presented.

4. Plans for DPR assimilation at ECMWF

Assimilation of DPR reflectivities at ECMWF would be a natural next step following the assimilation of all-sky microwave radiances and NEXRAD gauge-radar precipitation composites. It would improve the initialisation of tropical cyclones, frontal precipitation and convection systems in both the topics and extratropics. In addition, height-resolved precipitation observations would help further constrainmicrophysical assumptions in the forecast model and in the observation operator. Reflectivities would be assimilated directly into 4D-Var using RTTOV-SCATT version 13, which for the first time will have a radar capability. DPR assimilation will also benefit from preparations being made for the assimilation of the EarthCARE cloud radar.

5. DPR follow-on sensor discussions

JAXA completed the Prime mission phase of the GPM/DPR at the end of November 2017 and moved the Extended mission phase. Now discussions of the DPR follow-on sensor are very active in the JAXA. Recently, the US Decadal Survey 2017 recommended the Clouds, Convection and Precipitation (CCP) mission should be one of 5 designated missions (highest priority), and so we already started to talk with the NASA for possible collaboration in the CCP mission. We’re now studying specifications of the DPR follow-on sensor, such as making the observation width twice (500 km), and opinions from users will be important. Here, we’d like to introduce our recent activity and discuss the DPR follow-on sensor with ECMWF.

25 July
at 10:30

Room: LT

The emerging role of the land surface in weather and climate prediction

Speaker: Paul Dirmeyer (COLA, USA)

### Abstract

Like the ocean, the land surface is a slow manifold relative to the atmosphere that provides predictability and prediction skill across a range of time scales.  Although the peak influence of land surface states is in the “subseasonal” time range between 1-3 weeks, significant impact of land, or errors in its representation, begins in forecasts at the first morning of simulation. The process chains that link soil moisture, vegetation, snow, and other land states through the energy and water cycles manifest through their effects on the growing daytime boundary layer, cloud formation and convection.  Thus, the diurnal cycle is key to assessing and improving model performance related to land-atmosphere interactions.  Daily, monthly and seasonal mean skill arising from coupled land-atmosphere feedbacks can only improve by improving the diurnal cycle. We show evidence of land surface impacts on prediction skill from a variety of global models and highlight current shortcomings that may inform model development.

24 September
at 10:30

Room: MR1

Middle atmosphere dynamic, needs and future infrastructures for observations

Speaker: Philippe Keckhut (UVSQ/LATMOS)

### Abstract

The middle atmosphere has been poorly investigated for a long time, except the stratosphere and related ozone chemistry issues. Atmospheric waves carry energy and momentum from one region to another. While atmospheric dynamics and the vertical wave interactions exhibit unresolved questions and while new numerical simulations cover a larger vertical range, high-resolution observations are highly required to addressed these issues and improve our understanding and models. A key part of this interaction is the understanding of the role of atmospheric oscillations, particularly tides, gravity and planetary waves, in driving this interaction. Critical to understanding and prediction of sudden stratospheric warming events is to understand the location and structure of shear-zones in the mean-flow where planetary waves break. Most small-scale gravity waves are not resolved by typical climate models and only partially resolved by weather forecasting models. Climate models therefore must parameterize gravity waves to ensure an accurate simulation of middle and upper atmosphere mean climate and variability. Many parameters of the gravity wave parametrizations and particularly gravity wave source parameters are uncertain due to a lack of long-term high-resolution observations.

ARISE (Atmospheric dynamics Research Infrastructure in Europe) is an European infrastructure providing multi-instrumental and multi-sites observations from equator to poles. Some complementary instruments are located on super sites, like lidar, radar and spectrometers, while other provide à global coverage like the infrasonic network. Good progress has been obtained during the last decade and can be expected from a sustainable ARISE infrastructure, in atmospheric modelling, weather forecasting and monitoring of extreme events in relation with civil security applications, from its new 3D images of atmospheric state and its spatial and temporal variability.

The amplitudes of the atmospheric tides are large in the middle atmosphere. Tides generated by stratospheric ozone and by the water vapor in the upper troposphere, can induce some systematic differences between non-simultaneous measurements and represent a key issue for satellite validation and long-term variability when times of measurements are changing. Actual instruments are not numerous and suffer from discontinuities. Temperature trends in the lower and middle stratosphere during the last decade are evaluated using ground-based Lidar, GPS Radio Occultation (RO) and Aqua Advanced Microwave Sounding Unit (AMSU). While trends have slowdown around the 2000’s, in the last decade the stratospheric temperature observations show that atmosphere continue to cool over most of the globe with a rate ranging from -0.4 to -0,7 K/decade. New type of observations can be obtained from space by miniaturized instruments. A possible strategy consists of having a constellation of small satellites to insure a global survey. The nano-satellite MARTIC can provide the required global observations of temperature covering also the mesosphere. GOMOS instrument on Envisat has provided a great opportunity to validate this concept.

Recent results within ARISE project, prospective works and data availability will be presented.

23 October
at 10:30

Room: LT

Turbulence encounter by research aircraft HALO –Generation mechanism and predictability

Speaker: Martina Bramberger (DLR)

### Abstract

In September/October 2016, the North Atlantic Waveguide and Downstream Impact EXperiment (NAWDEX) campaign took place in Keflavik, Iceland. During this campaign,
on 13 October 2016, the synoptic background conditions in and around Iceland favoured the excitation of mountain waves and their vertical propagation through the troposphere. The research flight lead the High Altitude and Long Range Research Aircraft HALO through this mountain wave field at lower stratospheric flight levels when it encountered strong localized turbulence. We hypothesize that mountain wave breaking is the dominant mechanism leading to the observed turbulence. To test this hypothesis, we present a comprehensive case study in which turbulence-resolving in-situ aircraft measurements are employed to analyze and quantify turbulence in the described region with parameters such as the turbulent kinetic energy and the energy dissipation rate. Furthermore, the in-situ measurements are compared to turbulence forecasts of the graphical turbulence guidance system (GTG) forced by HRES operational forecasts. This analysis is supported by idealized 3D EULAG simulations to determine the involved processes for the generation of turbulence. Complementing, forecasts and operational analyses of the integrated forecast system (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) are used to analyze the meteorological situation.

1 November
at 15:30

Room: LT

Low-level wind shear and surface winds in cloud-topped boundary layers

Speaker:  Louise Nuijens (TU, Delft)

### Abstract

Thermodynamic and radiative impacts of clouds on circulations receive much attention. But what about the more direct coupling of clouds to winds, e.g., via the transport of momentum?

I will present idealized Large Eddy Simulations that evaluate the influence of low-level wind shear on convection, cloudiness and the character of momentum transport. We focus on two cases: a subtropical trade-wind regime with predominantly shallow cumulus and congestus, and a midlatitude cold air outbreak with stratocumulus transitioning into cumulus. The simulations are run with DALES on domains of 50x50 - 100x100 km^2.

The first order effect of large-scale wind shear is to adjust near-surface winds via momentum transport. With parametrized surface fluxes, this quickly leads to a different thermodynamic development of the boundary layer, and a different transition from stratocumulus to cumulus. With prescribed surface fluxes, differences in the transition are marginal, but trade cumulus convection and the boundary layer are shallower under stronger shear. I will show that shear reduces minima and maxima in vertical velocity in the sub-cloud layer, and limits the aggregation of convection that can lead to deeper clouds. Shear also has a noticeable impact on cloud-base cloud amount by adjusting turbulence and entrainment across the transition layer.

Under most geostrophic wind profiles, momentum transport slows down the cloud layer, and can either lead to faster or slower near-surface winds depending on the direction of shear and wind turning. The total momentum transport induces friction in the sub-cloud layer, but below convective areas momentum transport accelerates the flow. Mesoscale aggregation of convection is accompanied by pronounced mesoscale variability in near-surface winds, on the order of 2-6 m/s. The relative importance of mesoscale circulations versus local up-and downdrafts on the momentum transport is still under study.

Finally, I will show ongoing work investigating the imprint of cloud cover and convection on low-level winds from 10 year of Cabauw data (soon the new Ruisdael Observatory). Compared to clear-sky days, days with cumulus convection moderately increase mixing of wind across the 200 m near-surface layer, in particular by further enhancing winds in the lowest 20 m during midday, and show more pronounced increases of 200 m averaged winds throughout the day. As cloud cover becomes larger than 50%, the mixing will significantly decrease.

7 November
at 10:30

Room: LT

The Diagonal Score

Speaker: Zied Ben-Bouallegue

### Abstract

The diagonal score (DS) is a new score that can be used as a complementary performance measure to the well-known and widely applied CRPS. DS is useful for the verification of ensemble forecasts, in particular when high-impact weather matters. First, we show how to set up a general framework for the design of proper scores. Building blocks are provided such that one can design one’s own proper score which responds to specific requirements in terms of risk aversion and event(s) of interest. In this context, the diagonal score is developed as a summary performance metric where the relationship between event climatological probability of occurrence and users’ risk aversion is fixed by design. The properties of the new score, such as propriety and equitability, are discussed based on synthetic datasets while its interpretation is illustrated based on ECMWF ensemble forecasts.

8 November
at 10:30

Room: LT

Multi-scale regimes of atmospheric motions - hurricane intensification

Speaker: Prof Rupert Klein

### Abstract

Flows of the Earth's atmosphere cover a very wide range of scales, from micrometer-sized raindrops to planetary-scale climate phenomena. The range of relevant time scales is equally broad. These scalings have stimulated many theoretical derivations via scale analysis of reduced dynamical models designed to capture particular scale-dependent dynamics. These derivations make for a substantial body of knowledge of theoretical meteorology.

In the first part of the lecture I will introduce a systematization of such reduced model equations that is based on the principles of dimensional and asymptotic analysis. This approach allows one to rederive a large number of these models in a unified fashion from the full compressible flow equations via classical single-scale asymptotics.

More importantly, this unified approach lends itself naturally to multiple scales analyses, i.e., to studies of how scale-dependent phenomena described by different reduced model equations are coupled across the scales. The second part of this lecture will cover the example of a theory for tropical storm intensification that was derived by Paeschke et al, JFM, vol. 701, 137-170 (2012), and is currently being developed further in the speaker's ongoing research.

14 November
at 10:30

Room: LT

How well do stratospheric reanalyses reproduce high-resolution satellite temperature measurements?

Speaker: Corwin Wright (University of Bath)

### Abstract

Reanalyses are widely used for a range of purposes as proxies to the true past state of the atmosphere. This is particularly the case in the stratosphere, where historical observations are sparse. Furthermore, a range of high-quality reanalysis products are now available, and the spread between these reanalyses is often used as a proxy for the uncertainty in the true value. But how realistic are these stratospheric reanalyses, and how dangerous an assumption is it to use their spread in this way?

Here, we resample stratospheric temperature data from six modern reanalyses (CFSR, ERA-5, ERA-Interim, JRA-55, JRA-55C and MERRA-2) to produce synthetic satellite observations, which we directly compare to retrieved satellite temperatures from the COSMIC, HIRDLS and SABER satellite instruments. We explicitly sample standard public-release products in order to best assess their suitability for typical usage. We find that all-time all-latitude correlations are very high (0.97–0.99 at 30km in altitude, falling to 0.84–0.94 at 50 km), but with significant variability against both latitude and height. The highest correlations are seen at high latitudes and the lowest in the sub-tropics, but root-mean-square (RMS) differences are highest (10K or greater) in high-latitude winter. In particular, reanalyses reproduce reality more poorly in regions of high gravity activity and in disrupted periods such as post-SSW recovery.

We then analyse co-located instrument-pairs of real and synthetic measurements using a hierarchical clustering analysis. Using this method, we demonstrate that full-input reanalyses (those which assimilate the full suite of observations, i.e. excluding JRA-55C) are more tightly correlated with each other than with observations, even COSMIC observations which they all assimilate. This may suggest that these reanalyses are over-tuned to match their comparators. If so, this could have significant implications for future reanalysis development.

15 November
at 10:30

Room: LT

Nonhydrostatic Atmosphere and Ocean Models using Continuous and Discontinuous Galerkin Methods

Speaker: Frank Giraldo (Department of Applied Mathematics, Naval Postgraduate School)

### Abstract

In this talk I will give an introduction to the following three on-going projects in my group: NUMA (an atmosphere dynamical core for NWP), NUMO (an ocean dynamical core) and CliMa (a new atmospheric model for climate).  The aim of this talk is to characterize the overlap between all three modeling components. For example, all three models share similar numerical methods such as continuous and discontinuous Galerkin methods and time-integrators (IMEX).  All three models are nonhydrostatic (solving compressible Euler or incompressible Navier-Stokes). NUMA has been well-documented and is performant on multi-CPU and multi-GPU computers. NUMO shares the same modeling framework as NUMAso can use all of the communicators (CPU or GPU). CliMa, on the other hand,  is an entirely new model being built from scratch in an open source and open development approach and uses many of the lessons learned from the NUMA project. CliMa is a project in collaboration with Caltech and MIT to build components for the atmosphere, ocean (including ice), and land. Although no results are yet available for CliMa, I will describe the general approach being considered for this new model.

16 November
at 10:30

Room: LT

Tropical cyclones in models: Subseasonal forecasts, climatology and new diagnostics

Speaker: Suzana J Camargo (Lamont-Doherty Earth Observatory,  Columbia University)

### Abstract

In this talk, I’ll discuss the characteristics of tropical cyclones in climate models, which are used in projections of TC activity under anthropogenic climate change. Some characteristics of TC climatology improve with model resolution, but not all do, and the improvement is not uniform across models. Using a large number of climate models, the relationship of standard TC diagnostics with the mean climate state is analyzed. Models with the same resolution can have a very different TC climatology, even if their large-scale environments are very similar. In order to understand these differences, two new diagnostics were developed that can give insight on how to improve models’ TC climatology, as well as the reliability of their projections.

In the second part of this talk the ability of the current generation of models in forecasting  tropical cyclones (TCs) – hurricanes, typhoons – weeks in advance will be discussed.  There is predictability in these time scales due to the well-known modulation of TC activity by the Madden-Julian Oscillation (MJO), with a higher level of TC activity when the MJO is in its active phase in a region. As the models’ skill in forecasting the MJO has improved in the last few years, the possibility of forecasting TC formation weeks in advance can be examined. The questions we will discuss are: How well do models simulate the MJO-TC relationship? Do models have skill in forecasting the probability of TC formation weeks in advance? Is the model skill dependent on the amplitude of the MJO?

12 December
at 10:30

Room: LT

Dynamics and predictability of North Atlantic Oscillation regimes

Speaker: Franco Molteni

### Abstract

Despite observational evidence of a distinct regime behaviour in the variability of the North Atlantic Oscillation (NAO), the theoretical support for the existence of separate NAO regimes has been limited. In this seminar, a dynamical explanation of NAO regimes is given by a theoretical model of the interactions between zonal flow (and associated temperature gradient), planetary waves and surface heat fluxes in the North Atlantic. Using observational diagnostics to guide the choice of empirical parameters, a 3-variable model is developed, which is formally equivalent to the Lorenz (1963) chaotic model for Rayleigh-Benard convection, and possesses two regimes originated by oscillations around unstable stationary states. Following earlier studies, the model can be expanded to a 5-variable system by splitting the zonal-mean wind into its barotropic and thermal component, and including a variable representing the area-averaged amplitude of high-frequency baroclinic eddies. The extended model still displays a chaotic, two-regime behaviour, with additional sub-seasonal variability driven by the energy exchanges associated with high-frequency eddy amplification and decay. Finally, the usefulness of this model as a tool to interpret and diagnose critical aspects of NAO modelling and long-range predictions will be discussed.

13 December
at 10:30

Room: LT

Seasonal variability of the temperature differences between ECMWF IFS and middle atmospheric Rayleigh lidar measurements at Rio Grande (Tierra del Fuego, Argentina) in 2018

Speaker: Sonja Gisinger (DLR)

### Abstract

As revealed from satellite observations, the region around the Southern Andes, Drake Passage, and the Antarctic Peninsula constitutes a hotspot of stratospheric gravity wave (GW) activity.  It is this region where global circulation models show a lack of GW drag (GWD) resulting in deficiencies in polar vortex dynamics, polar stratospheric temperatures and ozone concentration. So far, the sources of this "missing GWD" have not been uniquely identified. Different mechanisms are proposed in literature: (i) the downwind advection and meridional refraction of orographic GWs from the Southern Andes and the Antarctic Peninsula into the polar night jet (PNJ), (ii) unresolved orographic GWs from small islands, (iii) secondary GWs generated in the breaking region of the primary orographic waves, (iv) non-orographic GWs from sources associated with winter storm tracks over the Southern Ocean, and (v) a zonally uniform distribution of small amplitude waves by non-orographic mechanisms such as spontaneous adjustment and jet instability around the edge of the stratospheric PNJ.

In order to quantify the important sources and
propagation pathways of mid- and high-latitude GWs in the Southern Hemisphere, the Institute of Atmospheric Physics of the German Aerospace Center (DLR) installed the Compact Rayleigh Autonomous Lidar (CORAL) at Rio Grande (53.79S, 67.75W, Tierra del Fuego, Argentina) in October 2017. These ground-based measurements will be complemented by airborne remote-sensing and in-situ measurements onboard the German research aircraft HALO (High Altitude and Long-Range Research Aircraft) during the SOUTHTRAC field campaign in September 2019. The CORAL is specifically designed for the investigation ofgravity waves in the middle atmosphere between 25 and 100 km altitude. It runs fully autonomous and one full year of data above Rio Grande is now available. This temperature data is compared to ECMWF analysis and short-term forecasts (cycle 45r1) at Rio Grande. It is found that above 30 km, the largest temperature difference between the CORAL and the ECMWF system occurs in gravity wave active times of the year. The impact of sponge and vertical resolution on this temperature difference is also investigated.

## 2017

11 January
at 10:30

Room: LT

How good (or bad) is the circulation of the stratosphere and mesosphere in the IFS?

Speaker: Inna Polichtchouk (University of Reading, UK)

### Abstract

Accurate representation of the stratospheric circulation is important for tropospheric predictability on intraseasonal timescales, because of the downward influence of the stratosphere on the troposphere.  The “downward control” principle states that the stratospheric Brewer Dobson circulation (BDC) is primarily driven by the wave breaking/saturation aloft. Thus, the stratospheric circulation in turn depends on the representation of the mesospheric momentum budget. This talk reviews the state of the middle atmosphere in the IFS, with a focus on the BDC and the semi-annual oscillation. I will compare the middle-atmosphere circulation to reference datasets and assess the impact of 1) the parametrized non-orographic gravity wave drag; 2) treatment of the sponge layer; 3) the cubic octahedral discretization; and, 4) stochastic physics.

12 January
at 14:00

Room: LT

The global ICON Ensemble at DWD

Speakers: Michael Denhard and Cristina Primo (DWD, Germany)

### Abstract

Since October 2015 DWD runs an experimental ICON ensemble suite with 40 members and approx. 40km horizontal resolution on the global scale up to +168h lead time twice a day (00/12UTC). The global grid contains a 20km two-way nested area over Europe. The ensemble is initialized by analyses from our ensemble data assimilation system (ICON EDA) which is a combination of a Local Ensemble Transform Kalman Filter (LETKF) with a hybrid ensemble/3D-Var variational system for the high-resolution deterministic model. At the time there is no stochastic physics implemented and the error growth properties of the ensemble are determined by the diverse co-variance inflation techniques in the LETKF such as multiplicative inflation factors, relaxation to the prior and stochastic SST perturbations.  Moreover, the static NMC Background error co-variances are added to the flow dependent ensemble co-variances to rescale the innovations. In the first part we show verification results for the ICON-EPS forecasts in comparison to the ECMWF-EPS and analyze the spread skill relation for both ensembles. The second part introduces techniques for predicting the error growth properties along trajectories in the state space of a model. We use the "Broyden family" methods to iterate a Broyden matrix in state space of the Lorenz63 and 95 models. During iteration the Broyden matrix gains information on the error growth properties of the dynamical system. We discuss, if the information in the Broyden matrices along a trajectory can be used as an approximation of the singular vector approach.

15 February
at 10:30

Room: MR1

Flood forecast sensitivity to temperature using ECMWF ensembles for 145 catchments in Norway

Speaker: Trine Jahr Hegdahl (NVE, Norway)

### Abstract

The Norwegian flood forecasting service is based on a flood-forecasting model run on 145 basins. The basins are located all across Norway and differ in both size and hydrological regime. Current flood forecasting system is based on deterministic meteorological forecasts, and uses an auto-regressive procedure to achieve probabilistic forecasts. An alternative approach is to use meteorological and hydrological ensemble forecasts to quantify the uncertainty in forecasted streamflow. The aim of our study is to establish and assess the performance of both meteorological and hydrological ensembles for 145 catchments in Norway, which differ in size, elevation and hydrological regime. We identify regional differences and improvements in performance for preprocessed meteorological forecasts. A separate study further investigates the sensitivity to forecasted temperature for specific snowmelt induced floods. In Norway, snowmelt and combined rain and snowmelt floods are frequent. Hence, temperature is important for correct calculations of snowmelt. Temperature and precipitation ensembles are derived from ECMWF covering a period of nearly three years (01.03.2013 to 31.12.2015). To improve the spread and reduce bias we used standard methods provided by the Norwegian Meteorological Institute. Precipitation is corrected applying a zero-adjusted gamma distribution method (correcting the spread), and temperature is bias corrected using a quantile-quantile mapping (using Hirlam (RCM) 5 km temperature grid as a reference). Observed temperature and precipitation data are station data for all of Norway, interpolated to a 1×1 km2 grid (SeNorge.no). Streamflow observations are available from the NVE database. The hydrological model is the flood-forecasting operational HBV model, run with daily catchment average values. The results show that the methods applied to meteorological ensemble data reduce the cold bias present in the ECMWF temperature ensembles. Catchments on the western coast, having a lower initial performance, show the highest improvement by the temperature corrections, whereas some inland catchments in southeastern Norway show reduced performance. Ensemble spread for precipitation improves, but is not recognized in the discharge performance measures. Both precipitation and temperature show an east-west divide in performance. Corrected temperature ensemble lead to improved performance in discharge for some western catchments. Overall, the regional analyzes including all data, show that catchments have different sensitivity to temperature correction and will benefit from regional or catchment specific bias correction. Spring flood events, in catchments located west and southeast, showed different discharge response to temperature correction (more than 2°C). For the western catchment the increased temperature, led to higher discharge, whereas there were minor change for the southeastern catchment.

23 February
at 10:30

Room: LT

Subseasonal forecasting – a battle between damped persistence and tropical forcing?

Speaker: Warwick Norton (CUMULUS, UK)

### Abstract

Cumulus

We review some of the forecast performance across the 2016/17 winter where the seasonal forecasts expected a negative NAO state yet this not really played out. Rather there has been significant forecast volatility, with no forecast skill past week 2 for Europe (or in forecasting the NAO). In the southern hemisphere Australia has experienced an extremely hot summer which was also poorly forecast in the subseasonal range. We discuss sources of forecast error particularly associated with underestimating maritime continent convection but also other factors that may have led to poor forecast skill this year such as lack of MJO activity.

We examine what could be predicted with perfect knowledge of the tropics from relaxation experiments. We compare this year to other recent years where skill in predicting the NAO has been higher. Results based on Rossby wave source analysis suggest that tropical teleconnections are too weak in the ECMWF model - this can lead to periods of under confidence in forecasting predictable extratropical signals. We conjecture that current subseasonal models contain too much damped persistence of the initial conditions and not enough forcing from the tropics.

6 March
at 14:00

Room: LT

Water Information in Australia - The Post Millennium Drought Experience

Speaker: Dr Dasarath Jayasuriya (BoM, Australia)

### Abstract

Water data and information are needed for planning, managing and meeting the sustainable development goals related to water resources taking into account climate changes, population growth and other drivers impacting supply security. The Australian National Plan for Water Security (2007) postulated that better water information was essential for providing water security during Australia's periodic droughts. After the Millennium Drought which lasted from 1996 to 2007, the Government and the policy bureaucracy understood that they were facing a water crisis, but had no nationally consistent and accessible data to make informed decisions. Water data were held by approximately 200 organisations across state and local governments with no standardisation, transparency, and accessibility. Parochial interests often led to ‘gaming’.

The presentation lays out the Australian experience and its response to the water data and information challenge and shares the Government’s Water Information Program initiative over the last 10 years. Highlights relate to socialising the universal availability of water data, water information products and water forecasting services. Collectively they provide water intelligence to Bureau’s stakeholders including Government, industry and community.

Dr Dasarath Jayasuriya

23 March
at 10:30

Room: MR1

Uncertainties in simulated evapotranspiration from land surface models over a 15-year Mediterranean crop succession

Speaker: Sebastien Garrigues (CEH/UoR/INRA)

### Abstract

https://www.ecmwf.int/sites/default/files/elibrary/2017/17047-uncertaint...

11 April
at 14:00

Room: LT

Dataflow for Geocomputing

Speaker: Georgi Gaydadjiev (Maxeler, London, UK)

### Abstract

Ever since Von Neuman, predicting the weather has been one of humanities top computing challenges. The challenge can be split into two parts: (1) writing the software to predict the weather and (2) running the software to predict the weather. Running the software includes deciding on discretisation, data sizes, and building custom configurations of computing, memory and storage components.

A key question arises. Should we build computers that are easy to program or should we build computers that are efficient in running the largest models we can conceive. Of course in the initial decades, software, math and models need to be developed. However in the steady state, we will need to transition to optimising the operational aspects of running complex models.

Maxeler Multiscale Dataflow Computing addresses the steady-state challenge of optimising operational efficiency in Space, Time and Value (STV). We re-evaluate choices in discretisation of space, time and value, and build optimal computational arithmetic pipelines to compute PDE solutions in minimal time and with minimal cost.

Maxeler Dataflow computing has been demonstrated in Italy to compute a local weather model 60x faster and in China, to be 14x faster than a Tianhe 1a (dual GPU node) on a node-2-node basis. The UK government purchased a significant Maxeler machine for Daresbury labs. Still programming challenges remain and we are looking forward to continuing the dialogue with the geoscientists on how this new computational paradigm can be deployed with minimal impact on programming and code maintenance.

21 April
at 10:30

Room: LT

SODA3 (Simple Ocean Data Assimilation ocean/sea ice reanalysis) and a step toward a coupled reanalysis?

Speaker: James Carton (Univ. Maryland, USA)

### Abstract

Atmospheric reanalyses produce surface fluxes as a residual of their update cycle. These fluxes should be consistent with estimates of ocean heat and freshwater storage and divergence of transports.  Here we compare the ERA-Int, MERRA2, and JRA-55 fluxes with the imbalances apparent in the increments produced by the SODA3 ocean reanalysis system during the data-rich eight year period 2007-2014.   The heat flux comparison reveals that the regional imbalance falls in the range of 10-30 W/m2 in time mean with even larger imbalances on seasonal time scales.  In the vertical the corresponding temperature imbalances are concentrated in the mixed layer.  We argue that in the interior gyres these imbalances are the result of seasonal errors in the atmospheric reanalysis representation of surface heat and freshwater fluxes (the problem is the atmosphere).  In other regions such as the Gulf Stream we show evidence of substantial ocean model error. Elsewhere errors in momentum fluxes appear to dominate the temperature and salinity increments.  We also examine the impact on fluxes of the choice of bulk parameterization used to calculate surface fluxes from atmospheric state variables.

In the second part of the talk we present a strategy for correcting surface fluxes based on the ocean observations and we then discuss the results of experiments testing this strategy.  Examination of the results confirms that in the interior gyres our bias-correction strategy reduces the seasonal error in surface heat flux to less than 5 W/m2.  We conclude with a discussion of the changes that are needed to address biases at high latitude.

25 April
at 10:30

Room: LT

Developments in ensemble variational data assimilation at Météo-France

Speaker: Benjamin Ménétrier (Météo-France, France)

### Abstract

A brief overview of the work that is being carried out at Meteo-France in data assimilation will be presented. Short term developments include a better resolution for the ensemble of global 4DVars, whose size might double. Significant steps are also made towards the operational implementation of an ensemble of 3DVars for the regional model. Long-term plans for both global and regional models are based on a transition from 3D/4DVar to 3D/4DEnVar algorithms. After 3 years of development within the OOPS framework, numerous improvements for the EnVar methods are now available: enhanced localisation, faster distribution of members, hybrid background error covariance matrix, block-Krylov methods, etc. The implementation of all observation operators in the OOPS framework has been recently completed, enabling deeper investigations about the EnVar behaviour in an operational-like setup.

A crucial aspect of ensemble methods, and especially of EnVar algorithms, is the need for an efficient and well-tuned localisation. Affordable methods are now available to diagnose localisation functions objectively, using the ensemble only. A detailed presentation of both mathematical background and practical implementation of these methods will be given, showing consistent results for several atmospheric and oceanic models. Extensions of the theory towards hybrid covariance matrices and 4D localisation have been developed recently. All these diagnostics are publicly available in an open-source, easily operable code that works for any kind of model grid.

25 April
at 14:00

Room: LT

Non-oscillatory Forward-in-Time Unstructured-Mesh Models for Fluid Flows

Speaker: Joanna Szmelter (Loughborough Univ., UK)

### Abstract

The presentation will summarize the development of a fully unstructured (and hybrid) mesh class of models for multi-physics applications with emphasis on simulating inertia gravity waves. Global and limited area atmospheric models will be discussed. The methodology employs an edge-based, finite volume discretisation within the non-oscillatory forward-in-time (NFT) framework. The edge-based data structure allows integration of the generic physical form of the governing PDE over arbitrarily-shaped cells. Aspects of unstructured meshes flexibility, such as optimal point distribution, adaptivity and multigrid will be discussed together with different options of applying the general NFT framework based on the unstructured mesh Multidimensional Positive Definite Advection Transport Algorithm (MPDATA) and elliptic (Krylov) solvers. This approach will be evaluated for a range of models from soundproof and compressible nonhydrostatic to engineering flow solvers. Simulations of stratified orographic flows and the associated gravity-wave phenomena in media with uniform and variable dispersive properties will be presented. They verify the developments and demonstrate the efficacy of the implicit large eddy simulation operating on unstructured meshes for study of stratified turbulent flows.  Numerical examples for engineering problems will include coastal flows, gas dynamics at Mach numbers from zero to supersonic, and solutions from Arbitrary Lagrangian Eulerian (ALE) codes using conservative MPDATA based remapping techniques.

26 April
at 10:30

Room: LT

Compatible finite element methods for numerical weather prediction

Speaker: Jemma Shipton (Imperial College, UK)

### Abstract

We present recent work on developing a compatible finite element model for numerical weather prediction. This work has been motivated by the requirement for numerical discretisations that are stable and accurate on nonorthogonal grids (such as icosahedral or equiangular cubed sphere grids) without sacrificing properties of conservation, balance and wave propagation that are important for accurate atmosphere modelling on the scales relevant to weather and climate (Staniforth et. al. 2012).

Compatible finite element methods are a type of mixed finite element method (where different finite element spaces are used for different fields) where the divergence of the velocity space maps on to the pressure space. This necessitates the use of div-conforming finite element spaces for velocity, such as Raviart-Thomas and Brezzi-Douglas-Marini, and discontinuous finite element spaces for pressure. The main reason for choosing compatible finite element spaces is that they have a discrete Helmholtz decomposition of the velocity space; this means that there is a clean separation between divergence-free and rotational velocity fields. Cotter and Shipton (2012) used this decomposition to demonstrate that compatible finite element discretisations for the linear shallow water equations satisfy the basic conservation, balance and wave propagation properties listed in Staniforth and Thuburn (2012).

In the talk we will show the progress we have made towards extending this approach to the fully 3D equations via a vertical slice model. Many current atmospheric models use a staggered Charney Phillips grid in the vertical to ensure a good representation of hydrostatic balance. In the finite element context the equivalent staggering requires the temperature field to be discontinuous in the horizontal direction but continuous in the vertical. We present a stable and accurate advection scheme for this field. The success of this approach is illustrated by benchmarking results from our model, implemented in Firedrake (www.firedrake.org)

5 May
at 10:30

Room: LT

Improved Climate Forecasting Service of Australian Bureau of Meteorology

Speaker:  William Wang (Bureau of Meteorology, Australia)

### Abstract

Australia Bureau of Meteorology has started seasonal climate outlook service since 1989 based purely on statistical methods using tropical SST conditions as predictors. In May 2013 the Bureau of Meteorology Climate Information Services has started issuing climate outlooks based on the Predictive Climate Ocean Atmosphere Model for Australia (POAMA), a dynamical climate model developed by the Bureau of Meteorology and CSIRO Marine and Atmospheric research division. Since 2016, we have been developing our next generation of climate forecasting system and products based on UKMO Glosea5 or ACCESS-S. This talk is to give an overall picture of the climate prediction services in Australia through the following aspects:

1. A very brief introduction of our Bureau’s climate forecast service history; why we did what we did, experiences and lessons we obtained from the past;

2. The current dynamic climate forecasting system

1. A very brief introduction of (POAMA)

2. The revolutionary transition from statistic to dynamic and how did we make such a CHANGE;

3. What we investigate when we develop a new climate forecasting system and how, including verification metrics, such as percent consistence, LEPS, ROC skill, Brier skill score etc. and some major results as the benchmarks of a system;

4. The current services and the online products and relevant issues.

3. The development of the next generation of Bureau’s climate forecasting system

4. The new ACCESS-S/UK Met Office Glosea5 model and why it was chosen;

1. Development of new forecasting system and products– the concept of seamless forecasting from weather to annual climate prediction.

2. Primary results of this development

3. A brief introduction of a new verification metric, the so called weighted percent consistence

15 May
at 13:30

Room: LT

Measuring Large Scale Divergence and Vorticity by Aircraft

Speaker: Bjorn Stevens (MPI, Germany)

### Abstract

During NARVAL-2 an extensive array of dropsondes were launched over the tropical Atlantic, near the ITCZ, to test methods for measuring large scale vertical velocity.  These measurements have been evaluated and show that as few as 12 dropsondes launched by an aircraft are well suited to estimating divergence on the scale of a flight leg.  Analysis of high-resolution (1-2 km) simulations over the tropical Atlantic during the ICON period are used to evaluate the credibility of the measurements, and the richness of the vertical structure observed, as well as to characterize the spatial and temporal correlation of divergence as a function of scale. The analysis and measurements open a new chapter in observing diabatic processes in the tropical atmosphere and underpin a major new field initiative planned for 2020.

16 May
at 10:30

Room: LT

Mesoscale aggregation of shallow marine cumulus convection

Speaker: Christopher Bretherton (University of Washington, USA)

### Abstract

Over the oceans, shallow cumulus convection, often mixed with patchy stratocumulus, is a common cloud type.  It is usually 'aggregated' into mesoscale patches or polygons of deeper cumuli, with possible consequences for the mean vertical structure of cloud cover and cloud-precipitation-aerosol interaction.  Large-eddy simulations (LES) covering domains 50 km or more across also exhibit mesoscale aggregation of shallow cumulus convection, but it is not fundamentally well understood.   To further that understanding, we analyze the development of convective aggregation in multiday LES of a 108x108 km doubly periodic domain simulating mean summertime conditions at a location east of Hawaii.  The simulated convection aggregates within 12 hours.  Vertically resolved heat and moisture budgets on mesoscale subdomains elucidate this process.  Shallow cumulus deepen preferentially in more humid regions of the boundary layer, stimulating net moisture convergence into those regions.  Sensitivity studies show that the aggregation does not require precipitation.  Aggregation is weakened but not prevented if radiative cooling and surface fluxes are horizontally homogenized.  A unifying conceptual model explains these findings.

18 May
at 10:30

Room: MR1

"How do I know if I’ve improved my continental scale flood early warning system?"

Speaker: Hannah Cloke (University of Reading, UK)

### Abstract

Flood early warning systems mitigate damages and loss of life and are an economically efficient way of enhancing disaster resilience. The use of continental scale flood early warning systems is rapidly growing. The European Flood Awareness System (EFAS) is a pan-European flood early warning system forced by a multi-model ensemble of numerical weather predictions. Responses to scientific and technical changes can be complex in these computationally expensive continental scale systems, and improvements need to be tested by evaluating runs of the whole system. It is demonstrated here that forecast skill is not correlated with the value of warnings. In order to tell if the system has been improved an evaluation strategy is required that considers both forecast skill and warning value. The combination of a multi-forcing ensemble of EFAS flood forecasts is evaluated with a new skill-value strategy. The full multi-forcing ensemble is recommended for operational forecasting, but, there are spatial variations in the optimal forecast combination. Results indicate that optimizing forecasts based on value rather than skill alters the optimal forcing combination and the forecast performance. Also indicated is that model diversity and ensemble size are both important in achieving best overall performance. The use of several evaluation measures that consider both skill and value is strongly recommended when considering improvements to early warning systems.

19 May
at 14:00
Room: LT

Application of a CubeSat-Based Passive Microwave Constellation to Operational Meteorology

Speaker: Al Gasiewski (University of Colorado, USA)

### Abstract

In their most recent decadal assessment (Earth Application from Space, 2007) of Earth science space missions the U.S. National Research Council identified the Precipitation and Allweather Temperature and Humidity (PATH) mission as one of ten recommended medium cost missions. Based on the NRC’s outlined goals, PATH would have the unique capability of providing allweather temperature and moisture soundings and cloud and raincell imagery at spatial scales comparable to AMSU-A/B or ATMS, but at sub-hourly temporal resolution. The essential need is to provide the atmospheric penetrability and spatial resolution of operational microwave sensors but with temporal resolution commensurate with the natural rate of evolution of convectively driven weather. This seminar will focus on the merits of a constellation of passive microwave sounding and imaging CubeSats for achieving PATH goals from the multiple viewpoints of calibration accuracy, data assimilation and global sampling, downlink capability and latency, and orbital lifetime and launch availability. Microwave spectral imagery at 50, 118, and 183 GHz with spatial resolution of ~10-30 km and temporal resolution of ~15-60 minutes from such a fleet could be expected to significantly enhance forecasting of mesoscale convective weather and hurricane rain band evolution, along with provide valuable temporal gap-filling data for synoptic weather forecasting. It is argued that from a joint technology, science, and operational standpoint that a cost-effective realization of the PATH goals, but with the additional features of global coverage and improved NWP sensitivity, can be achieved by a low-cost random-orbit constellation of CubeSats supporting the ATMS and 118 GHz bands. The CU PolarCube mission will be discussed as a basis for this fleet concept.

22 May

at 9:30

Room: CC

Statistical postprocessing of multi-model ensemble
precipitation forecasts in the US National Weather Service

Speaker: Tom Hamill (NOAA Earth System Research Lab, USA)

### Abstract

Taking concepts developed in programs such as THORPEX/TIGGE, the US NWS is embracing the use of multi-model ensembles and their statistical postprocessing using short training data sets.  The intended goal is to produce dramatically improved forecasts of important weather elements such as temperature, winds, and precipitation, both deterministic and probabilistic.  Generating reliable and skillful forecasts of precipitation will be the focus of this talk.  Postprocessing of precipitation is especially challenging since forecast bias depends on precipitation amount, and a short training sample (here, the previous 60 days) is often insufficient to estimate this conditional, often location-dependent bias.

This talk will discussed a sequential algorithm for precipitation postprocessing over the US for forecast leads of +1 to +10 days using US and Canadian global ensemble data, an algorithm that provides a workaround for limitations imposed by using a short training data set. The steps in the postprocessing include: (a) pre-specification of "supplemental locations" for each model grid point -- i.e., the specification of other grid points with similar precipitation climatologies and terrain characteristics that are likely to have similar forecast biases. (b) generating forecast and analyzed cumulative distribution functions (CDFs) for each grid point using the last 60 days of forecasts, including data from supplemental locations. (c) Quantile mapping of each member forecast at each grid point; (d) Dressing each quantile-mapped forecast with amount-dependent noise to account for the under-spread character of ensemble forecasts; (e) estimation of probabilities from the ensemble relative frequency; and (f) Savitzky-Golay smoothing of forecasts in regions with little variation in terrain height.  The resulting forecasts are shown to be highly reliable and skillful.

25 May
at 10:30

Room: LT

20th Century trends in potential predictability and the role of land surface

### Abstract

Speaker: Bart van den Hurk (KNMI, The Netherlands)

Climate change does give rise to shifts in patterns of risks of high-impact extreme events. An important means to adapt to extreme events is early warning, based on skilful forecasts. The ability to forecast any signal is inherently limited by the chaotic nature of the system. A change in the variability patterns in the climate system may or may not impose shifts in the inherent potential predictability of phenomena at monthly to seasonal time scales, which may or may not change our ability to prepare to these phenomena.

During a short sabbatical stay I've explored signatures of trends in potential predictability and the role of land surface processes in this. Use was made of earlier 20th century reforecasts by Antje Weisheimer, where at 4 startdates per year an ensemble of 51 4-month forecasts was produced initialized from ERA20C. In order to explore the role of the land surface, a duplicate experiment was performed in which the land surface in each of the ensemble members was initialized from different states, removing the source of predictability arising from this component in the climate system.

The seminar will review some related studies reported earlier in the literature, and will present early results of the experiments carried out at ECMWF. Suggestions for further analyses from the audience are more than welcome.

19 June
at 14:00

Room: MR1

Atmospheric Rivers in Europe: from moisture sources to impacts and future climate scenarios

Speaker: Alexandre Ramos (Instituto Dom Luiz, Portugal)

### Abstract

An atmospheric river (AR) detection algorithm is used for the North Atlantic ocean basin, allowing the identification of the major ARs affecting western European coasts between 1979 and 2014. The western coast of Europe was divided into five domains, namely the Iberian Peninsula, France, UK, Southern Scandinavia and the Netherlands, and Northern Scandinavia. Following the identification of the main ARs that made landfall in western Europe, a Lagrangian analysis was then applied in order to identify the main areas where the moisture uptake was anomalous and contributed to the ARs reaching each domain.

There is a strong relationship between extreme precipitation across Europe and ARs.  In the particular case of the Iberian Peninsula, the major AR events that affected the region were studied in detailed. It was analyzed if the extreme precipitation days in the Iberian Peninsula are association (or not) with the occurrence of ARs. Results show that the association between ARs and extreme precipitation days in the western river basins is noteworthy, while for the eastern and southern basins the impact of ARs is reduced.

Since the ARs are associated with high impact weather it is of most importance to assess changes in the ARs frequency in future climate changes. Regarding Europe, changes in the vertically integrated horizontal water transport were analyzed using six global climate models. There is an increase in the vertically integrated horizontal water transport which lead to an increase in the ARs frequency for the 2074- 2099 period when compared with the historical simulation (1980-2005). This increase in  future ARs frequency is estimated to be more visible in the high emission scenarios (RCP8.5) when it can more than double the annual mean of ARs obtained for the historical simulation, as shown in Figure 2 for the “Southern Scandinavia and The Netherlands” domain.

20 June
at 14:00

Room: MZR

WAVE2NEMO: A regional WAM-NEMO model setup

Speaker: Øyvind Breivik (Norwegian Meteorological Institute, Norway)

### Abstract

The WAVE2NEMO project, funded by CMEMS, aims to implement a number of wave effects in a regional NEMO version. The project builds on work started at ECMWF and implements Coriolis-Stokes forcing, wave-induced mixing by breaking waves and wave-modified momentum fluxes in forced mode with wave fields taken from a regional WAM model. A wave-forced model of the North Sea and the Baltic Sea is found to have improved water level representation during two wind storms in the autumn of 2013. The model also shows slightly improved SST biases in the Baltic Sea compared to a control run. Recent work on approximate Stokes drift profiles (Breivik et al, 2016, Li et al, 2017) has led to a new layer-averaged Stokes drift profile which is now being tested in the regional NEMO setup. We hope to collaborate with ECMWF on the implementation of these wave effects in the most recent version of NEMO.

20 June
at 14:00

Room: LT

Porting IFS physics cloud scheme (CLOUDSC) to GPUs with OpenACC

### Abstract

A physics cloud scheme is an important component of a numerical weather/climate prediction model which represents the cloud processes in it. The IFS physics cloud scheme (CLOUDSC) solves five prognostic equations for water vapour, cloud liquid water, rain, cloud ice and snow mixing ratios in an implicit numerical framework. It is a computationally intensive part in the ECMWF model. GPU computing has been extensively applied in scientific and engineering computing recently due to the progress of GPU hardware and related programming models such as CUDA/OpenCL and OpenACC. Given the advantages with respect to code portability and simplicity with OpenACC over CUDA we implement an accelerated CLOUDSC with OpenACC. It combines MPI, OpenMP and OpenACC to fully exploit the power of GPUs across a single or multiple nodes, together with various optimizations. The results show that in terms of the total GPU runtime the obtained performance of 4 NVIDIA GK210 GPUs (2 NVIDIA K80) on a single node for a single time-step is comparable to that of a whole node of 2 Intel Xeon Haswell CPU with 24 cores if the workload saturates GPUs; but without taking into account the GPU data transfer and other overheads, the GPU actual calculation time with a single GPU is about 17% less than that of a whole CPU node with 24 cores for the same problem size. In an operational forecast where multiple time-steps are taken data can be resident on GPU and need to be communicated to CPU only during an I/O step. Therefore, based on the results of this implementation, we conclude that a GPU adaptation of the CLOUDSC can be competitive in terms of performance with respect to CPU.

22 June
at 11:15

Room: MZR

A statistical-dynamical ensemble approach to forecasting water hazards

Speaker: Louise Slater (Loughborough University, UK)

### Abstract

Traditional hydrologic forecasting approaches are either statistical, relating climate precursors to streamflow/stage, or dynamical, forcing hydrologic models with meteorological forecasts. In contrast, hybrid statistical-dynamical techniques benefit from different strengths: they are computationally efficient, can integrate and ‘learn’ from a broad selection of input data (GCM forecasts, Earth Observation time series, teleconnection patterns), and can benefit from recent progress in machine learning (e.g. multi-model blending, post-processing and ensembling techniques).

Using climate forecasts from the North American Multi Model Ensemble (NMME: CCSM3, CCSM4, CanCM3, CanCM4, GFDL2.1, FLORb01,GEOS5, and CFSv2), we conduct systematic probabilistic forecasting of monthly-seasonal streamflow and water levels in several hundred catchments across the U.S. and U.K, over weekly to decadal timescales. In heavily urbanised or agricultural catchments, we find that changing land use is a key predictor of streamflow and water levels. While our current approach uses various proxies to model the effects of land cover, this work opens up new possibilities for combining Earth Observation time series with GCM forecasts to predict a variety of hazards (incl. low/high water levels and water pollution) from space using data science techniques.

23 June
at 10:30

Room: MR1

Bias correction of tropical cyclone size and structure in the ECMWF global ensemble prediction system

Speaker: Jeff Kepert (Bureau of Meteorology, Australia)

### Abstract

Global EPS systems provide very valuable warning of severe weather risk, including tropical cyclones. One limitation arises because the spatial resolution of the EPS is necessarily too coarse to capture the fine details of the tropical cyclone's core circulation, resulting in the predicted storms having systematic biases in structure and intensity. In particular, the cyclones are too weak and the radius to maximum winds is too large, with these biases increasing with forecast length. Ocean waves are a major impact mechanism of tropical cyclones, but these atmospheric biases result in errors in the predicted ocean wave field also. While these biases to not affect users who respond purely to the expected risk of a tropical cyclone in their vicinity, they are important for users who wish to make more quantitative use of the wind or wave predictions.

We have developed a method for bias correcting tropical cyclone structure and intensity in EPS systems, and applied it to cyclones off north west Australia in the ECMWF global EPS. The method diagnoses the properties of forecast storms within the EPS, and replaces them in the surface wind and pressure field with parametric vortices with the corrected intensity and structure. The correction scheme is statistical, based on regression analysis of historical errors. The bias-corrected wind field ensemble is then used to force a wave model ensemble.

This work was supported by Woodside, Shell, Inpex and Chevron, who operate in the waters off north west Australia.

27 June
at 11:00

Room: MR1

A Case Study of the June 2013 Biomass-Burning Haze Event Using WRF-Chem

Speaker: Andy Chan (University of Nottingham, Malaysia Campus, UK)

28 June
at 10:30

Room: LT

Self-organization of convection and regulation of tropical climate

Speaker: Marat Khairoutdinov (Stony Brook University, USA)

### Abstract

Evidence from paleoclimate reconstructions suggests that the tropical climate has been essentially stable with just a few degrees variations in SSTs despite much higher concentration of greenhouse gases than at present. It has been hypothesized that the tropical climate is maintained by self-aggregation or clustering of convection. Idealized cloud-resolving simulations show that warmer SSTs are conducive to aggregation, which has a tendency to dry out the atmosphere reducing the greenhouse effect and, hence, providing powerful negative feedback to warming. Similar mechanism can also operate in response to projected climate warming due to anthropogenic forcing. Recent results from idealized Near-Global (NG) cloud-resolving simulations of tropically centered belt on aquaplanet show that while  the number of small and medium size convective clusters tend to be invariant of warming, the number of super-clusters associated with large-scale equatorially trapped waves such as Kelvin-waves can substantially increase in the warmer climate.  However, contrary to several recent studies, our NG experiments over constant-SST aquaplanet with Earth-like circumference alone the equator show a substantial decrease of MJO variance at warmer SSTs. Possible mechanisms for such behavior will be discussed. Also, some preliminary results of global cloud-resolving simulations of Earth using a newly developed global cloud-resolving model at 4 km grid spacing will be presented.

3 July
at 10:30

Room: LT

EC-Earth as a test-bed for climate prediction and services research

Speaker: F J Doblas-Reyes  (ICREA and BSC, Barcelona, Spain)

### Abstract

The EC-Earth climate model has the atmosphere and ocean components in common with the ECMWF seasonal forecast system. However, there are many differences between the two models such as the atmosphere and ocean cycles, the resolution, the Earth system components, etc. This talk will discuss these differences using EC-Earth as a climate forecast system and suggest ways in which the differences can be exploited to provide useful feedback to ECMWF. The main ideas will be illustrated in the context of climate services research.

4 July
at 10:30

Room: LT

An introduction to the European Environment Agency and its work on key thematic areas

Speaker: Hans Bruyninckx (Executive Director, EEA, Belgium)

### Abstract

The presentation will provide a summary of the EEA, its governance, networks and member countries. It will look at its 2014-2020 work programme focusing on various thematic areas and relevant European and global policies.

The presentation will also assess anticipated challenges for the Agency.

Moving beyond this general introduction, the presentation will then look at the EEA’s principal areas of work such as air pollution, climate change and energy, water management, marine, and the Copernicus Land monitoring service (CLMS) which the EEA manages. Finally, a summary of the EEA’s interactions with the Copernicus Climate Change Service (C3S) and Copernicus Atmosphere monitoring Service (CAMS) will be provided.

4 July
at 14:00

Room: LT

EuroHPC and domain science driven technologies for exascale

Speaker: Thomas Schulthess (Director of the Swiss Supercomputing Centre, Switzerland)

6 July
at 10:30

Room: LT

Coupled data assimilation efforts at the US Naval Research Laboratory

Speaker: Sergey Frolov (Naval Research Laboratory, Monterey, California, USA)

### Abstract

Data assimilation in coupled models of ocean-atmosphere-ice presents a unique set of challenges. The spatial and temporal scales vary by an order of magnitude between fluids, the covariances between components of the coupled system are poorly known, the assimilation methods tend to differ, and coupled models often do not have tangent linear and adjoint models. In this presentation, we show several algorithmic solutions that allow us to resolve these challenges. Specifically, we introduce the interface solver method that augments existing stand-alone systems for ocean and atmosphere by allowing them to be influenced by relevant measurements from the coupled fluid. To propagate information between fluids, we use coupled ensembles. In this talk we present a combination of development plans for the Navy’s global coupled model, as well as set of preliminary results on the impact of assimilating SST-sensitive radiances in the atmospheric model and first results of hybrid DA in 1/12 degree model of the global ocean.

10 July
at 10:30

Room: LT

Representing the stratosphere in atmospheric models (and why it matters)

Speaker: Ted Shepherd (Dept of Meteorology, Reading University)

### Abstract

Over the last two decades, it has become apparent that the state of the stratosphere affects the troposphere, and thus that model deficiencies in the stratosphere have tropospheric implications. Whilst stratosphere-troposphere dynamical coupling is a robust phenomenon on many timescales, the lack of a detailed understanding of the mechanisms involved means that model deficiencies in this respect can be difficult to alleviate. This talk will discuss some of the issues involved, as well as highlighting some of the early findings from the Stratosphere Task Force.

12 July
at 14:00

Room: MR3

Robust and transparent planning and operation
of water resource infrastructure

Speaker: Francesca Pianosi (Dept. of Civil. Eng., Bristol University, UK)

### Abstract

Sustainable management of water resources is crucial to underpin population’s health and the economy while increasing resilience against hydro-meteorological hazards such as floods and droughts. In the UK, the water industry faces significant water challenges due to increasing variability of hydrological conditions, changing patterns of water demand and the urgency of reconciling human needs with the protection of the natural environment. In response to such challenges, the UK regulatory frameworks for the water industry (AMP6) has promoted a shift in focus from a ‘capex’ (capital expenditure) to a ‘totex’ (total expenditure) approach and emphasised the need to develop new skills to find ‘no build’ solutions and address supply and quality issues at catchment scale rather than at each individual infrastructure (e.g. treatment plants or pumping station).

To put this priority into practice, two methodological gaps need to be fill in: [1] How to integrate and exploit “built’ infrastructures (e.g. reservoirs, pumping stations, etc.) and “information” infrastructures (e.g. increasingly sophisticated monitoring and forecasting systems) – to promote water efficiency and enhance resilience of water resource systems. [2] How to estimate and compare long-term costs of alternative infrastructure or management options, given the increasingly high uncertainty in future conditions (both on the supply and demand side) induced by unprecedented rate of change in environmental (e.g. climate and hydrology) and socio-economic (e.g. population and consumption behavior) conditions.

The goal of this project is to build the next-generation analytical approaches (simulation and optimisation models and methods) to fill these gaps. These tools will produce actionable information to support both operational (short term) and design (long-term) decisions in a robust and transparent way. The project will be carried out in close collaboration with partners representative of the key players of the UK water industry: water suppliers (water companies), knowledge and model providers (consultancy company, government research institutes such as the MetOffice) and regulators (Environment Agency). All methods will be developed and tested on case study applications provided by water companies, so to ensure that they are actually valuable to address the most urgent issues they face, and they will be implemented in open-source software packages so that also other water practitioners besides those directly involved in the project will benefit from its findings and outputs.

25 July
at 10:30

Room: MR1

Seasonal analysis of near-surface biases in ERA-Interim over the Canadian Prairies

Speaker: Alan Betts (Atmospheric Research)

### Abstract

We quantify the biases in the diurnal cycle of temperature in ERA-Interim for both warm and cold season using hourly climate station data for four stations in Saskatchewan from 1979-2006. The warm season biases increase as opaque cloud cover decreases, and change substantially from April to October. The bias in mean temperature increases almost monotonically from small negative values in April to small positive values in the fall. Under clear skies, the bias in maximum temperature is of the order of -1 o C in June and July, and -2 o C in spring and fall; while the bias in minimum temperature increases almost monotonically from +1 o C in spring to +2.5 o C in October. The bias in the diurnal temperature range falls under clear skies from -2.5 o C in spring to -5 o C in fall. The cold season biases with surface snow have a different structure. The biases in maximum, mean and minimum temperature with a stable BL reach +1 o C, +2.6 o C and +3 o C respectively in January under clear skies. The cold season bias in diurnal range increases from about -1.8 o C in the fall to positive values in March. These diurnal biases in 2-m temperature and their seasonal trends are consistent with a high bias in both the diurnal and seasonal amplitude of the model ground heat flux, and a warm season daytime bias resulting from the model fixed leaf area index. Our results can be used as bias corrections in agricultural modeling that use these reanalysis data, and also as a framework for understanding model biases.

8 August
at 10:30

Room: MR1

Introducing the new Master of Science Degree in Environmental Meteorology

Speaker: Dino Zardi (University of Trento, Italy)

### Abstract

The seminar introduces the project of a new programme, leading to an MSc degree in Environmental Meteorology, jointly offered by the Universities of Trento (Italy) and Innsbruck (Austria). The programme aims at preparing experts with a solid background in atmospheric processes relevant for a range of environmental systems and interactions. Courses cover not only typical meteorological subjects - including observational, theoretical, and numerical modelling approaches - but also environmental topics, such as hydrology, renewable energy resource assessment, agricultural and forest interactions with the atmosphere, air quality measurement and modelling, mountain meteorology, environmental physical-chemistry, biogeochemistry. All the lectures will be given in English, partly in Trento and partly in Innsbruck. The programme is going to start in September 2018. Access will be offered to a limited number of selected candidates. During my seminar, I will present this new educational initiative, and will be very happy to hear comments and suggestions from the audience.

6 September at 10:30

Room: LT

Parametrization of non-orographic gravity-waves: formalism, impact and test against observations

Speaker: François Lott, (LMD, France)

### Abstract

A stochastic parameterization of the non orographic gravity waves emitted by convection and fronts is presented.  For the front the formalism is based on a spontaneous adjustment theory where potential vorticity anomalies emit gravity waves in the course of their evolution. The introduction of explicit sources and the use of a stochastic multiwave formalism makes that the momentum fluxes predicted by the scheme are highly intermittent. This intermittent character is one of the key properties of the gravity waves measured by constant level balloons during the vorcore and   concordiasi campaign. It is shown that the scheme can be realistic in representing it. It is also shown  that intermittency in non-orographic gravity waves prediction can be important to predict the final warming in the middle atmosphere of the Southern Hemisphere in early spring. With sources, we can also address how the gravity waves forcing changes when the climate change. The results so far are quite neutral, at least in the middle atmosphere of the LMDz GCM, which probably follows that GWs are strongly filtered by the large scale background winds in the middle atmosphere.

6 September at 15:30

Room: LT

Ensemble Seasonal Coupled Streamflow Forecast for Hydropower in Brazil

Speaker: Alberto Assis dos Reis (CEMIG, Brazil)

### Abstract

The Brazilian electric system is essentially hydrothermal, with a great weight of hydraulic generation (near 65%). The streamflow forecast can be very beneficial to allow early response in extreme climactic events and for a more efficient operation of the hydro power plants. At this project we aim at using ensemble weather forecasts and ESP-Ensemble Streamflow Prediction technique as a forcing for the hydrological models to develop a robust forecasting. The developments will be conducted within the FEWS-Cemig platform which is already running in operational mode. First we will deal with the uncertainty of the observed precipitation, combining different source of gridded observed precipitation to obtain a better estimative, test different sampling methods to apply the ESP methodology, run the hydrologic models for a group of basins and apply flow data assimilation to improve the models results. Then we will deal with the uncertainty of short term, intra-seasonal and seasonal precipitation forecast models and apply bias correction technics to improve the flow forecasts. Finally we will couple the observed precipitation; flow data assimilation; short term, intra-seasonal and seasonal precipitation forecasts and the ESP technic to obtain a seamless ensemble seasonal flow forecast with the hydrological models.

7 September at 10:30

Room: LT

Recent Developments in Atmospheric River Science, Prediction and Applications

Speaker: F. Martin Ralph (CW3E, Univ. California/ Scripps Institute of Oceanography, USA)

### Abstract

A number of key developments have occurred recently on the subject of atmospheric rivers (AR).  These include advances in observations, physical process understanding, predictions, applications and policies.  This presentation will highlight a few of these developments.

• Detailed observations of 21 ARs using dropsondes from research aircraft show that an average AR transports, as vapor, roughly 2 times as much water as the Amazon River discharges, as liquid.

• Extreme precipitation from a series of landfalling ARs led to damage of a spillway of a major flood control dam in February 2017, which triggered an evacuation of 200,000 people in Northern California.

• Methods are being developed to evaluate AR landfall forecast skill, partly to support potential use of AR forecasts in future reservoir operations.

• New observations focused on ARs are now available from a specialized mesonet in California and an airborne targeting approach using multi-aircraft dropsonde deployments is under development (including use of research and reconnaissance aircraft normally dedicated to hurricane activities in the warm season).

• A critical mass of research and experimental forecast capability, with an emphasis on AR science, predictions and applications, has been developed at the Center for Western Weather and Water Extremes.

15 September at 13:30

Room: LT

Prediction of Arctic sea ice on subseasonal to seasonal time scales

Speaker: Zampieri Lorenzo (AWI, Germany)

### Abstract

Sea ice forecasts are becoming a demanding need since human activities in the Arctic are constantly increasing and this trend is expected to continue. In this context, the recent availability of the Subseasonal to Season al Prediction Project (S2S) Dataset has a particularly good timing and provides a solid base to make an initial assessment of the predictive skills of probabilistic forecast systems with dynamical sea ice . In this study , we employ different verification metrics to compare the S2S sea ice forecasts with satellite observations and the models ’ own analys es. In particular , the focus is on the sea ice spatial distribution in the Arctic, which is relevant information for potential final users. The verification metrics, specifically chosen to quantify the quality of the forecasted sea ice edge position , are the Integrated Ice Edge Error (IIEE), the Spatial Probability Score (SPS) and the Modified Hausdorff Distance (MHD).

Despite the early development stage of Arctic sea ice predictions on the seasonal time scale , and the fact that the main focus of the S2S systems is mostly not on sea ice per se, our findings reveal that some of the S2S models are promising , exhibiting better predictive skills than the observation -based climatology and persistence . However, the results also point to critical aspects concerning the data assimilation procedure and the tuning of the models , which can strongly affect the forecasts quality . The comparison of different versions of the ECMWF forecast system shows the benefits brought by a coupled dynamical description of the sea ice instead of its prescription based on persistence and climatological records. Moreover, the systematic application of the verification metrics to such a broad pool of forecasts provides useful indications about strengths and limitation of the verification metrics themselves. Given the increasing availability of new and better sea ice observations and the possible improvement s to coupled seasonal forecast systems, the formulation of reliable Arctic sea ice predictions for the subseasonal to seasonal time scales appears to be a realistic target for the scientific community.

27 September at 14:00

Room: MZR

Strengthening the link between meteorological and energy forecasting communities: Datasets and analytics

Speaker: Pierre Pinson (Technical University of Denmark)

### Abstract

Renewable energy modelling and forecasting has come a long way since the first work performed and published in the early 80s. However, the underlying analytics has not progressed much, expect for a few breakthrough related to the transition from deterministic to probabilistic forecasting, or to the recent availability of new types of data in large quantity e.g. distributed surface observations, weather radar images, etc. In this talk, we will review and discuss these changes and how they benefit the integration of renewable energy generation in existing power systems and electricity markets. One is left to realize though that much more could be done if high-resolution regional reanalysis data was available for instance, and if developing big-data based approach to the seamless prediction of renewable energy generation at the continental scale. Personal thoughts on which directions such research is to take, and on further collaboration between energy and meteorological communities, will close the talk."

Short bio: Pierre Pinson is a Professor at the Centre for Electric Power and Energy (CEE) of the Technical university of Denmark (DTU, Dept. of Electrical Engineering), also heading a group focusing on Energy Analytics & Markets. He holds a M.Sc. In Applied Mathematics from INSA Toulouse and a Ph.D. In Energy Engineering from Ecole de Mines de Paris (France). He acts (or has acted) as an Editor for the IEEE Transactions on Power Systems, the International Journal of Forecasting and Wind Energy. His main research interests are centered around the proposal and application of mathematical methods for electricity markets and power systems operations, including forecasting. He has published extensively in some of the leading journals in Meteorology, Power Systems Engineering, Statistics and Operations Research. He has been a visiting researcher at the University of Oxford (Mathematical Institute) and the University of Washington in Seattle (Dpt. of Statistics), as well as a scientist at the European Center for Medium-range Weather Forecasts (ECMWF, UK) and a visiting professor at Ecole Normale Superieure (Rennes, France). He is leading a number of initiatives aiming to profoundly rethink electricity markets for future renewable-based power systems and with a more proactive role of consumers. This focus on consumer-centric and community-driven electricity markets translates into proposals for peer-to-peer energy exchange, from mathematical framework to actual demonstration in Denmark.

5 October
at 10:30

Room: MZR

A new framework for cumulus parametrization

Speaker: Christian Jakob (Monash University, Australia)

### Abstract

The representation of convection in climate model remains a major Achilles Heel in our pursuit of better predictions of global and regional climate. The basic principle underpinning the parametrization of tropical convection in global weather and climate models is that there exist discernible interactions between the resolved model scale and the parametrized cumulus scale. Furthermore, there must be at least some predictive power in the larger scales for the statistical behaviour on small scales for us to be able to formally close the parametrized equations.

The presentation will discuss a new framework for cumulus parametrization based on the idea of separating the prediction of cloud area from that of velocity. This idea is put into practice by combining an existing multi-scale stochastic cloud model with observations to arrive at the prediction of the area fraction for deep precipitating convection. Using mid-tropospheric humidity and vertical motion as predictors, the model is shown to reproduce the observed behaviour of both mean and variability of deep convective area fraction well. The framework allows for the inclusion of convective organisation and can - in principle - be made resolution-aware or resolution-independent.

When combined with simple assumptions about cloud-base vertical motion the model can be used as a closure assumption in any existing cumulus parametrization. Results of applying this idea in the the ECHAM model indicate significant improvements in the simulation of tropical variability, including but not limited to the MJO.

6 October
at 10:30

Room: MR1

GEOMETRIC: Geometry and Energetics of Ocean Mesoscale Eddies and Their Rectified Impact on Climate

Speaker: David Marshall (Clarendon Laboratory)

19 October
at 10:30

Room: LT

LDAS-Monde global capacity assimilation of satellite-derived vegetation and soil moisture products: analysis impact over North America

Speaker: Clement Albergel (Météo-France, France)

### Abstract

In this study LDAS-Monde, a land data assimilation system with global capacity, is applied over North America to increase monitoring accuracy for land surface moisture energy and water states and fluxes, including evapotranspiration and stream flow as well as vegetation growth. LDAS-Monde ingests information from satellite-derived Surface Soil Moisture (SSM) and Leaf Area Index (LAI) estimates to constrain the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (ISBA-CTRIP) continental hydrological system. LDAS-Monde uses the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth, while transfer of water and heat through the soil rely on a multilayer diffusion scheme. SSM and LAI estimates are assimilated using a Simplified Extended Kalman Filter (SEKF), which uses finite differences from perturbed simulations to generate flow-dependence between the observations and the model control variables (LAI and seven layers of soil: from 1 cm to 100 cm depth).

LDAS-Monde analysis impact over 2007-2016 is assessed over North America using satellite-driven model estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project as well as upscaled ground-based observations of gross primary productivity from the FLUXCOM project. Over the US, in-situ measurements of soil moisture from the USCRN network and of turbulent heat fluxes and GPP from FLUXNET-2015 are used in the evaluation, together with river discharges from the USGS. Those data sets highlight the added value of LDAS-Monde compared to an open-loop simulation (i.e. no assimilation). Finally, it has been shown that LDAS-Monde has a strong ability to monitor agricultural drought, by providing improved initial conditions which persist through time, aiding agricultural drought prediction.

24 October
at 10:30

Room: MR1

GNSS & ATOMMS RO:  New Cubesat-Based Radio Occultation Systems for Weather & Climate

Speaker: E Robert Kursinski (Space Sciences & Engineering, Boulder, CO, USA)

### Abstract

Reducing the uncertainty of weather and climate predictions requires better understanding of the hydrological and energy cycles and the intimate coupling and complex interplay between atmospheric water, temperature and stability, dynamics and short and long wave radiation.  Orbiting radar and lidar measurements have greatly increased our understanding of aerosols, clouds and precipitation and Aeolus promises analogous advances on winds in the near future.  Greatly increasing the quantity and information content of radio occultation (RO) profiling promises to provide analogous advances about temperature and water vapor as well as constraints on winds. When taken together, these combined, global, precise and high vertical resolution observations of temperature water vapor, winds, aerosols, clouds, precipitation and energy fluxes would better tie the entire weather-climate system together and yield more observationally constrained global analyses and forecast initialization, better process-related constraints to guide model improvements and reduced uncertainty about GCM realism and predictions.

The ability of GPS RO to profile atmospheric temperature and pressure with very high vertical resolution, precision and accuracy, particularly in the UTLS, is well established. With regard to water vapor, histograms of low latitude specific and relative humidity derived from COSMIC GPS RO data reveal the levels of uncertainty among global analyses and climate models. These results indicate that MERRA water vapor analyses are the best in the middle and upper troposphere while ECWMF (circa 2007) is better in the lower free troposphere. While present RO sampling densities are too sparse to impact global moisture analyses much, greatly increasing the GNSS RO sampling densities via cubesats would more tightly constrain and improve the analyses.  Our cubesat-based GNSS RO constellation, designed to provide several tens of thousands of occultations per day with performance approaching that of COSMIC-2, is scheduled to begin launching at the end of 2018.

A significant advance beyond GPS RO is achievable.  We have been developing the Active Temperature Ozone and Moisture Microwave Spectrometer (ATOMMS) RO system to probe the atmosphere near the 22 & 183 GHz absorption lines of water and 169 & 184 GHz lines of ozone.  By profiling both the speed and absorption of light, ATOMMS will profile water vapor, temperature and pressure simultaneously, which GNSS RO cannot do, from near the surface to the mesopause, with random uncertainties of 1-3% for water vapor and 0.4K for temperature and still better absolute uncertainty over most of the altitude range, with 100 m vertical resolution. Performance in clouds should be within a factor of two of clear air performance. This orbital profiling performance approaches that of radiosondes, but with far better accuracy via RO’s inherent self-calibration.

With funding from NSF, we developed a prototype ATOMMS instrument and demonstrated several key ATOMMS capabilities on the ground including retrieving water vapor to better than 1% in optical depths up to 17 through clear, cloudy and rainy conditions.

While conceived for climate, miniaturization of the ATOMMS instrument and cubesat technology have made NWP sampling densities feasible. A 60 satellite constellation delivering 25,000 ATOMMS and 170,000 GNSS RO occultations each day, providing complete global coverage every 6 hours, could be implemented for a fraction of the cost of a JPSS satellite.  Such a constellation could be implemented in stages, beginning perhaps with 4-6 ATOMMS satellites focused on polar science. This would then be expanded over time via additional satellites with the number of ATOMMS occultations increasing in proportion to the square of the number of satellites.

An ATOMMS observation simulation study would help quantify the impact of large numbers of ATOMMS profiles on NWP analyses and forecasts and move this concept forward.

30 October
at 10:30

Room: MR1

On the Nexus between Carbon Cycle and Air Quality: Exploring Multiple Constraints on Anthropogenic Combustion and Fires

Speaker: Ave Arellano
(University of Arizona, LATMOS/UPMC)

### Abstract

It  is  imperative  that  we  provide  more  accurate  and  consistent  analysis  of  anthropogenic  pollution emissions at scales that is relevant to air quality, energy, and environmental policy.

Here, we present three proof-of-concept studies that explore observational constraints  from  ground, aircraft,  and  satellite-derived measurements of atmospheric composition on bulk characteristics of anthropogenic combustion in megacities and fire regions. We focus on jointly analyzing co-emitted combustion products such as CO2, NO2, CO, SO2, and aerosols from GOSAT, OCO-2, OMI, MOPITT, and MODIS retrievals, in conjunction with USEPA AQS and NASA field campaigns. Each of these constituents exhibit distinct atmospheric signatures that depend on fuel type, combustion technology, process, practices and regulatory policies. Our results show that distinguishable patterns and relationships between the increases in concentrations across the megacity or large fire events due to emissions of these constituents enable us to: a) identify trends in combustion  activity  and  efficiency,  and  b)  reconcile  discrepancies  between  state- to  country-based emission  inventories  and  modeled  concentrations  of  these  constituents. For  example, the  trends  in enhancement ratios of these species reveal combustion emission pathways for China and United States that  are  not  captured  by  current  emission  inventories  and  chemical  reanalysis. Analysis of  their  joint distributions  has considerable  potential  utility  in  current  and  future  integrated  constituent  data assimilation and inverse modeling activities like CAMS for monitoring, verifying, and reporting emissions, particularly for regions with few observations and limited information on local combustion processes. Our targeted evaluation of the global forecast and analysis of CAMS CO and CO2 during KORUS-AQ field campaign in  May  2016 suggests that  CAMS  is  able  to  capture the contrast in combustion efficiency between Chinese outflow and Seoul. Analyses of MOPITT and IASI XCO as well as GOSAT XCO2 column retrievals in  CAMS  better  capture the  variability  in  Seoul but  not  in  the  Chinese  outflow  suggesting insufficient constraints over this region. This work also motivates the need for continuous and preferably collocated  satellite  measurements  of  atmospheric  composition  (including  CH4) and  studies  related  to improving  the  applicability  and  integration  of  these  observations  with ground- and  aircraft-based measurements.

16 November
at 15:30

Room: LT

Medium-range forecasts with a non-hydrostatic global atmospheric model on a cubed sphere grid

Speaker: Song-You Hong (KIAPS, Seoul, Korea)

### Abstract

Korea Institute of Atmospheric Prediction Systems (KIAPS), Seoul, Korea, has embarked a national project in developing a new global forecast system in 2011. The ultimate goal of this 9-year project is to replace the current operational model at Korea Meteorological Administration (KMA), which was adopted from the United Kingdom’s Meteorological Office’s model. Since July 2015, the test version of the Korean Integrated Model (KIM) system that consists of a spectral element non-hydrostatic dynamical core on a cubed sphere and a revised physics package has been running in a real-time testbed. In 2017, an updated KIM with the advanced 4-DEnvar at about 12-km has been launched.  Its performance and operational deployment schedule will be presented, together with a special focus on the aerosol indirect effects on the medium-range forecasts.

21 November at 15:30

Room: LT

Evolutions and developments of global data assimilation at Météo-France

Speaker: Loïk Berre and Gérald Desroziers

### Abstract

The global data assimilation at Meteo-France is based on the IFS/ARPEGE model. The current and next configurations of the deterministic and ensemble components of this system will be briefly reminded. This includes a specific normalisation of the wavelet correlation model, which has been recently implemented.

As the error covariance specification plays a crucial role in the assimilation system, a diagnostic study of error contributions in data assimilation cycling is being conducted. This is based on a linear expansion of forecast error as function of contributions with specific ages (i.e. either old, or recent) and of different types (observations, model, background). Specific perturbations are then activated in the Ensemble Data Assimilation (EDA) system, in order to diagnose error contributions from old background states, and also from recent observations. The contribution of recent model errors is then diagnosed by comparing information provided respectively by a specific EDA experiment and by innovation-based diagnostics.

The growing role of ensembles also motivates the development of the 4DEnVar formulation, which has received increasing interest during recent years. From the beginning, Meteo-France has made the choice to implement this new 4DEnVar scheme within the OOPS (Object Oriented Prediction System) framework, initiated at ECMWF. In particular, with such a system, the background error covariance matrix is an object that can take different forms.

Unlike most implementations of 4DEnVar, the formulation developed at Meteo-France relies on the use of 4D state control variables instead of so-called alpha control variables. It also enables an observation space control variable to be used. Moreover, the use of the 4D state as control variables makes easier the formulation of hybrid 4DEnVar. In this case, the 4D state control variable remains indeed unchanged, while the background error covariance matrix simply becomes a linear combination of ensemble localised covariances and wavelet-based covariances.

Several developments related to 4DEnVar will be presented, such as the diagnosis of horizontal and vertical localisations, and the advection of localisation in order to account for dynamical effects. With the intention of using a common localisation for the different variables, and also in order to account for anisotropic aspects of the mass/wind cross-covariances, scale transformations are applied to wind and surface pressure. A parallelized version of the EDA component of 4DEnVar will also be presented, together with preliminary results.

22 November at 13:30

Room: LT

Statistical post-processing of ensemble forecasts for wind speed

Speaker: Sándor Baran (University of Debrecen, Hungary)

### Abstract

Ensemble forecasts often show an underdispersive character and may also be biased, so that some post-processing is needed to account for these deficiencies. We present different versions of two popular methods for calibration of wind speed forecasts, namely the Bayesian model averaging and the ensemble model output statistics (EMOS). Both approaches provide estimates of the probability density functions of the predictable weather quantities, where model parameters are estimated using forecast ensembles and validating observations from a given rolling training period. The presented models are applied to wind speed forecasts of the fifty-member ECMWF ensemble and the eleven-member ALADIN-HUNEPS ensemble of the Hungarian Meteorological Service. The results indicate improved calibration of probabilistic and accuracy of point forecasts in comparison to the raw ensemble and to the climatological forecasts.

We also show two semi-local methods for estimating the EMOS coefficients where the training data for a specific observation station are augmented with corresponding forecast cases from stations with similar characteristics. Similarities between stations are determined using either distance functions or clustering based on various features of the climatology, forecast errors, and locations of the observation stations. In a case study on wind speed over Europe with forecasts from the Grand Limited Area Model Ensemble Prediction System, the proposed similarity-based semi-local models show significant improvement in predictive performance compared to standard regional and local estimation methods. They further allow for estimating complex models without numerical stability issues and are computationally more efficient than local parametrization.

30 November at 10:30

Room: LT

Dynamically Consistent Parameterization of Mesoscale Eddies

Speaker: Pavel Berloff (Imperial College)

### Abstract

This work aims at developing a new approach for parametrizing mesoscale eddy effects for use in non-eddy-resolving ocean circulation models. The idea is to approximate transient eddy flux divergence in a simple way, to find its actual dynamical footprints, and to relate these footprints to large-scale flow properties.

7 December at 10:30

Room: LT

NOAA Center for Weather and Climate: Data, Information and Services

Speaker: Michael Tanner (NOAA Center for Weather and Climate)

### Abstract

The NOAA Center for Weather and Climate (CWC) within the National Centers for Environmental Information (NCEI) is the official data management entity for climatological, oceanographic, and geophysical information in the United States.

CWC performs data synthesis, and data and information dissemination to promote the scientific integrity and usefulness of its products and services. As a part of this responsibility, CWC analyses long-term environmental trends through monitoring and assessment at multiple temporal and spatial scales. CWC also ensures scientific data stewardship of its holdings, including both remotely- and directly-sensed climate and weather, oceanographic, and geophysical data records including related and derived environmental information. CWC also performs quality assurance and reanalysis of historical data to establish and update baseline data sets or standards for global and national environmental monitoring.

CWC advances and enables weather and climate science and decision-making through the acquisition, monitoring, analysis, synthesis, and delivery of observations, derived products and assessments, and information and outreach services. CWC engages across the US, international organizations, the private and public sectors to promote awareness, understanding, access and use of its data, information and capabilities to ensure that all products and services meet user requirements.

11 December at 14:00

Room: LT

Improved winter Euro-Atlantic atmospheric blocking in high-resolution simulations with EC-Earth

Speaker: Paolo Davini (ISAC-CNR, Torino, Italy)

### Abstract

The numerical simulation of atmospheric blocking, in particular over the Euro-Atlantic region, still represents a main concern for the climate modeling community. Here we discuss winter atmospheric blocking representation in a set of atmosphere-only climate simulations produced with EC-Earth during the Climate SPHINX PRACE project. This includes 30-year long runs at five different horizontal resolutions (from T159 to T1279) with several ensemble members (up to 10).

Results show that the usual negative bias in blocking frequency over Europe becomes negligible at T511 and T799. A combined effect by the more resolved orography and by a change in tropical precipitation is identified as the source of an upper tropospheric planetary wave. At the same time, a weakening of the meridional temperature gradient reduces the upper level baroclinicity and the zonal mean winds. Following these changes, in the high resolution configurations the Atlantic eddy-driven jet stream is weakened favoring the breaking of synoptic Rossby waves over the Atlantic ridge and thus increasing the simulated European blocking frequency.

However, at high-resolution the Atlantic jet stream is too weak and the blocking duration is still underestimated. This suggests that the optimal blocking frequencies are achieved through compensation of errors between eddies found at upper levels (too strong) and eddies at lower levels (too weak).

## 2016

7 January
at 10:30

Room: MR1

Fire and haze in Indonesia: causes, impacts and predictability

Speaker: Dr Robert Field (NASA, USA)

### Abstract

The 2015 fire season in Indonesia began in August, following the start of the dry season in July. By September, much of Sumatra, Kalimantan, Singapore, and parts of Malaysia and Thailand were covered in thick smoke, affecting the respiratory health of millions of people. At its peak, visibility was reduced to less than 10% of normal in places, and large parts of Borneo could not be seen from space. Preliminary estimates suggest that greenhouse gas emissions from the burning exceeded those of Japan’s mean annual fossil fuel emissions.  Even after the worst of the fire was over, the remnant pollution stretched halfway around the equator. It was an environmental and public health catastrophe, made all the worse by the fact that we knew of its potential several months earlier.

2015 was a repeat of events that have occurred in Kalimantan since the 1980s and in Sumatra since at least the 1960s. Fires set to clear land and remove agricultural residues escape into degraded peat soil, which can become flammable during stronger-than-normal dry seasons. Once the fire is underground, it is extremely difficult to extinguish, and can burn continuously until the return of the monsoon rains. Research since the 1997/98 haze disaster has given us a reliable understanding of how much fire and haze will occur for a given drought strength, which is strongly influenced by large-scale climate patterns such as El Niño. Ongoing research into the socio-economic drivers of the fire is beginning to identify the roles of landholders large and small. Solving the problem will ultimately involve eliminating fire from degraded peatlands, which, long-term, will need to be re-wetted and re-habilitated, and done in the context of difficult issues surrounding the governance of Indonesia’s natural wealth and the need for economic development.

In the short-term, however, an urgent priority is to develop systematic responses to medium and long-term weather forecasts. Prevention and pre-preparedness measures need to be triggered when forecasts begin locking in on dangerously strong dry seasons, even if the forecasts are issued when it is still wet. This is not unrealistic. Basic fire danger rating systems are now established in Indonesia and are used to monitor for dry conditions. There was also meaningful progress in Indonesia’s operational response this year, including the acceptance of international fire-fighting assistance. The problem is that burning occurs opportunistically, and as soon as conditions are dry enough. The operational response was too late, and would have been far more effective if action were taken in response to the forecast, with a strong focus on prevention, rather than to the crisis. I argue that early warning triggers tied to medium and long-term rainfall forecasts, such as those produced at the ECMWF, are central to reducing severe fire and haze in Indonesia.

Robert Field is a Columbia University Associate Research Scientist at the NASA Goddard Institute for Space Studies. He works with the GISS climate model, specializing in the water cycle, and the cause, fate, and effects of emissions from biomass burning. From 2000-2004, he was part of a joint project between the governments of Indonesia, Malaysia and Canada to develop fire danger rating systems in the region. He has a PhD in atmospheric physics from the University of Toronto.

20 January
at 10:30

Room: LT

NASA Science: Observing Earth, Observing Other Earths

Speaker: Dr Ellen Stofan (NASA, USA)

### Abstract

NASA science pushes the boundaries of our knowledge about Earth, the Solar System including our Sun, and the universe. Our studies of Earth are helping us to better monitor and model our changing climate, and to help increase climate resilience around the world. NASA looks beyond Earth to explore the planets of our solar system, expanding our understanding of planetary climates and addressing the question- Are we alone? Telescopes such as Kepler have shown that planetary systems are common; the next generation of telescopes will be used to begin studying the atmospheres of planets around other stars.

21 January
at 10:30

Room: LT

From parameterising to resolving: the role of eddies and resolution in coupled models

Speaker: Helene Hewitt (Met Office Hadley Centre, UK)

### Abstract

As the resolution of coupled models has increased, the representation of eddies in the ocean component has changed from being parameterised to resolved. We show results from coupled models that span the eddy regime and discuss why high resolution and explicit representation of eddies might be important across the full range of prediction timescales. In particular, recent results from a version of HadGEM3 with a 1/12 degree ocean suggest that ocean eddies and resolution may play an important role in accurately simulating the climate system. Future plans around traceability and experiment design to assess the role of ocean resolution are discussed.

26 January
at 14:00

Room: LT

Empowering drought management in the Middle East and North Africa through timely data provision

Speaker: Dr Rachael McDonnell (ICBA)

### Abstract

Drought is a constant presence in the Middle East and North Africa (MENA) region. Current droughts reveal the gaps and limitations in drought management in the region. Drought conditions in the southern Levant in January and February 2014 once again emphasized the urgent need to support the governments and people in these countries in developing efforts to manage the impacts of these extreme events. This need is further heightened by any analysis of future climate conditions in the region.

The talk will highlight how modeling and data generation will be used to support decision-makers in the region to try to mitigate some of the impacts. The Middle East and North Africa-Regional Drought Management System (MENA RDMS) will harness the enormous innovations from the ongoing data revolution to bring new climate/water/food data as part of monitoring and early warning systems. These are vital components in implementing preparedness and mitigation measures. It will serve the region by:

• Establishing a regional drought monitoring and early warning system and associated information delivery systems
• Providing assessment of drought vulnerabilities and impacts
• Assist officials who are charge with relief efforts by providing “value-added” information during drought events.

2 February
at 10:30

Room: LT

IFS refactoring for OOPS

Speakers: M. Fisher, A. Geer, P. Lean, O. Marsden, D. Salmond, Y. Tremolet & T. Wilhelmsson (ECMWF, UK)

### Abstract

Work on OOPS has progressed and related refactoring has taken place in recent months in many parts of the IFS code. We will present the refactoring work and give an overview of the changes in the code that have happened and that can be expected in the coming cycles. We will focus on changes in the existing IFS code rather than OOPS itself.

The following aspects will be presented:

• Introduction
• Geometry and Model objects, SPAM
• Trajectory handling
• Jb, background and first guess
• ODB interface
• GOM and HOP interfaces
• Upcoming IFS cycles

8 February
at 10:30

Room: LT

Strategies for seasonal forecasting with equatorial bias correction

Speaker: David Mulholland (University of Reading, UK)

### Abstract

Seasonal forecast skill depends crucially on the accurate and balanced initialisation of the ocean, and this is complicated by the need to use a bias correction scheme during ocean data assimilation to deal with errors in wind stress forcing. It has been found that this initialisation method, as used in the current operational seasonal forecast system, leads to an initialisation shock when the bias correction term is removed, which introduces spurious variability into the tropical thermocline and appears to degrade forecasts of sea surface temperature (SST). Alternative initialisation methods have been tested using sets of 7-month forecasts, including one in which the bias correction term is slowly removed during the forecasts, rather than being removed instantaneously at t=0. This essentially removes the initialisation shock, and results in improved SST forecast skill as measured in several key regions.

29 February
at 10:30

Room: MR1

Better observations, better forecasts?

Speaker: Francois Massonnet (BSC, formerly IC3, Barcelona)

8 March
at 14:00

Room: MZR

Spectral/hp element discretisations for Massively Parallel Computing

Speaker: Prof Spencer Sherwin (Imperial College, London)

### Abstract

Compact high order approximations using spectral/hp element discretisations combine the desirable approximation properties of spectral methods with the complex geometry capabilities of finite volume or finite element methods. However an additional advantage of these discretisations is the alignment of their computational footprint with the emerging hardware where computational speed is much dictated by memory movement as floating points operations. Over the past ten years we have been developing an open-ware spectral/hp element framework, Nektar++ (www.nektar.info) to broaden the application of these methods and facilitate their utility.  Part of the framework has permits us to allowed to compare continuous Galerkin projection (CG) used in classic finite element methods with Discontinuous projections such as the Discontinuous Galerkin (DG) or Flux Reconstruction methods. In this presentation we will outline our studies comparing CG and DG implementations for the type of elliptic operators we adopt in our semi-implicit approximation of the incompressible Navier-Stokes equations. We will then outline our current developments under the EU exascale project, ExaFlow (http://exaflow-project.eu/) , to combine the favourable properties of the CG and DG approximations to adapt the projections to hardware communication hierarchies.   We will then outline our current application of these technique to high Reynolds number aerodynamics prediction related to Formula One cars and emerging application such as shallow water formulations.  www.sherwinlab.info

10 March
at 10:30

Room: CC

Microphysics Matters? A Global Perspective

Speaker: Dr Richard Forbes (ECMWF, UK)

### Abstract

Microphysics deals with molecular scales, driven at the "cloud" scales of turbulent motions and atmospheric dynamics, but with impacts that are global. How do we reconcile these different scales? How do we know how much of the complexity of the real microphysical world we have to observe, understand and represent in our global models? I will discuss these issues in the context of parametrization in GCMs and then focus on one example of cloud over the Southern Ocean in the IFS, where most global NWP and climate models have large systematic errors. Understanding the source of this error in terms of microphysics has implications for utilising data assimilation for model error diagnosis, for development of model parametrizations, and for reducing a regime-dependent systematic error with potentially far-reaching global consequences relating to hemispheric albedo and prediction of cross-equatorial transport.

22 March
at 10:30

Room: LT

Forecast Verification - Decision Support Analytics

### Abstract

Changes in models, observations or even computing approaches are all likely to result in changes to forecasts.  When the forecast change is small, identifying if it is an improvement can be challenging and expensive.  Decision support statistics can help identify even very small improvements.  By making use of paired forecasts, and respecting the day-to-day and even hour-to-hour autocorrelation in weather, forecasts and forecast errors, identification can be made more efficiently and with higher likelihood of long-term success.

Perhaps just as importantly, statistical input can help design evaluation runs to minimize cost while maximizing the power of the results.  For instance, the number of runs can be reduced significantly, if forecasting evaluation techniques are determined in advance.  These decision support techniques can be used to determine if an added set of observations is significant, whether a computer change is systematically more harmful, or if the impact of small changes to physics packages or model cores will have a long-term positive impact.  Techniques will be reviewed and sample results shared.

Dr. Betsy Weatherhead is a senior scientist at U. Colorado at Boulder.  She has worked on issues as diverse as climate change, ozone depletion, radiative transfer and indigenous reports of climate change.

Dr. Weatherhead is proud to share a number of awards including the 2007 Nobel Peace Prize for her contributions to the Intergovernmental Panel on Climate Change.  She often works on topics in atmospheric science that require high level statistical or technical expertise, including developing techniques for evaluating small differences in forecasting skill.  Her work on detecting changes in ozone culminated in the cover story on ozone recovery for Nature in 2006. In the past few years she has been heavily involved in AMS, chairing the AMS Summer Community Meeting in 2011-2014 and founding the AMS Forecast Improvement Group (FIG).  She is currently teaching a new graduate course that she developed in environmental statistics.

23 March
at 14:00

Room: MR1

Land surface model and assimilation system at JMA

Speaker: Kengo Miyaoka (JMA, Japan)

### Abstract

In this seminar, I present the JMA land surface modelling and data assimilation activities. The Simple Biosphere (Sib) Model is used to represent the land surface processes. An Optimal Interpolation is used to analyse snow depth whereas the soil moisture analysis relies on a climatology. The land surface model and data assimilation systems for snow analysis are described, and activities for updating the model are presented. Ongoing research on ASCAT surface soil moisture data assimilation development is also briefly presented.

4 April
at 15:30

Room: MR1

Statistical Post-Processing of GEFS Ensemble Forecasts for Precipitation Accumulations

Speakers: Michael Scheuerer & Thomas Hamill (NOAA, USA)

### Abstract

We present and compare two different methods for statistical post-processing of ensemble precipitation forecasts which are developed and demonstrated with GEFS precipitation reforecasts over the conterminous United States and verified against an 1/8-degree climatology-calibrated precipitation analyses.

The first approach is non-parametric and forms, for each location, an new ensemble from the analyzed precipitation amounts by identifying dates in the past that had reforecasts similar to today’s forecast. A variant of this method is presented that augments the data at each location by finding supplemental locations with similar characteristics (climatology, terrain, etc.). The resulting increase of training data will be shown to be particularly beneficial for the probabilistic prediction of rare events.

As a second approach we consider a parametric method that generates full predictive probability distributions for precipitation accumulations by fitting shifted, left-censored gamma distributions to  statistics of the raw ensemble forecasts. This distribution type is shown to be adequate for modeling the distribution of analyzed precipitation accumulations given the ensemble forecasts both in  situations with good predictability (e.g. at short lead times) and decreased predictability (e.g. at longer lead times or during summer months).

Probabilistic forecasts by both methods will be verified using common metrics (skill, reliability, and so forth). We study how the different ensemble statistics and non-linear components in the parametric approach contribute to its performance, and we discuss, for both methods, the effect of training sample size on the reliability and resolution of the post-processed predictions

6 May
at 11:15

Room: LT

Using advanced data assimilation to improve operational predictions from the NCEP Global Forecast System (GFS) model

Speaker: Daryl Kleist, (University of Maryland, USA)

### Abstract

Data assimilation improvements have been a key component to the increased skill of the operational NCEP GFS model over the past decade. Two significant improvements within the past five years have been related to the introduction of hybrid assimilation, where information from climatological error covariance estimates is combined with flow-dependent ensemble estimates. This talk will focus on the hybrid algorithm developed at NCEP with emphasis on the application of an ensemble-variational (EnVar) algorithm for the GFS including the extension to 4D EnVar. Results derived from both simulated and real observation experiments will be presented, including verification from the current real-time demonstration at NCEP.

Additionally, a discussion of the initialization of tropical cyclones in the operational GFS will be presented. The current operational GDAS/GFS utilizes a combination of vortex relocation, bogus wind assimilation, and assimilation of minimum sea-level pressure information driven by real-time information from operational tropical cyclone forecast agencies. While the mechanical vortex scheme has been demonstrated to reduce track errors in older versions of the GFS, recent sensitivity experiments show that for newer generations of the GFS the mechanical relocation may produce increased errors in track forecasts at longer lead times despite reducing the initial position uncertainty.

Experiments with the full resolution GFS will be utilized to explore the sensitivity on forecasts of Hurricane Joaquin (2015).

10 May
at 10:30

Room: LT

Significance of changes in forecast scores

Speaker: Alan Geer, (ECMWF, UK)

### Abstract

The impact of developments in weather forecasting is measured using forecast verification, but many developments, though useful, have impacts of less than 0.5% (about 0.5h) on medium-range forecast scores. Chaotic variability in the quality of forecasts makes it hard to achieve statistical significance when comparing these developments to a control, and surprisingly large sample sizes may be required. By making an independent realisation of the null distribution used in the hypothesis testing, using 1,885 paired forecasts (about 2.5 years of testing), it is possible to experimentally test the validity of the normal statistical framework for forecast scores. This shows that the naive application of Student's-T can generate too many false results. A known issue is temporal autocorrelation but statistical multiplicity also needs to be considered. For example, across three forecast experiments, multiplicity causes a 1 in 2 chance of a false result. The t-test can be reliably used to interpret the significance of changes in forecast scores, but only when these effects are treated correctly. Given the large sample sizes required to achieve statistical significance in the medium-range, there is need to devise testing strategies to make the best use of scare supercomputer resources. Finally, it is sometimes hoped that short-range verification can avoid the need for medium-range verification, by making an assumption that short-range statistics are indeed an predictor of improvements at longer ranges. However, short-range verification has its own set of problems, which will be discussed briefly.

13 May
at 10:00

Room: MR1

Applications of equal area partitions of the unit sphere

Speaker: Paul Leopardi (Bureau of Meteorology, Australia)

### Abstract

IFS uses an algorithm since 2007 for partitioning the sphere which was developed by our guest speaker Dr Paul Leopardi.

Paul Leopardi's extensive publication history and interests can be found here:
http://maths-people.anu.edu.au/~leopardi/

16 May
at 15:30

Room: LT

Gridded Probabilistic Forecasts of Weather Parameters with an Analog Ensemble

Speaker: Dr Stefano Allessandrini (NCAR, USA)

### Abstract

Forecast information is often distributed as a two-dimensional (2D) product.  We present a novel application of the analog ensemble (AnEn; Delle Monache et al., 2011, 2013) to generate gridded, short-term probabilistic forecasts of 10-m wind speed and 2-m temperature. The AnEn technique has been widely used in both meteorology and  renewable energy applications. It is an effective method to generate skillful and reliable probabilistic predictions of meteorological variables, the wind and solar power for short-term forecasts up to 72 hours. It is based on a historical dataset including measurements paired with corresponding deterministic predictions. For each forecast lead time and location, AnEn is created using the measurements corresponding to the past deterministic predictions that are more similar to the current forecast. Until recently the AnEn technique proposed by Delle Monache et al. (2013) has been used to generate predictions at specific locations, where observations are available. By using an analysis field as the ground-truth AnEn is extended here over a 2D grid, where each grid point is considered as a different location and treated independently. An in-depth analysis of AnEn skill and a comparison between AnEn and ECMWF-EPS forecasts will be presented.

18 May at 14:00

Room: LT

Ocean and Coupled Data Assimilation: theory, practice, and what lies on the horizon

Speaker: Prof Stephen Penny (University of Maryland and NCEP, USA)

### Abstract

As the community transitions to fully coupled Earth system models as the norm, we will need to gain a more general understanding of data assimilation to apply it appropriately in new contexts. We will begin with a brief exploration of alternative mathematical foundations of data assimilation, examine the application of atmospheric-oriented data assimilation techniques to the ocean and how these might fail, and highlight potential future opportunities and problems in coupled DA.

18 May at 10:30

Room: MR1

Atmospheric seasonal forecasts of the 20th Century: multi-decadal variability in predictive skill of the winter NAO

Speaker: Antje Weisheimer (ECMWF, UK)

### Abstract

Recent studies suggest that considerable success as been achieved in forecasting seasonal climate anomalies over the Euro-Atlantic area during recent winters. However, this raises the question of how long a sample period is needed to estimate seasonal skill robustly. A new ensemble of retrospective atmospheric seasonal forecasts using the ECMWF model and ERA-20C covering the period 1900 to 2009 has been created which provides the opportunity to study many aspects of atmospheric seasonal climate prediction - here I will discuss the multi-decadal variability aspect of predicting the winter NAO.

10 June at 11:30

Room: LT

Skilful seasonal winter forecasts for Europe

Speaker: Adam Scaife (Met Office, UK)

### Abstract

We discuss recent evidence that the extratropical winter circulation in the Atlantic region is predictable.  Forecasts from the latest Met Office GloSea5 and decadal predictions systems exhibit highly significant skill levels for predictions of the NAO and associated winter weather when tested over past decades. In this seminar we discuss the evidence for this predictability, it's sources and mechanisms, and the performance of real time forecasts since these systems became operational.  We also highlight a raft of new potentially skilful climate services that could be driven by this important development

15 June at 14:00

Room: LT

Why does it rain over the Great Plains at night?

Speaker: David Parsons, (University of Oklahoma, USA)

### Abstract

Researchers have shown beginning 100 years ago that convection over the Great Plains of North American has a nocturnal maximum during the summer. The dynamical explanation for these nocturnal storms is still actively debated in the scientific literature and such systems are often poorly represented in weather and climate models. Nocturnal convection was also the focus of a major field experiment over the central United States called PECAN (Plains Elevated Convection at Night). This talk presents results from three studies by the authors exploring the behavior of nocturnal convective systems within the context of the regional environment through observations, theory, and modeling. This research suggests that the interaction between cold pools generated by nocturnal convection and the region’s low-level jet commonly falls within a partially blocked flow regime that will lead to generation of bores. These bores are long-lived and produce net upward displacements of air that often approaches or exceeds 1 km. The combination of this ascent and advection of moisture by the low-level jet can lead to nocturnal conditions aloft that are more favorable for deep convection than those stability profiles found in the boundary layer during the day.  The role of bores in initiating and maintaining convection at night over this region will be illustrated leading to speculation that such processes may need to be parameterized in weather and climate models

20 June at 15:30

Room: LT

Impact of the QBO on Predictability of the MJO

Speaker: Harry Hendon (Bureau of Meteorology, Australia)

### Abstract

The MJO during boreal winter is observed to be significantly stronger during the easterly phase of the QBO than during the westerly phase for the period 1982-2014. Using 33 years of hindcasts from the POAMA coupled model forecast system and other available hindcasts from the S2S archive, we show that this strengthened MJO activity during the easterly QBO phase translates to improved prediction of the MJO by up to 9 days as depicted by the RMM indices. Forecast skill is higher for events of similar initial magnitude in QBOE years compared to QBOW years, thus ruling out higher skill in QBOE years simply because the MJO was overall stronger. Although it is as yet unclear as to whether there is an impact of the QBO on the MJO during the forecasts, a simple forecast sensitivity experiment suggests that the QBO-easterly phase favors an eastward expanded Indo-Pacific convective region.  Thus, stronger, longer lasting MJO’s should be favoured in QBOE years due to an expanded region of warm pool convection. However, the mechanism of impact of the QBO on the MJO, especially the seasonality of the impact, is as yet established.

8 July at
14:00

Room: MR1

Plant hydraulics and response to water stress

Speaker: Pierre Gentine (Columbia University, USA)

### Abstract

In this presentation we will show how the biosphere regulates land-atmosphere interactions on monthly times scales and in particular how plant hydraulics influences the response of plants to droughts. We will show how new remote sensing products (vegetation optical depth in the microwave spectrum and sun-induced fluorescence) can be used to evaluate those feedbacks between the biosphere and the atmosphere and to constrain the land-surface models as well as atmospheric processes (clouds in particular) over continents. We will discuss implications for sub- to seasonal predictions.

11 July at
10:30

Room: LT

Revisiting hydrometeorology using cloud and climate observations

Speaker: Alan Betts (alanbetts.com)

### Abstract

A review of the insights into hydrometeorology that have emerged from the analysis of 620 station-years of the Canadian Prairie hourly data: the role of snow as a climate switch that drops temperature on the Prairies by 10K, and transforms the BL coupling; the long memory of 2-5 months of precipitation anomalies; the 24-hr imbalance of the diurnal cycle as a function of cloud cover; and the coupling coefficients between temperature and humidity anomalies and cloud/radiation and precipitation in the warm season. These provide a solid observational basis for model evaluation (refs: see alanbetts.com)

12 July at
10:30

Room: LT

Panasonic Weather: From Observing Systems to Global Modeling

Speaker: Neil Jacobs (Panasonic Avionics Corporation, USA)

### Abstract

Panasonic Weather (formerly AirDat) has been in the weather space since the late 1990s and running global models since 2007.  This talk will focus on Panasonic's global modeling program, including new observing systems, quality control processes, data assimilation, ensemble configuration, various aspects of radiation and physics schemes, air-sea coupling, parallel testing and “R2O”, as well as computational resource and hardware management.  Additionally, a brief overview will also be provided on nested limited area models, and how optimizations to those models feed back enhancements to the global model.

Bio:

Dr. Jacobs directs the research and development of both the tropospheric airborne meteorological data reporting system (TAMDAR), as well as the numerical models run by Panasonic. His areas of expertise include mesoscale dynamics, numerical weather prediction, and data assimilation. He is the chair of the American Meteorological Society’s Forecast Improvement Group, and also serves on the WMO’s aircraft-based observing systems expert team. Prior to joining Panasonic (AirDat) in 2005, Dr. Jacobs worked on various analysis and modeling projects including NASA's Earth Systems Science Program, GOES satellite imagery, Department of Energy's Ocean Margins Program, and the National Weather Service's Atlantic Surface Cyclone Intensification Index.  He has a BS in mathematics and a BS in physics from the University of South Carolina, a MS in air-sea interaction from North Carolina State University, and a PhD in numerical modeling from North Carolina State University.

15 July at
10:30

Room: LT

Model Error and Data Assimilation

Speaker: Mike Fisher (ECMWF, UK)

This seminar will be repeated on 22 July at 10:30 in MR1

### Abstract

As analyses become more accurate, it becomes increasingly necessary to take model error into account in our data assimilation algorithms. In this seminar, I will give an update on progress in representing model error in 4dVar, discuss the relevance of a weak-constraint formulation to parallelisation of 4dVar, and suggest directions for future research.

15 July at
13.30

Room: LT

Particle filters in high dimensions

Speaker: Chris Snyder (NCAR, USA)

### Abstract

Particle filters offer an elegant solution to the problem of state estimation. They make no assumptions about the form of the underlying probability distributions and, in principle, are applicable in the presence of strong nonlinearity and non-Gaussianity. Driven in part by geophysical applications, much recent work has focussed on particle-filter algorithms for high dimensional systems. I will review the basics of particle filters and then present a small sample of further topics: reasons that high-dimensional system are especially challenging for particle filters, a bound on the performance of an important class of particle filters, and a potential path toward more effective high-dimensional particle filters.

2 September at 10.30

Room: MR1

Understanding the physical drivers of extreme rainfall at different spatial and temporal scales

Speaker: James Doss-Gollin (Columbia University, USA)

### Abstract

We have been using as a case study the Ohio River Basin in the Midwest USA. We show that the dominant mechanism of extreme rainfall in this region is consistent with eastward-propagating frontal systems and a dipole-like pressure schematic which draws moisture from the Caribbean and Gulf of Mexico, particularly in non-summer seasons. The frequency of regional extreme precipitation events varies considerably at an annual scale, and we find clear signatures in geopotential height and temperature fields of the most "active" seasons (in number of regional extremes). Finally, I’ll discuss our ongoing progress in work seeking to relate the transient frontal systems earlier identified to transient Rossby waves; I'll present some preliminary results on how persistent, high-amplitude, low-frequency (quasi-stationary) waves may modulate the occurrence of these transient systems and thus extreme rainfall; with regional (Ohio River Basin) and hemispheric spatial scales

12 September at 14:00

Rom: MR1

SMOS neural network soil moisture assimilation

Speaker:  Nemesio Rodriguez Fernandez (CESBIO, France)

### Abstract

Neural networks (NN) are an efficient tool perform a non-linear mapping from SMOS brightness temperatures to soil moisture datasets. I will discuss two applications (the first one briefly):
i) the new SMOS Near-Real-Time soil moisture dataset implemented at ECMWF and delivered to ESA and EUMETSAT.
ii) the assimilation of SMOS soil moisture fields obtained with a neural network trained on H-TESSEL model predictions. The bottom-line idea is that this soil moisture dataset shows similar properties with respect to the model while it is driven by the input brightness temperatures. In a first step we have used the offline surface-only assimilation system forced with ERA-Interim. The results of these experiments have been compared to those of the assimilation of ASCAT soil moisture and to in situ measurements in a large number of sites (>400). In a second step, the analysed surface fields were used to run atmospheric forecasts. The results are promising as assimilating SMOS NN soil moisture shows a positive impact in the forecast of air temperature and relative humidity.

23 September at 13.30

Room: LT

What is the ultimate predictability limit of weather

Speaker: Fuqing Zhang (Penn State University, USA)

### Abstract

Through high-resolution deterministic and ensemble sensitivity experiments with both regional and global models, and with both realistically large and minute idealized initial perturbation uncertainties, this talk seeks to answer what is the ultimate predictability limit of multi-scale weather. Highlights will be given to severe weather events such as midlatitude winter storms, tropical cyclones and tornadic thunderstorms.  These experiments suggests such a limit may exist both in terms of overall global error energy at different wavelengths and in terms of feature-based verifications of individual events. Such a limit is intrinsic to the underlying dynamic system and instabilities even if the forecast model and the initial conditions are nearly perfect. Minute uncontrollable initial conditions originated from small-scale instabilities can grow upscale that will eventually limit the predictability of various weather at increasingly larger scales.

7 October
at 10.30

Room: LT

Ground-based GNSS data processing and assimilation at the UK Met Office

Speakers: Jonathan Jones and Gemma Halloran (Met Office, UK)

### Abstract

Ground-based GNSS meteorology exploits the delay in the travel time of a signal from a Global Navigation Satellite System (GNSS) satellite reaching a receiver on the ground. The Zenith Total Delay (ZTD) is a measure of the excess path travelled by a GNSS signal through the atmosphere (were a satellite at zenith) compared to its path through a vacuum. Through the EIG EUMETNET GNSS Water Vapour Programme and its predecessors, several European institutions have been actively involved in ground-based GNSS meteorology for more than 15 years, and ZTD has been operationally assimilated in global and regional NWP models since 2007. As a column integrated observation, influenced by both humidity and surface pressure, ZTD assimilation poses a number of challenges. In this seminar, we will give an overview of GNSS data processing, the current state of the art in ground-based GNSS meteorology, and discuss some of the challenges behind assimilating ZTD observations.

2 November
at 10.30

Room: MZR

The influence of the spatial scale of initial-condition errors on atmospheric predictability

Speaker: Prof. Dale Durran (University of Washington, USA)

### Abstract

One important limitation on the accuracy of weather forecasts is imposed by unavoidable errors in the specification of the atmosphere's initial state. Much theoretical concern has been focused on the limits to predictability imposed by small-scale errors, potentially even those on the scale of a butterfly. Very modest relative errors at much larger scales may nevertheless pose a more important practical limitation. We demonstrate the importance of large-scale uncertainty by analyzing ensembles of idealized simulations of mesoscale convective systems.  We consider several environments with different low-level shears and pairs of ensembles with equal amplitude large- or small-scale perturbations in the surface moisture.

As foreshadowed by results obtained with a simple barotropic model in a largely overlooked section of Lorenz’s classic 1969 paper “The predictability of a flow which possesses many scales of motion,” equal-amplitude initial perturbations at wavelengths of 8 and 128 km produce identical losses of predictability after five hours of simulation.  These results imply that minimizing initial errors on scales on the order of 100 km is at least as likely to extend the accuracy of forecasts at lead times longer than 4-5 hours than potentially expensive efforts to minimize initial errors on much smaller scales.

These simulations also demonstrate that convective systems, triggered in a horizontally homogeneous environment with no initial background circulations, can generate a background mesoscale kinetic energy spectrum with a slope proportional to the -5/3 power of the wave number, similar to that observed in the atmosphere.  The horizontally divergent and rotational parts of the kinetic energy spectrum are examined along with their relative contributions to the -5/3 spectrum.

3 November
at 10.30

Room: MR1

Weakly or strongly nonlinear mesoscale dynamics?

Speaker: Erik Lindborg (Royal Insitute of Technology, Sweden)

### Abstract

It has been shown that wave number spectra at  atmospheric  mesoscales (length scales from ten to a couple of hundred km) display an approximate minus five-third third power law, just as small scale turbulence. Recently, it has been debated whether the spectra are generated by a strongly nonlinear downscale energy cascade or by weakly nonlinear inertia-gravity waves.  To shed light on this issue investigators have used aircraft data to estimate the ratio, R,  between divergent and rotational energy. In this talk I will argue that a necessary condition for weak nonlinearity is that the group velocity is much larger than a characteristic fluid velocity. This leads to a condition on the Rossby number which is not consistent with observations of the ratio R.  On the other hand, in order for the dynamics to be defined as strongly nonlinear, I suggest that it is sufficient to demonstrate that the kinetic and potential energy spectra,are of Kolmogorov type.  Using data from a huge number of aircraft segments from the MOZAIC data set  kinetic energy  and temperature spectra are calculated in the upper troposphere and stratosphere, using a criterion based on ozone concentration to distinguish between stratospheric and tropospheric segments. We find that all spectra, in particular the stratospheric spectra, display a clean minus five third power law at mesoscales. Making a Helmholtz decomposition, we show that R is slightly larger that unity in the stratosphere while it is smaller than unity in the troposphere at mesoscales. We also show that it is necessary to  use of the order of one thousand flight segments to obtain reasonably converged results for R. Based on these observations we argue that the dynamics is not weakly nonlinear, but is governed by strongly nonlinear interactions.

11 November at 10.30

Room: LT

MJO teleconnections in the S2S database

Speaker: Frederic Vitart (ECMWF, UK)

### Abstract

The World Weather Research Program (WWRP) and World Climate Research Program (WCRP) launched a joint research initiative in 2013, the Sub-seasonal to Seasonal prediction project (S2S) whose main goal is to improve forecast skill and understanding of the sub-seasonal to seasonal time-scale and to promote its uptake by operational centres and exploitation by the application communities. A main deliverable of this project is the establishment of an extensive database containing sub-seasonal (up to 60 days) near real-time forecasts (3-weeks behind real-time) and re-forecasts.  This research database, hosted at ECMWF and CMA, is now available to the research community from the ECMWF and CMA data portals.

This presentation will describe the S2S project and show some preliminary results on the ability of the S2S models to predict the Madden Julian Oscillation and simulate its teleconnections in the Extratropics.

14 November
at 10.45

Room: LT

Lightning at ECMWF

Speaker: Philippe Lopez (ECMWF, UK)

### Abstract

Lightning is a severe weather phenomenon known to affect numerous human activities, in particular through air traffic disruptions, power supply outages, damages to building and the triggering of wildfires. Lightning can also occasionally lead to injuries or even fatalities. A parameterization of lightning has been developed to diagnose lightning flash densities from convective hydrometeor contents, CAPE and convective cloud base height output from the ECMWF convection scheme. Its calibration and validation using LIS/OTD satellite lightning climatology and its comparison against existing parameterizations in 10-year-long 80km resolution simulations will be presented. Examples of applications in higher resolution deterministic forecasts as well as in the ensemble prediction system will then be given. Finally, the sensitivities of lightning (over a target region) to meteorological variables 24 hours earlier, as computed using the adjoint of the lightning parameterization, will be discussed. This will pave the way to future work towards the assimilation of lightning observations, especially from the next-generation of geostationary satellites.

16 November at 10.30

Room: LT

On stochastic representations of model uncertainties

Speaker: Martin Leutbecher (ECMWF, UK)

### Abstract

Members in ensemble forecasts differ due to the representations of initial uncertainties and model uncertainties.   The inclusion of stochastic schemes to represent model uncertainties has improved the probabilistic skill of the ECMWF ensemble by increasing reliability and reducing the error of the ensemble mean. Recent progress, challenges and future plans concerning stochastic representations of model uncertainties at ECMWF are described.  The coming years are likely to see a further increase in the use of ensemble methods in forecasts and assimilation. This will put increasing demands on the methods used to perturb the forecast model. An area that is receiving a greater attention than 5 to 10 years ago is the physical consistency of the perturbations. Other areas where future efforts will be directed are the expansion of uncertainty representations to the dynamical core and to other components of the Earth system as well as the overall computational efficiency of representing model uncertainty.

29 November at 14.00

Room: LT

Semi-Lagrangian semi-implicit finite-difference dynamical core of the SLAV model

Speaker: Mikhail Tolstykh (INM/RAS & Hydrometcentre of Russia, Russia)

### Abstract

The semi-Lagrangian semi-implicit finite-difference dynamical core of SLAV global atmosphere model is presented. Its distinct features are the use of vertical component of the absolute vorticity and the horizontal divergence as prognostic variables, the unstaggered grid, and high-order finite-differences. The dynamical core can use reduced lat-lon grid and the variable resolution in latitude. The algorithm for wind velocity reconstruction (Tolstykh, Shashkin, J Comput Phys 2012) avoids solving Poisson equations on the sphere.

Currently, the SLAV configuration with approximately 13km horizontal resolution can use up to 9000 cores with efficiency more than 50%. So far, we use Fast Fourier transforms (FFT) in some parts of the dynamical core. Hence data transpositions are needed in parallel implementation. We work on scalable iterative grid-point solvers to elliptic problems. Also, we have successfully tested computation of meridional derivatives at the reduced grid in the grid-point space. These developments will help to avoid the use of FFT in the model code thus moving scalability limit further.

## 2015

3 February at 10:30

Room: LT

Solar Radiation Forecasting for the Energy Industry: The Australian experience

Speaker: Alberto Troccoli (Commonwealth Scientific and Industrial Organisation (CSIRO))

### Abstract

Prediction of solar radiation is key in sectors such as solar power and agriculture; for instance, it can enable more efficient production of energy from solar power plants. Specifically, select ECMWF model output is a key input to the Australian Solar Energy Forecasting System (ASEFS), an operational system run by the the Australian Energy Market Operator.

In this talk I will first present the rationale for the ASEFS project. I will then discuss an assessment of the quality of the direct solar radiation forecast by two versions of the ECMWF NWP model up to 5 days ahead. The performance of the model is measured against observations from four solar monitoring stations over Australia, characterized by diverse geographic and climatic features, for the year 2006. As a reference, the performance of global radiation forecast is carried out as well. In terms of direct solar radiation, while the skill of the two model versions is very similar, and with relative mean absolute errors (rMAEs) ranging from 18% to 45% and correlations between 0.85 and 0.25 at around midday, their performance is substantially enhanced via a simple postprocessing bias-correction procedure. There is a marked dependency on cloudy conditions, with rMAEs 2–4 times as large for very cloudy-to-overcast conditions relative to clear-sky conditions. There is also a distinct dependency on the background climatic clear-sky conditions of the location considered. Tests made on a simulated operational setup targeting three quantiles show that direct radiation forecasts achieve potentially high scores. Overall, these analyses provide an indication of the potential practical use of irradiance forecast for applications such as solar power operations.

11 February at 15:30

Room: LT

Statistical post-processing of ensemble weather forecasts: Current developments and future directions

Speaker: Professor Tilmann Gneiting (ECMWF Fellow), Heidelberg Institute for Theoretical Studies (HITS)

### Abstract

Statistical post-processing techniques serve to improve the quality of numerical weather forecasts, as they
seek to generate calibrated and sharp predictive distributions of future weather quantities and events.
I will review the state of the art in post-processing, with focus on ensemble forecasts and ongoing joint work
between the ECMWF and the Computational Statistics group at the Heidelberg Institute for Theoretical
Studies (HITS).  Current and future challenges include the treatment of extreme events, and the calibration of
probabilistic forecasts of combined events and spatio-temporal weather trajectories, for which discrete copula
based techniques, such as ensemble copula coupling (ECC) and the Schaake shuffle, are attractive options.

18 February at 10:30

Room: MR1

Towards a parametrization for surface heterogeneity

Speaker: Chiel van Heerwaarden, (Max Planck Institute for Meteorology, Hamburg, Germany)

### Abstract

We have studied the heterogeneously heated Convective Boundary Layer (CBL) with the aim to create a parameterization for land-surface heterogeneity. This system has been investigated by means of dimensional analysis and results from Large-Eddy Simulations (LES) and Direct Numerical Simulations (DNS). We present results from two different experiments: a CBL that is heated from patches with a fixed surface heat flux, and a CBL that is heated from stripes with a fixed surface temperature. The first experiment represents for instance an urban heat island, whereas the second is applicable to flow over arctic leads. For the first experiment, we show that each simulation contains first the formation of a peak in kinetic energy, corresponding to the “optimal” heterogeneity size with strong secondary circulations, and subsequently the transition into a horizontally homogeneous CBL. We have developed scaling laws that show that the optimal state and transition do not occur at a fixed ratio of the heterogeneity size to the CBL thickness, but instead occur at a higher ratio for simulations with increasing heterogeneity sizes. For the second experiment, we show that imposing a fixed surface temperature directs the system towards a steady state where the release of heat from the warm stripes equals the amount of heat taken up from the cold stripes. In this development, the system travels back and forth between different states and exhibits oscillations in the kinetic energy.

19 February at
10:30

Room: MZR

Integrated simulations of the hydrologic, energy and biogeochemical cycles in terrestrial systems: concepts and applications

Speaker: Prof Stefan Kollet (Bonn University)

### Abstract

In this seminar, I will talk about the simulation approach we are following in the Centre for High-Performance Scientific Computing in Terrestrial Systems (HPSC TerrSys), which is based on coupling of physics-based modeling platforms from the deeper subsurface into the atmosphere closing the hydrologic and energy cycles in terrestrial system models. The resulting integrated Terrestrials Systems Modeling Platform, TerrSysMP, is applied over regional watersheds and the European continent (Euro-CORDEX domain) in order to compare to a suite of in-situ measurements and remotely sensed observations, and understand the challenges and possibilities of the proposed simulation approach. We find that the memory effects of deeper groundwater dynamics pose a challenge in arriving at physically consistent initial conditions, which is also well-known in ocean modeling. The great potential lies in the ability to characterize all components of the hydrologic and energy cycle, which is not possible with more traditional simulation approaches, and, thus, synthesize and assimilate all available observations. Ultimately, we see the possibility of a continental monitoring system of freshwater resources that is based on a fully integrated multi-scale observation-simulation framework.

24 February at 14:00

Room: LT

Bayesian flood frequency analysis for the River Eden in Carlisle, UK, using gauged flow data and historical flood records

Speaker: Brandon Parkes, (King's College London)

### Abstract

The talk will discuss extensions to current methods of extreme value analysis for determining the magnitude of rare floods. The extensions allow recognition of the fact that the observations of discharge are subject to noise.
The characterisation of this noise for both the observed time series and values derived from historic flood records is considered. A Bayesian approach to estimation of the parameters of the extreme value distribution is then utilised to generate predictive bounds. The sensitivity to the assumptions made about the noise is also explored.

6 March at 14:00

Room: LT

Climate science for climate services: the new Met Office Hadley Centre Climate Programme

### Abstract

The first two challenges to climate science have been to establish whether or not the climate is warming, and if it is to what extent the warming is due to emissions of greenhouse gases. The IPCC 5th Assessment Report of Working Group 1 (2013) established that “Changes in the atmosphere, cryosphere and ocean show unequivocally that the world is warming” and that “It is extremely likely (95% certainty) that human influence is responsible for more than half of the warming since 1950”. So the challenges for climate science move now to understanding past, present and future climate variability and change in order to help society and decision makers develop resilience to climate events, make wise adaptation decisions and developing carbon budgets to limit the damage of climate change: Climate science needs to move from the seminar room into actionable information for climate services.

In this talk I shall present the new science programme of the Met Office Hadley Centre, and its role in the broader UK and European context, with emphasis on how we are responding to these new challenges. There are two classes of event that demand attention: climate events, which are of regional scale and of seasonal duration, such as the European summer of 2003 or the UK winter storms of 2013/14, and the character and frequency of high impact weather events, such as heavy rainfall events or high wind events. The goals are to develop observations of past events, to make statements about the role of anthropogenic climate change in increasing the probability of current events, and to develop understanding and prediction systems of future events, from a season ahead, 1-10 years ahead and decades ahead. This programme, we believe, forms the science required to develop climate services, such the Copernicus Climate Change Service.

30 March at
10:30

Room: LT

A new framework for identifying sources and sinks of available potential energy in tropical cyclones

Speaker: Remi Tailleux, (University of Reading)

### Abstract

The intensification of tropical cyclones is often poorly forecast by NWP models. Tropical cyclones intensify as the result of the conversion of available potential energy (APE) into kinetic energy. This deceptively simple definition is hard to use in practice, however, because of the longstanding difficulty to define and quantify available potential energy for a moist atmosphere. In this talk, I'll review the origins of this difficulty and propose a new APE framework that circumvents most of the previous difficulties. Its main new attributes are: 1) it is based in terms of the locally-defined positive definite APE density, which allows for the study of local energy budgets; 2) the reference state does not need to be obtained by an adiabatic re-arrangement of the fluid parcels; 3) it defines separate thermodynamic efficiencies for thermal and moist effects; 4) it cleanly separates boundary sources of APE from interior sinks/sources due to irreversible thermodynamic processes. Some of the concepts will be illustrated in the context of a realistic simulation of hurricane MEGI, and a strategy for identifying weaknesses in model simulations outlined.

Tropical cyclones in a hierarchy of high-resolution GCMs

Speaker: Pier Luigi Vidale, (University of Reading)

### Abstract

Over the last few years we have been developing global models, based on the HadGEM family, to study the impact of resolution on the simulation of the climate system. As the resolution is increased, our focus has been on the emergence of processes, and their interaction with the rest of the climate system. While our tropical cyclone (TC) climatology indicates that the GCMs simulate these phenomena with increasing accuracy in terms of track densities and variability, TC intensity continues to be underestimated. We will show some recent examples from investigations with cloud-system resolving (CSR) models applied in limited area mode, as well as (coarse) global. Preliminary results indicate how, for the Unified Model, a grid spacing of 4km starts to mitigate the problem of biases in TC intensity.

Equally, there is increasing need for data sets that allow robust assessment of climate model performance, but TC observations are scarce and inhomogeneous. We have been collecting and processing a number of re-analysis products in order to understand uncertainty in TC frequency, track density and landfall. Results indicate that the re-analyses are in better agreement for more recent times, which points to the value of data assimilation.

28 April at
14:00

Room: LT

Tropical Cyclone Predictions from the Met Office Global Model: a Brief History and Recent Developments

Speaker: Julian Heming, (Met Office, Exeter)

### Abstract

This presentation will firstly provide an overview of tropical cyclone predictions from the Met Office Global Model with an emphasis on the impact of the initialisation procedure used between 1994 and 2012.

A major upgrade to the Met Office Global Model was implemented in July 2014. This included a major revision to the model’s dynamical core, improved physics and increased horizontal resolution to about 17 km at mid-latitudes. The impact of these changes on both tropical cyclone track and intensity predictions will be presented.

Finally, results will be presented on the impact of a new scheme which became operational in February 2015 to assimilate tropical cyclone warning centre estimates of central pressure in the Met Office Global Model.

8 June at
10:30

Room: MR1

Surface analysis at DWD - present state and future developments

Speaker: Martin Lange, (DWD)

### Abstract

The NWP system at DWD is based on three operational models: ICON, COSMO-EU, and COSMO-DE for the respective global, European and German domain, each with an own assimilation cycle. Current development activities include the ensemble data assimilation both for the global and for convective scale, with a hybrid VarEnKF system for ICON and an ensemble Kalman filter (KENDA) for COSMO. Further, the replacement of COSMO-EU by a nested area over Europe is under intense preparation, and a tile model for ICON is scheduled for operational use in the middle of 2015. Surface analysis is an integral part of all these systems and development steps.

At DWD, the surface analysis is build up by a heterogeneous system of assimilation methods for snow, SST, screen level parameter and soil moisture even changing with the different model suites. Snow and SST analysis make use of an old fashioned Cressman method with blending of external data from NCEP, near surface parameter are analysed with an OI in the global, and a nudging scheme in COSMO-EU. For soil moisture analysis the 2D var method after Hess (2001) is used in C-EU, and a parameterized variant in the ICON analysis which circumvents the additional forecast runs required to determine the Jacobians.

One further aspect of future development at DWD is the use of satellite derived soil moisture data which, besides tuning large scale soil water content itself, should also help to improve surface emissivity that is of general importance for the assimilation of satellite data.

The talk will give an overview about the present system and development activities either integrating the existing surface assimilation methods into ensemble data assimilation or using ensemble Filters also for surface related variables.

12 June at 14:00

Room: LT

Predictability of tropical cyclone tracks: a multi-model multi-analysis approach

Speaker: Takeshi Enomoto (Kyoto University/Application
Laboratory, Japan Agency for Marine-Earth Science and Technology, Japan)

### Abstract

Track error of the forecast of tropical cyclones of major operational centres have been reduced to approximately 100 km per day on the average in recent years. For a particular case, however, some or all forecasts from the operational centres may still fail to predict the observed tracks. We examine the relative contribution of the analysis error and model uncertainty by conducting forecast experiments from multiple analyses using multiple numerical weather prediction and climate models. Case studies for a few tropical cyclones indicate that the ambient flow near the storm centre is of primary importance although the distribution of diabatic heating may have significant influence.

24 June at
14:00

Room: LT

A New Paradigm of ENSO's Impact on Asia Monsoon

Speaker: Prof Fei-Fei Jin (Department of Meteorology
School of Ocean & Earth Science & Technology
University of Hawaii at Manoa)

### Abstract

Several mechanisms have been proposed to explain how ENSO may influence the Asian monsoon. We propose that a significant part of impacts of ENSO on the Asian monsoon is through a previously overlooked ENSO combination mode of Indo-Pacific climate variability generated by the interaction between the Western Pacific warm pool seasonal cycle and ENSO. This combination mode (C-mode) is characterized by near-annual and sub-annual timescales (combination tones) and contributes substantially to the observed low-level atmospheric circulation and precipitation anomalies in West-North Pacific (WNP) region. In fact, this C-mode is a part of more general ENSO frequency cascade as the result of the nonlinear interaction of ENSO with the annual cycle.  This cascade effective transfer from the ENSO power in its interannual band to higher frequencies (combination tones) so to generate ENSO responses not only characterized by different timescales but also by unique circulation and rainfall patterns. This new dynamic theory provides insight into ENSO induced WNP circulation variability and thus ENSO's impact on Asian monsoon system. Moreover, the associated subannual/interannual frequency climate variability is deterministic in its nature and hence as potentially predictable as ENSO.

25 June at
10:30

Room: LT

Improving weather forecasts by including land-surface model parameter uncertainty?

René Orth (ETH, Zürich)

### Abstract

The land surface forms an important component of any Earth system model in general and therefore also of a numerical weather prediction system. The hydrology of the land surface is extremely complex and highly uncertain. In this talk I will demonstrate the importance of recognizing land surface uncertainty parameterization and its impact on predicting future weather.

Focusing on the land-surface model HTESSEL we present in this study a novel methodology for a comprehensive calibration using multiple observational datasets in Europe. We select 6 poorly constrained parameters which we vary using multiplicative factors. To explore the entire parameter space we perform a large number of uncoupled simulations with different combinations of parameter perturbations. Therefrom we derive the sensitivity of HTESSELs performance to individual parameters and identify several best-performing parameter perturbations. We discuss our findings within the context of the current default parameter set.

Furthermore we carried out several sub-seasonal coupled forecasts using the current ECMWF ensemble prediction system, which includes HTESSEL. In this context we employ the best-performing versus additional, randomly chosen parameter perturbations. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations. This shows that a calibration using uncoupled (and hence less computationally demanding) simulations may lead to improvements in a coupled model. This is remarkable since the sensitivity of the forecast skills to individual HTESSEL parameters differs from the sensitivities computed from the uncoupled simulations.

Finally, we construct weather forecast ensembles using ensemble members derived with different best-performing parameter perturbations of HTESSEL. We show that this incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, partly even beyond the skill of the present default system.

24 July at
10:30

Room: LT

Intrinsic versus Practical Limits of Multi-Scale Atmospheric Predictability

Speaker: Fuqing Zhang (Dept. of Meteorology, Penn State University, USA)

### Abstract

This talk I will present our recent findings on the limits of intrinsic versus practical predictability of multi-scale severe weather phenomena ranging from tornadic thunderstorms, hurricanes and winter cyclones through convection-permitting real-data case simulations and idealized “identical-twin” experiments. We seek to understand both the intrinsic limits of predictability of such severe weather events under nearly perfect initial conditions given a nearly perfect forecast model, and the practical limits of predictability given the current level of (practically large) uncertainties in the forecast model and initial conditions. Highlights will be given to the multi-scale error growth dynamics within idealized baroclinic waves with varying degree of convective instabilities. In the dry experiment free of moist convection, error growth is controlled primarily by baroclinic instability under which the forecast accuracy is inversely proportional to the amplitude of the baroclinically unstable initial condition error (and thus predictability can be continuously improved without limit through reducing the initial error). Under the moist environment with strong convective instability, rapid upscale growth from moist convection will lead to the forecast error being increasingly less sensitive to the scale and amplitude of the initial perturbations when the initial error amplitude is sufficiently small; this will ultimately impose a finite-time barrier to the forecast accuracy (limit of intrinsic predictability). However, if the initial perturbation is sufficiently large in scale and amplitude (which is likely the case for most current-day operational models), the baroclinic growth of large-scale finite-amplitude initial error will control the forecast accuracy at all scales for both dry and moist baroclinc waves; forecast accuracy can be improved (and thus limit of practical predictability can be extended) through reduction of initial condition errors, especially those at larger scales.

14 September at 10:30

Room: MR1

IASI retrievals of dust properties

Speaker: Virginie Capelle (LMD, France)

### Abstract

Aerosols represent the dominant uncertainty in radiative forcing, partly because they present a very high spatio-temporal variability and remaining uncertainties concerning their composition, size, etc. In this context, satellite observations may offer a global and continuous
observation at high resolution. In particular, remote sensing in the thermal infrared has several advantages: observations are available both for daytime and nighttime, dust characterization is possible over desert and, even more important, vertical sounders allow retrieving dust layer mean altitude. Here are presented 8 years of dust aerosol properties (AOD and mean altitude) retrieved from IASI from July 2007 up to now. The method is based on a “Look-Up-Table” (LUT) approach, where all radiative transfer computation is performed once for all and “off-line”, for a large selection of atmospheric situations, of observing conditions, of surface characteristics (in particular the surface emissivity and temperature), and different aerosol refractive index models. Dust AOD is compared with AERONET visible coarse-modeAOD. Mean
aerosol layer altitude  is compared at local scale with the
Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP/CALIPSO) aerosol altitude. First results combining IASI and AIRS observations will be also shown, given the opportunity to observe dust at four points of the day: ~9:30AM/PM for IASI/METOPA and ~1:30AM/PM for AIRS/AQUA, opening the way to the analysis of the aerosol diurnal cycle.

18 September at 10:30

Room: MR1

Carbon Monoxide Data Assimilation for Atmospheric Composition and Climate Science: Evaluating Performance with Current and Future Observations

Speaker: Jerome Barre (NCAR, USA)

### Abstract

Current satellite observations of tropospheric composition made from low Earth orbit provide at best one or two measurements each day at any given location. Comparisons of Terra/MOPITT carbon monoxide (CO) and IASI/Metop CO observation assimilations will be presented. We use the DART Ensemble Adjustment Kalman Filter to assimilate observations in the CAM-Chem global chemistry-climate model. Data assimilation impacts due to both different instrument capabilities (i.e. vertical sensitivity and global coverage) will be discussed. Coverage is global but sparse, often with large uncertainties in individual measurements that limit examination of local and regional atmospheric composition over short time periods. This has hindered the operational uptake of these data for monitoring air quality and population exposure, and for initializing and evaluating chemical weather forecasts. By the end of the current decade there are planned geostationary Earth orbit (GEO) satellite missions for atmospheric composition over North America, East Asia and Europe with additional missions proposed. Together, these present the possibility of a constellation of geostationary platforms to achieve continuous time-resolved high-density observations of continental domains for mapping pollutant sources and variability on diurnal and local scales. We describe Observing System Simulation Experiments (OSSEs) to evaluate the contributions of these GEO missions to improve knowledge of near-surface air pollution due to intercontinental long-range transport and quantify chemical precursor emissions. Our approach uses an efficient computational method to sample a high-resolution global GEOS-5 chemistry Nature Run over each geographical region of the GEO constellation. The demonstration carbon monoxide (CO) observation simulator, which will be expanded to other chemical pollutants, currently produces multispectral retrievals (MOPITT-like) and captures realistic scene-dependent variation in measurement vertical sensitivity and cloud cover. The impact of observing over each region is evaluated independently. Winter and summer cases studies are investigated i.e. where emissions, cloud cover and CO lifetime significantly change.

20 October
at 10:30

Room: LT

Key conclusions of the first international urban land surface model comparison project

Speaker: Sue Grimmond, (University of Reading, UK)

### Abstract

The first international urban land surface model comparison was designed to identify three aspects of the urban surface-atmosphere interactions:
(1) the dominant physical processes
(2) the level of complexity required to model these
(3) the parameter requirements for such a
model.
Offline simulations from 32 land surface schemes, with varying complexity, were considered. Model results were analysed within a framework of physical classifications and over four stages. These results, whilst based on a single site and less than 18 months of data, have implications for the future design of urban land surface models, the data that need to be measured in urban observational campaigns, and what needs to be included in initiatives for regional and global parameter databases.

21 October at 11:00

Room: LT

Metrological approach to Earth Observation uncertainties: the project FIDUCEO

Speaker: Chris Merchant (University of Reading, UK)

### Abstract

For many historic Earth Observation (EO) datasets that are key to climate science and meteorological re-analysis, uncertainty information is absent, generic, unrealistic and/or partial. This is true both for Fundamental Climate Data Records (FCDRs – i.e., observed radiances) and [Thematic] Climate Data Records (CDRs — containing geophysical products). This is clearly unsatisfactory: long-term records of meteorological and climate variables from space-based observations need to provide trustworthy information about variability and change over decades, so that they can be used for rigorous science, decision-making and climate services (including re-analysis).

Improved realism and rigour are needed in the generation of FCDRs and CDRs in relation to stability and uncertainty information, and this is the aim of the H2020 project "Fidelity and Uncertainty in Climate data records from Earth Observation" (FIDUCEO).

Defensible uncertainty estimates need to be realistic (demonstrably not underestimating uncertainty) and traceable (obtained by assessing and propagating all known effects that introduce uncertainty). FIDUCEO will develop realistic, traceable uncertainty information for four FCDRs (AVHRR, HIRS, MW humidity sounders, Meteosat VIS). New versions of these FCDRs with harmonised calibration across the full sensor series will be developed in a common format that supports calculation of observation error covariances or alternative ensemble members. Example geophysical CDR products will be derived from each FCDR, with uncertainty estimates obtained by uncertainty propagation. Beyond the products directly generated, the project aims to demonstrate and promote better handling of uncertainty in EO datasets and applications by providing cookbooks and tools.

The seminar will give an overview of the project, its rationale and its approach. How in practice metrological principles apply to EO will be illustrated with reference to one FCDR. Aims include stimulating discussion on how improved uncertainty information can be relevant within data assimilation, and highlighting the opportunities to be involved in trail blazing applications of FIDUCEO data.

30 October
at 10:30

Room: LT

JMA's New Seasonal Prediction System
(JMA/MRI-CPS2)

Speaker: Yuhei Takaya (JMA, Japan)

### Abstract

A new version of JMA’s Seasonal Ensemble Prediction System (JMA/MRI-CPS2) was implemented to JMA's operational suite in June 2015. The system is used to produce three-month, warm/cold season and El Niño predictions. I will present an overview of the JMA/MRI-CPS2 and improvements with changes made in the new version. The changes include improved resolution and physics in atmospheric and oceanic components and the introduction of an interactive sea ice model. Verification of reforecasts shows that JMA/MRI-CPS2 has higher predictive skill than JMA/MRI-CPS1 for the seasonal and El Niño predictions.  Some preliminary diagnostics indicate that the new features such as the sea-ice coupling, land initialization, and greenhouse gas forcing are contributed to improve predictive skills. Predictive skills are also compared with those of some systems in the EUROSIP system.

13 November
at 13:00

Room: MR1

Estimation of observation errors and their correlations in AIRS radiance data

Speaker: Pierre Gauthier, University of Québec in Montréal (on sabbatical at the Dept. of Meteorology, University of Reading)

### Abstract

Diagnostics of statistical consistency proposed by Desroziers/et al./ (2005) have been used in recent studies to estimate the observation error for many types of observations. In particular, it has been found that for hyperspectral infrared sounders like AIRS or IASI, there is an important interchannel observation error correlation that must be taken into account. To get around this observation error inflation or thinning  of the data can be used but at the expense of not extracting all the information contained in these observations. The Desroziers diagnostics offer an approach that can provide an estimate of those interchannel correlation which have been found to be beneficial in terms of impact on analyses and forecasts (Bormann /et al./, 2010; Stewart /et al./, 2013; Garand and Heilliette, 2015). In this presentation, a 1D model is introduced which uses a Jacobian of the RTTOV as a 1D linear observation operator, and the background error statistics from the Environment Canada variational data assimilation system. In this framework, the error statistics are specified and known and have been used to investigate the properties of the Desroziers iterative procedure to get information about the observation error correlations. As pointed out in other studies (e.g., Ménard, 2015), an additional constraint is necessary to discriminate between estimated background and observation error. If the background error statistics are assumed to be the true ones and kept fixed, then fitting the innovations covariances yields the true observation error. It is also possible to assess the impact of having in reality under- or over-estimated the background-error.

Taking a different angle on the problem, observation error correlations can be associated with representativeness error due to sub-grid scale variability. Using a high resolution (2.5 km) model, the sub-grid scale variability has been estimated and its image in observation space provides a physically-based representation of the observation error. Results from very preliminary experiments  indicate that this could be a sound alternative but it requires more work to take into account other components that make up representativeness error as presented in Chun et al.(2015).

20 November
at 14:00

Room: LT

ICEMUSIC - a new THz instrument concept for climatology and meteorological applications

Speaker: Peter Hargrave, (University of Cardiff, UK)

### Abstract

Clouds play a crucial role in the global climate system and energy budget of the atmosphere, in that they reflect near-infrared radiation back to space (cooling effect), whilst reflecting thermal emission from the Earth's surface back to Earth (warming effect). The net effect on the atmosphere is very important to understand. It depends on the cloud's horizontal extent, vertical position, ice water content, and ice microphysical properties, all of which influence the cloud's optical thickness. These parameters are currently poorly constrained in global circulation models, and represent large uncertainties in predictions of future climate.

We have developed a novel instrument concept to observe ice clouds and humidity that will allow us to retrieve these critical parameters. This instrument uses large arrays of detectors to make observations in the millimetre and submillimetre wavelength regions. It completely avoids the need for mechanical scanning, and has large advantages over the "traditional" heterodyne instruments proposed for this type of observation. Particularly, we benefit from high sensitivity, high spatial and spectral resolution, and we have access to frequency ranges not currently available with heterodyne technology. Recent technology developments will also allow such an instrument to significantly enhance the accuracy and resolution of temperature and humidity profiles.

23 November
at 15:30

Room: LT

The non-hydrostatic IFS from the point of view of the limited area version

Speaker: Mariano Hortal, (HIRLAM Project Leader on Dynamics)

3 December
at 10:30

Room: MR1

Representation of midlatitude atmospheric variability in global datasets: a spectral perspective

Speakers: Alessandro Dell’Aquila and Susanna Corti (ISAC-CNR, Italy)

### Abstract

We here present a process-oriented metric to evaluate global datasets in terms of their capability in reproducing the midlatitude atmospheric variability. In particular this methodology allows a separation of propagating and standing components of the atmospheric waves following the spatio-temporal spectral decomposition introduced by Hayashi (1979).

This technique has been recently applied to ERA-CLIM simulations (Dell’Aquila et al 2015) in order to evaluate signals of multi-decadal variability for planetary and baroclinic waves in the centennial reanalysis product as well as in the corresponding AMIP simulations . The results have been compared with a series of different reanalysis products, which assimilate atmospheric observations with increased diversity: from surface-only to surface, upper air and satellite observations.  All reanalyses are in good agreement regarding the representation of variability during the last decades of the twentieth century. This suggests that the assimilation of surface observations can generate high-quality extratropical upper-air fields. In the first decades of the twentieth century a suppression of high frequency variability is apparent in the centennial reanalysis products. This behaviour does not have a counterpart in the model integrations.

The capability of model simulations to reproduce the spatial patterns associated with low and high frequency disturbances, and the corresponding underlying processes, is also assessed.

References

Dell’Aquila A, Corti S, Weisheimer A, Hersbach H, Peubey C, Poli P, Berrisford , Dee D, Simmons  A (2015) Benchmarking midlatitude variability in centennial reanalyses and model simulations, Submitted to Geophysical Research Letters

Hayashi, Y. (1979), A generalized method of resolving transient disturbances into standing and travelling waves by space-time spectral analysis, J. Atmos. Sci., 36, 1017–1029, doi:10.1175/1520-0469(1979)

10 December at 10:30

Room: MZR

Atmospheric Boundary Layer features over complex heterogeneous terrain

Speaker: Joan Cuxart (University of Balearic Islands)

### Abstract

This talk will summarize some of the findings of the experimental campaigns made by the Atmospheric Boundary Layer (ABL) research team of the University of the Balearic Islands (UIB) since 2009. Campaign design, data analysis and high-resolution modelling are the three main tools described. The effect of the topography and the surface heterogeneities at different scales as observed in several locations (Garonne and Ebro basins, Mallorca, the Pannonian basin or the Cerdanya valley in the Pyrenees) will be summarily described, with special focus on the nocturnal boundary-layer features and the evening and morning transitions. A recurring picture seems to emerge and will be discussed in the seminar. On the other hand, we have a research station at the UIB Campus since 2013, located in a semi-rural area outside the city of Palma, where we measure all the terms of the Surface Energy Budget and most of the variables of the atmospheric surface layer and of the upper part of the soil. Instrumentation can be disposed at the most interesting configuration for any purpose, including initialization or validation of SVAT schemes. Furthermore, during 2016, a display of 10 supplementary energy-budget stations will be displayed in selected areas of the Campus (roughly 1 km^2), to evaluate the sub-kilometer variability of the measured quantities, in the so-called "Subpixel" campaign. Possible cooperation with the ECMWF using this experimental site may be explored.

11 December at 14:00

Room: MZR

Can the end of Moore's law improve resolution in climate modeling and weather prediction?

Speaker: Krishna V. Palem (Rice University, USA)

### Abstract

Many claim that the laws of physics dictating exponential growth in transistor scaling or Moore’s Law will end in the next 10 to 20 years. This argument is based, in part, on an analysis that switching devices cannot function deterministically as feature sizes get reduced to the molecular level. Moore’s Law, however, could continue if systems with nondeterministic switches could process information usefully. My research that aims to exploit this principle, dubbed inexact computing, suggests that circuits and computing architectures can be used effectively at molecular scale. Succinctly put, inexact computing systems allow compromises in accuracy to be traded for significant, often disproportionately high gains in performance and energy consumption. Surprisingly, climate modeling and weather prediction provide great opportunities in this regard. For example, we have shown collaboratively, through simulations, that by lowering the precision of the mantissa, the dynamical core of an IGCM application yields savings through inexactness of (almost) a factor of 3 in energy without compromising the quality of the forecast. Given a fixed energy budget, this result implies that we can afford to compute at higher resolution; a back-of-the-envelope calculation shows that a factor of eight in energy savings would allow us to double the model’s resolution. In active collaboration with colleagues at Argonne National labs on the supercomputing front, and Tim Palmer and Peter Duben at Oxford University, we are currently working to demonstrate that existing supercomputers with half-precision instructions can potentially help us achieve resolution gains by exploiting inexactness. A goal of my talk is to invite collaboration from colleagues at ECWMF to join our consortium with the eventual goal of working towards improved resolution in the IFS model.

Krishna V. Palem is the Ken and Audrey Kennedy Professor at Rice University with appointments in Computer Science, in Electrical and Computer Engineering and in Statistics, and a scholar in the Baker Institute for Public Policy. He was a Moore Distinguished Faculty Fellow at Caltech in 2006-2007, and a Schonbrunn Fellow at the Hebrew University of Jerusalem in 1999, where he was recognized for excellence in teaching. In 2002, he pioneered a novel technology entitled Probabilistic CMOS (PCMOS) and laid the foundations of inexact computing.  PCMOS and its potential applications were respectively recognized as one of the ten technologies 'likely to change the way we live' by MIT's Technology Review in 2008, and as one of the seven 'emerging world changing technologies' by IEEE as part of its 125th anniversary celebrations in 2009.  In 2012, Forbes (India) ranked him second on the list of eighteen scientists who are “some of the finest minds of Indian origin.” He is a Fellow of the IEEE, the ACM and AAAS, and the recipient of the IEEE Computer Society's 2008 W. Wallace McDowell Award. He was named a Guggenheim fellow in 2015 to pursue the research direction suggested by this abstract.

11 December
at 15:30

Room: LT

Forecasts triggering humanitarian action: methods, successes, and challenges

Speaker: Erin Coughlan (Red Cross)

### Abstract

Recognizing the potential value of existing weather and climate forecasts to anticipate extreme events, the Red Cross Red Crescent Movement and the World Food Programme are piloting a new approach called "Forecast-based Financing". This approach not only makes funding available for humanitarians to act based on a forecast (before a disaster happens), but develops standard procedures so that people automatically take action based on a predefined forecast threshold for extreme weather.

Come join this talk to hear which forecasts we are using around the world, from cyclone forecasts in Mozambique to GloFAS flood forecasts in Peru, and how we have recently successfully triggered action in advance of a disaster. We hope to solicit your recommendations and suggestions, as well as discuss further collaboration to scale up this concept and automatically use forecasts to prevent future humanitarian disasters around the globe.

## 2014

15 January 15:30

LT

Large eddy simulation of urban flows in an idealized fractal model city

Sonja Gisinger (Univ Innsbruck)

### Abstract

The majority of human activities and their impacts (e.g. pollution emission) takes place in the lowermost part of the atmosphere, especially in the extensively growing cities. Knowledge about the flow field and its modification through urban areas is essential for numerical weather and air quality predictions. The questions, how to describe an urban area, and how to parameterise its impact on the atmosphere in numerical prediction models must be considered.

In our work, we treated a city as a porous medium with a fractal geometry. We created an idealised model city (cf. Fig. 1) out of the Sierpinski triangle, a self-similar fractal with a fractal dimension of ≈1.585, and implemented it in EULAG using the immersed boundary method.

In analogy to Darcy's law, which describes the flow through a porous medium at low Reynolds numbers, we seek the relationship between the mean horizontal flow and the horizontal pressure gradient [1] for our high Reynolds number (turbulent) flow. A series of numerical simulations of the turbulent flow through the Sierpinski city was conducted for different flow speeds and different building heights. They indicate that the modified Darcy's law is valid for the turbulent flow through the fractal model city.

23 January 11:00

MR1

Using satellite observations and models to understand processes in the composition-climate system: Some examples

Apostolos Voulgarakis (Imperial College)

### Abstract

During the last decade, a wealth of satellite observations has brought a new era in atmospheric science as it has provided the opportunity for continuous monitoring of the state of the atmosphere on large spatial scales. There is enormous potential in using such data for understanding large-scale processes in the composition-climate system. Here, I will present how we have used such satellite observations in conjunction with global model sensitivity experiments in order to examine the interannual variability of important tropospheric constituents such as ozone, CO, NO2 and aerosols. Particular focus will be placed on the influence of biomass burning emissions. Furthermore, I will discuss the value of using such satellite datasets in combination rather than individually, in order to investigate and evaluate processes in composition-climate models. The focus will be on a study that examines the global correlation of tropospheric ozone and CO, two important constituents that are interrelated in a complex way. Finally, future plans on how such satellite-based analysis can be expanded using more observational datasets will be discussed.

27 January 10:30

LT

Representing model uncertainty in the ECMWF convection scheme

Hannah Arnold (Atmospheric, Oceanic and Planetary Physics, University of Oxford)

### Abstract

In order to produce reliable probabilistic weather forecasts, it is important to account for all sources of error in atmospheric models. In the case of weather prediction, the two main sources of error are due to initial condition uncertainty and model uncertainty – this talk will focus on how to represent the latter. Two approaches are considered – the use of a perturbed parameter scheme, and the use of stochastic parametrisations. The problem is first illustrated using idealised experiments in the Lorenz ’96 “toy model” of the atmosphere, before the two approaches are considered in the context of the convection parametrisation scheme in the IFS. For the perturbed parameter approach, four uncertain parameters are identified in the convection parametrisation scheme, and a Bayesian technique is used to estimate the degree of uncertainty in their values. Both a fixed and stochastically varying perturbed parameter scheme are then tested in the IFS. Finally, we test a generalisation to the SPPT stochastic parametrisation scheme, in which the tendencies from different physics schemes are perturbed independently. This results in a large improvement in ensemble forecast spread in the tropics. The talk concludes by considering the limitations of the study, and suggesting future avenues of research.

20 February 10:30

LT

Tropical cyclones' influence on the ocean: from event scale processes to climate scale consequences

Gurvan Madec (Locean-IPSL, Paris and NOC, Southampton)

### Abstract

Strong winds associated to Tropical Cyclones (TCs) trigger intense mixing in the upper ocean. While the resulting surface cooling feeds back negatively on TCs intensity, the associated sub-surface warming has been suggested to substantially modify the ocean heat transport. A 1⁄2 ° global ocean model experiment that realistically samples the ocean response to more than 3,000 TCs over the last 30 years is used to first investigate the processes controlling the TC-induced surface cooling at the local scale and then to assess the impact of TCs at the global scale.

Vertical mixing is the dominant process of the cooling occurring locally close to the TC track. It will be shown that the cooling magnitude can be described by combining an index measuring the storm’s power and an index measuring the resistance to surface cooling by upper-ocean stratification. The cooling is very sensitive to the pre-storm upper-ocean stratification, which can modulate its amplitude by up to an order of magnitude for a given storm’s power.

The processes explaining the surface cooling under TCs also participates to modify the mean ocean heat budget. Previous studies have focused on the climatic importance of TC- induced mixing, but cooling is increasingly due to surface heat fluxes as we consider larger space scales. Both heat fluxes and vertical advection associated to TCs are shown to also influence the ocean mean state. Vertical mixing does induce an enhanced ocean heat uptake consistent with previous estimates. However, most of the heat injected into the ocean during TC seasons is re- entrained by the winter mixed layer deepening. As a consequence, we find that the main TCs’ climatological impact is to reduce the amplitude of surface temperature seasonal cycle more than to modify the ocean heat transport.

24 February 16:00

MCR

Predictability of wintertime Euro-Atlantic weather regimes in medium-range forecasts

Mio Matsueda (University Oxford)

### Abstract

A weather regime is a persistent and/or recurrent large-scale atmospheric circulation pattern which is associated with specific weather conditions on a regional scale. Accurate simulations of weather regimes are important in weather and climate. The predictability of Euro-Atlantic weather regimes at medium-range timescales (up to 384hr) are investigated for winter (December-February) in the periods 2006/07-2012/13 and 1984/85-2012/13 using the THORPEX Interactive Grand Global Ensemble (TIGGE) and NOAA’s second-generation global medium-range ensemble reforecast datasets, respectively. The TIGGE portals quasi- operationally provide 9 medium-range ensemble forecasts routinely operated at NWP centres. We focus on five of the leading operational NWP centres: CMC, ECMWF, JMA, NCEP, and UKMO. The NOAA’s reforecast data has been produced with a fixed operational NWP model, using the 2012 version of NCEP’s Global Ensemble Forecasting System (GEFS), whereas the TIGGE data has been produced with a various versions of operational NWP model. The positive and negative phases of the NAO (NAO+ and NAO-), Atlantic ridge (ATLR), and Euro- Atlantic blocking (EABL) are detected as weather regimes over the Euro-Atlantic region from the ERA-Interim data. The NWP models have common biases in the frequency of regime transitions, and therefore the models prefer NAO- and ATLR to NAO+ and EABL with lead time, compared with the ERA-Interim. The models show small skill differences regarding probabilistic regime forecasts, suggesting that the skills of regime forecasts strongly depend on atmospheric flows. The models show higher forecast skills when predicting NAO+ and NAO-. The NAO+ and NAO- forecasts have a better skill than its climatological forecasts even at a lead time of 16 days. The persistence of NAO-is the most predictable. In contrast, EABL forecasts from ATLR have the lowest skill, followed by ATLR forecasts from NAO+, ATLR, and EABL.

19 March 10:30

LT

Production of ERA-20CL: An ensemble of 20th-century global land-surface reanalyses with 25km resolution

Takuya Komori (ECMWF)

### Abstract

As one of the products of ERA-CLIM reanalysis project, a set of global land surface reanalysis with 25km-resolution (referred to as ERA-20CL) for the period of 1900-2010 is currently in production. The production of ERA-20CL is based on meteorological forcing from the ERA-20C atmospheric reanalysis, involving application of downscaling techniques. Both the 10-member ensemble and the deterministic version of ERA-20CL are being produced following configurations of the forcing data set.

I will present some verification results of ERA-20CL products, and diagnostics to compare the performance with other reanalysis products.

16 April 10:30

LT

Implementation of 4D-EnVar and other improvements in Environment Canada's Global Deterministic Prediction System (GDPS)

Mark Buehner (Environment Canada, Data Assimilation and Satellite Meteorology Research Section)

### Abstract

Major changes to the data assimilation component of the GDPS will be described in this presentation. The most significant change is the replacement of 4D-Var with the 4D ensemble-variational data assimilation approach (4D-EnVar). This approach uses background ensembles generated by the global ensemble Kalman filter (EnKF) to estimate 4D flow-dependent background-error covariances. This enables a 4D analysis to be produced without needing the tangent linear and adjoint versions of the forecast model. Consequently, 4D-EnVar is much more computationally efficient and easy to maintain and adapt than 4D-Var. Other important changes include an improved satellite radiance bias correction scheme; assimilation of additional AIRS/IASI channels; improved treatment of radiosonde (4D) and aircraft observations; and the assimilation of ground-based GPS data. Results showing the impact of these changes (including also, the use of incremental analysis update, IAU, and recycling of physics variables) will be presented in preparation for the implementation of these changes in a parallel run.

2 May 14:00

LT

Revisiting the role of Sea Surface Temperature Structure in Tropical Oceanic Rainfall

Richard E. Carbone (Chief Scientist for Strategic Development and Research Earth Observing Laboratory, NCAR, Boulder, CO)

### Abstract

Past studies of sea surface temperature (SST) in relation to tropical ocean rainfall have arrived at somewhat divergent conclusions with respect to SST and gradients thereof (e.g. Neelin and Held, 1987; Lindzen and Nigam, 1991). Unlike most studies, Li and Carbone (2012) examined this issue from a mesoscale perspective, nominally at 100km scale, in an attempt to clarify the circumstances under which rainfall is triggered in the tropical western Pacific. They examined a 49 month timeseries of SST and rainfall as estimated from satellite observations. The seminar will begin with a brief summary of results, which shows a high frequency of mesoscale SST gradients and a propensity for onset of rainfall near the mode of the regional SST spectrum. While the statistical inference of dependence on SST is weaker than one might expect, coincidence with the convergent Laplacian of SST is strong.

The current work mainly emphasizes anomalies of and correlations between SST structure and rainfall in the MJO pass-band across the eastern hemisphere. The statistical inferences are, at once, broadly consistent with conventional wisdom on the role of SST in rainfall production and the pivotal role played by the convergent Laplacian of SST. It is concluded that the main role of SST in tropical oceanic rainfall is in production of moist static energy. That is to say, SST bears a decidedly conditional and somewhat indirect relationship to the occurrence of rainfall: i.e. if rain occurs, then more rain is likely over warm anomalies of SST. The SST Laplacian mainly triggers rainfall events through induced vertical air motion with sufficient kinetic energy to overcome convective inhibition in a conditionally unstable troposphere. Its role is directly associated with the frequency of rainfall events, however, it bears little direct relationship to cumulative rainfall beyond its capacity to influence approximately where, when, and how many events occur.

9 May 10:30

MR1

Extreme value estimation with the ACER method

Prof Arvid Naess (Norwegian University of Science and Technology)

### Abstract

Some background on the ACER method
The prediction of long return period values based on observed data for design purposes has been the subject of extensive research over many years. However, there does not seem to be a general agreement on the method and extreme value distribution that would serve these purposes in a completely satisfactory manner. Standard methods for estimating extreme values from limited sets of observed data are commonly based on assuming either that the distribution of epochal extreme values converges to a Gumbel (type-I extreme value distribution) or by adopting a peaks-over-threshold (POT) approach, assuming that the exceedances above high thresholds follow a generalized Pareto distribution . A weakness of these approaches is that they depend on adopting asymptotic distributions. However, it is hard to verify the applicability or correctness of such procedures. Here we establish a method for predicting extreme wind speeds and significant wave height that avoid invoking the ultimate asymptotic distributions, but rather try to capture to some extent also the sub-asymptotic behaviour of extreme value data. This has resulted in a method that appears to be more appropriate for the purpose of predicting for example extreme wave heights than the traditional methods based on asymptotic theory. In addition to a procedure for optimizing the fit to data, the method consists of constructing a cascade of conditional distributions that makes it very easy to account for dependence effects in the data time series. The resulting sequence of conditional distributions constitute an increasingly accurate representation of the exact extreme value distribution given by the data. In fact, when this sequence of conditional distributions has converged, an exact representation of the extreme value distribution given by the data has been obtained since then no approximations have effectively been made. Thus, a plot of these conditional distributions will provide a unique insight into the dependence structure of the recorded data time series.

16 May 09:30

LCR

Global Water Data Sharing

David Maidment (Center for Research in Water Resources, University of Texas at Austin) and James Nelson (Brigham Young University)

### Abstract

Talk 1: Global Water Data Sharing: Progress and Trends
Speaker: David Maidment, Center for Research in Water Resources, University of Texas at Austin

Scientists are increasingly being asked to share not only publications of findings but the data used to make those discoveries. The Consortium of Universities for the Advancement of Hydrologic Sciences Inc (CUAHSI) in response to developing tools for better management of hydrologic data has been involved with the OGC and WMO in developing the world standard WaterML for the way time series information at points can be shared. Such tools are making the ability to share data a reality and with an increasing amount of remotely sensed data and other applications available for flood, drought, and water resources management governments and others should be increasingly motivated to share information. David will discuss the current status and future possibilities that WaterML and water data services provides.

Talk 2: Applications of Water Data Sharing with Opportunities to Improve Flood Early Warning Systems in Latin America
Speaker: James Nelson, Brigham Young University

Less developed countries of the world lack resources including hardware, software and more importantly the human capacity necessary to manage their water information. Where initiatives have been undertaken to, they often are unable to pay for maintenance. Data and software tools like the CUAHSI HIS system are helping them join larger communities such as the Group on Earth Observations (GEO) that are pooling resources and making better water data management possible. Jim will discuss how the CUAHSI tools and the initiatives of GEO for data sharing are enabling them to use and create systems that will help them better manage their water resources with a particular emphasis on Flood Warning.

28 May 10:30

LT

Some remarkable properties about the energy balance of Earth

Graeme Stephens ( Jet Propulsion Laboratory, University of Reading and Met Office)

### Abstract

Perturbations to the Earth's energy balance force climate change. The latitudinal variation of the energy balance establishes regional climate zones through its influence on the atmospheric and ocean circulations that, in turn, move heat poleward. We currently lack a quantitative understanding of how this energy balance and the poleward energy transport adjust to different forcings that determine climate change and no constraint exists to guide this understanding in either observations or models. This talk will use observations gathered over the past decade to show how the Earth's energy balance exhibits a remarkable symmetry about the equator. It will be further argued that this symmetry is largely a consequence of a vanishingly small amount of heat transported across the equator and is a necessary condition of a steady state climate. Analysis will show that it is the clouds that are the principal agent that regulates this symmetric condition and it will also be shown that present-day climate models deviate substantially from the symmetric condition of Earth. The relevance of such symmetry will be speculated on.

3 June 10:30

LT

Use of GPS radio occultation data at ECMWF

Sean B Healy (ECMWF)

### Abstract

ECMWF will host a ROM SAF workshop on "The Applications of GPS radio occultation (GPS-RO) measurements" on June 16-18, 2014. As background information for the workshop, this seminar will review the GPS-RO the measurement technique, and explain how the data is assimilated at ECMWF. This will include a description of the new two dimensional forward operator being implemented in CY40R3. It will be shown that the GPS-RO is an important "anchor" measurement, but it has a null-space, meaning that some temperature biases are difficult to detect. The possible use of GPS-RO datasets for the direct testing model changes likely to affect stratospheric temperatures will be discussed.

9 June 14:00

MZR

Mitigating Model Error in CO Emission Estimation

Martin Keller (Department of Physics, University of Toronto)

### Abstract

Atmospheric CO has a significant impact on the oxidative capacity of the atmosphere via reaction with OH, and is furthermore a precursor of tropospheric ozone. In order to correctly model CO concentrations in chemical transport and chemistry climate models, good knowledge of surface emissions of CO is required. In recent years, a number of
studies have attempted to estimate CO emissions via a top-down or data assimilation approach. However, the tacit assumption assumption of a perfect transport model made in all data assimilation methods has been shown to lead to considerable uncertainties in the estimated emissions.

In this talk, I will present results from my attempts to mitigate the impact of model errors in top-down estimates of CO emissions using the GEOS-Chem 4D-Var inversion framework. First, I will present results from a newly implemented weak constraint 4D-Var system in the GEOS-Chem inversion framework, and discuss the benefits and challenges of weak constraint 4D-Var in emission estimation. Afterwards, I will present results from multispecies inversion experiments using space-based observations of  CO, O3, and NO2 and discuss the impact of constraining ozone concentrations and NOx emissions on estimated CO emissions.

30 June 14:00

LT

Overview of NOAA Data Assimilation Systems and Plan of a Global 4DVAR System

Yuanfu Xie, NOAA ESRL

### Abstract

There are several major efforts in improving global and regional data assimilation systems at NOAA. From NOAA National Weather Service to NOAA Office of Atmospheric Research, different data assimilation methodologies have been developed and tested collaborating with other research institutes, agencies and universities, such as 3DVAR, 4DVAR, EnKF and hybrid approaches. For lack of strong evidence of 4DVAR superiority, many NOAA data assimilation systems tend to use variations of ensemble approaches, hybrid 3DVAR or 4D-EnVar. In this presentation, we will review these efforts and discuss a possible global multi-scale 4DVAR system for NOAA future data assimilation. Some features of this system, along with supporting numerical experiment results, will be discussed during this presentation.

2 July 10:30

LT

The GOES-R Geostationary Satellite System and NWP User Readiness

Steven Goodman, NOAA/NESDIS GOES-R Program Office

### Abstract

NOAA’s Geostationary Operational Environmental Satellites (GOES) are a mainstay of weather forecasts and environmental monitoring in the United States. The next generation of GOES satellites, known as the GOES-R Series, is scheduled for launch in late 2015 and will usher in a new era in geostationary environmental satellites. The GOES-R satellites will provide continuous imagery and atmospheric measurements of Earth’s Western Hemisphere that will foster a host of improved and new environmental products and services.
GOES-R’s primary instrument, the Advanced Baseline Imager (ABI), will provide twice the spatial and three times the spectral resolution while scanning the Earth nearly five times faster than the current GOES. GOES-R will also host a new instrument, the Geostationary Lightning Mapper (GLM) that is designed to continuously map in-cloud and cloud-to-ground lightning with a 8 km spatial resolution and 80 percent detection efficiency over the Western Hemisphere. It will provide information to improve severe storm monitoring and warnings and contribute to improved aircraft safety and efficient flight route planning. GOES-R’s space weather instruments will provide improved observations of the sun and space environment with more timely dissemination and early warning to a diverse user community.
This presentation will provide an overview and status update of the GOES-R program and the activities leading to an operational GOES-R system. The new observations will provide dramatically improved weather, water, and space environmental services in the coming decades, enhancing public safety and providing economic benefits to the U.S. and our international partners.

3 July 14:00

LT

A modification of the IFS semi-Lagrangian trajectory scheme to improve forecasts of Sudden Stratospheric Warming events

Michail Diamantakis, ECMWF

### Abstract

Sudden Stratospheric Warming (SSW) events are poorly forecast by IFS. An investigation has shown that this poor performance is strongly linked with semi-Lagrangian numerics and particularly with the time extrapolation method used for computing the departure points. In this talk used algorithms for computing the departure points will be briefly reviewed. Different options for improving IFS forecasts of such events will be explored focusing on a recently proposed simple modification of the existing scheme. It will be shown that this method achieves large improvement of SSW forecasts without increasing computational cost.

7 July 14:00

LT

Evolution of Ensemble Data Assimilation at ECMWF

Massimo Bonavita, ECMWF

### Abstract

The Ensemble of Data Assimilations (EDA) has been a key contributor to the improved skill of both the high resolution (HRES) and ensemble forecasting (ENS) systems at ECMWF in recent years. This is mainly due to its ability to provide realistic estimates of the analysis and background error covariances in the data assimilation cycle. In this talk we review recent progress in the use of EDA-based error estimates in the 4D-Var analysis cycle.

On the other hand, computational constraints effectively limit the size and resolution at which the EDA can be run in operations, which limits the fidelity of the error estimates that can be obtained from the EDA and introduces sampling noise. This has led to exploring more efficient and scalable avenues for the cycling of the errors of the data assimilation cycle. Results from this experimentation will be presented and the implications of their adoption for operational use will be discussed.

30 July 10:30

LT

Coupling of diurnal and seasonal climate to clouds, precipitation, land-use and snow cover on the Canadian Prairies

Alan Betts

### Abstract

Analysis of the 13 climate stations across the Canadian Prairies with hourly observations from 1953-2011 of temperature, RH, precipitation and snow depth has transformed our understanding of land-surface-climate coupling, because trained observers (following the same protocol for 60 years) recorded in addition hourly opaque/reflective cloud cover in tenths (defined as cloud that obscured the sun moon or stars). These data can be calibrated on daily timescales against radiation measurements to give SWCF and LWCF. We find that cloud forcing of the diurnal climate has distinct warm and cold season behavior. From April to October, when incoming shortwave radiation dominates over longwave cooling, maximum temperature and the diurnal ranges of temperature and relative humidity increase with decreasing opaque cloud cover, while minimum temperature is almost independent of cloud. Anomalies of precipitation and cloud explain 70-80% of the variance of monthly mean temperature and RH in the warm season. A large land-use change from summerfallow to continuous cropping in recent decades has cooled and moistened the summer climate. During the winter period, both maximum and minimum temperature fall with decreasing cloud, as longwave cooling dominates over the net shortwave flux. With lying snow, 2-m temperature drops 10oC. On regional scales 10% fewer days with snow cover gives a winter climate warming of 1.4oC. Snow cover acts as a climate switch: the transition from the warm season unstable BL to the cold season stable BL occurs within 5 days. Papers are available at http://alanbetts.com

4 September 10.30

LT

Gravity waves and water vapor in the stratosphere as deduced from observations and ECMWF data

Peter Preusse & Paul Konopka, Forschungszentrum Juelich, Germany

### Abstract

Data of the global assimilation system of ECMWF resolve mesoscale dynamical process in the stratosphere such as gravity waves and transport processes. In a two-part presentation we will give examples for utilizing ECMWF data for stratospheric research.

A) Gravity waves (GWs) couple the different layers of the atmosphere by transporting momentum when propagating from lower to higher altitudes. Usually, general circulation models are too coarse to resolve GWs and therefore need to take into account their effects by submodels called GW parametrisation schemes. The ECMWF model is of
sufficient spatial resolution to resolve a larger part of the GW spectrum. Still a GW parametrisation is required. In the talk we will present how observations can be utilised to guide the parametrisation. In addition, we will discuss the properties of GWs resolved in ECMWF and assess the resolved waves by comparison with observations.

B) Based on multi-annual simulations with the Chemical Lagrangian Model of the Stratosphere (CLaMS), driven by ECMWF ERA-Interim reanalysis winds and diabatic heating rates, we discuss the seasonality of the water vapor distribution in the stratosphere. For model validation,
both in-situ and satellite observations of the last 10 years are used. Finally, the differences between the water vapor distribution provided by the ERA-Interim reanalysis and CLaMS simulations will be discussed.

12 September 14:00

LT

Challenges in atmospheric modeling in coming 10 years : A subjective point of views

Dr Song-You Hong Korea Institute of Atmospheric Prediction Systems (KIAPS), Korea

### Abstract

In this talk, we provide a subjective view on the development of model dynamics and physics in coming 10 years. As computer architecture evolves to a multi-node hardware, many centers have given efforts on the development of grid-point dynamical cores, whereas some centers retain the fundaments in traditional spectral dynamical cores (e.g., IFS, GRIMs). For the global NWP community, the horizontal resolution range from 10 km to 1 km in coming 10 years, which is regarded to be a gray zone for parameterized precipitating convection, whereas in the regional NWP, turbulence parameterization falls into another gray zone with the grid spacing from 1 km to 100 m. We will present our efforts to resolve the above issues using the GRIMs and WRF, together with the introduction of the development strategy of the KIAPS global NWP system, which is scheduled to be operational at KMA in 2020.

18 September 15:30

LT

Dynamics of Rossby wave trains in a quantitative PV-Θ framework

Franziska Gierth, University of Mainz, Germany

### Abstract

This will include an assessment of the impact of different physical processes (within the IFS) on Potential Vorticity. It provides a means of bridging the gap between physics and dynamics, allowing us address questions such as "what physics is key for medium-range predictability?", etc

30 September 10:30

MR1

Producing and transferring knowledge on climate change in Sweden: Experiences from the work with CORDEX at SMHI

Erik Kjellstrom, Rossby Centre, SMHI, Sweden

15 October 10:30

MR1

Bias correction and downscaling in climate predictions and projections

Jose Manuel Gutierrez, University of Cantabria, Santander/Spain and Oxford University, UK

### Abstract

Bias correction and downscaling techniques are nowadays widely applied to calibrate/transfer the coarse output of global models to the local scale required in impact studies –as characterized by local or gridded observation datasets.- Most of these techniques have been developed in the framework of climate change studies, working with multi-decadal projections of global circulation models. However, much less work has been done in the framework of climate predictions, where the initialization (lead time) plays a key role as an additional dimension in the analysis. In this case, the systematic drift (bias dependence on the forecast lead-time) present in state-of-the-art seasonal forecasting models poses new problems and challenges for bias correction and downscaling. In this talk we will focus on this problem. First, a statistical assessment of the drift of a state-of-the-art seasonal forecasting model will be presented, based on the full thirty-year (1981-2010) System4 hindcast consisting of 15 members running each month for 7 months. Results show important drifts even at long lead times (6 months) far away from the shock in the initial conditions. Moreover, the differences between members are statistically not significant in general, what suggests that only a few members may suffice to robustly remove the drift for bias correction and downscaling applications. The implications for bias correction and downscaling will be discussed and some ongoing activities in the framework of the SPECS and EUPORIAS EU-funded projects will be presented.

17 October 10:30

LT

Arctic sea ice - observations, reanalyses, predictions

Steffen Tietsche, Arctic group at Reading University, and ECMWF visiting scientist

### Abstract

Sea ice is a key component of Arctic weather and climate because it regulates the exchange of heat and momentum between ocean and atmosphere. However, observing and modelling sea ice well enough to provide reliable predictions is still a major challenge. I will introduce this talk with a review of demonstrated and suspected impacts of sea ice variations on large-scale atmospheric circulation, followed by an overview of recent and upcoming capacity for satellite-based sea ice observations. Efforts to assimilate these observations into numerical weather and climate models have been started in the last years. At ECMWF, the ocean reanalysis ORAP5 for the first time assimilates sea ice concentration. I will discuss the state of Arctic sea ice in ORAP5 with a focus on the last twenty years. ORAP5 compares favorably with available observations and other model reconstructions of Arctic sea ice. However, some aspects of simulating sea ice thickness remain uncertain. I will conclude the talk by pointing out that Arctic sea ice is potentially predictable on much longer time scales than the atmosphere, and that exploiting this predictability should help to improve weather and climate forecasts.

21 October 10:30

LT

Ongoing activities on the use of observations in the Météo-France NWP models

Jean-Francois Mahfouf, Météo France, France

### Abstract

In this presentation an overview will be provided on recent activities undertaken at Météo-France towards an increased usage of observations in the data assimilation systems for both the global model ARPEGE and the meso-scale model AROME. This will concern both short term activities leading to operational changes and longer term research linked to various challenges and to the preparation of future observing systems

23 October 11:00

LT

Towards an improved 20th Century reanalysis version “2c” dataset spanning 1851 to 2013

Gilbert P Compo1,2 (1)University of Colorado at Boulder, CIRES, Boulder, CO, United States, (2)NOAA Earth System Research Laboratory, Physical Sciences Division, Boulder, CO, United States

### Abstract

The historical reanalysis dataset generated by NOAA Earth System Research Laboratory and the University of Colorado CIRES, the Twentieth Century Reanalysis version 2 (20CRv2), is a comprehensive global atmospheric circulation dataset spanning 1871-2012, assimilating only surface pressure and using monthly Hadley Centre SST and sea ice distributions (HadISST1.1) as boundary conditions.  It has been made possible through collaboration with GCOS, WCRP, and the ACRE initiative. It is chiefly motivated by a need to provide an observational validation dataset, with quantified uncertainties, for assessments of climate model simulations of the 20th century, with emphasis on the statistics of daily weather. It uses, together with an NCEP global numerical weather prediction (NWP) land/atmosphere model to provide background "first guess" fields, an Ensemble Kalman Filter (EnKF) data assimilation method. This yields a global analysis every 6 hours as the most likely state of the atmosphere, and also yields the uncertainty of that analysis.

The 20CRv2 is being used in a variety of climate and weather studies. As an example, we investigate whether the Pacific Walker Circulation (PWC) has weakened or strengthened since 1900. Some researchers have suggested that observations of the PWC spanning the last century provide evidence that the global convective mass flux is decreasing. Global coupled climate models show a decrease in the PWC from the last century extending into the next. The debate surrounding this issue is complicated by different investigators using different indices to define the PWC, with some based on using both the rotational and divergent components of the tropical winds to diagnose what is in essence a divergent overturning circulation. The influence and effect of tropical sea surface temperatures (SST) is also a confounding issue. We find that, in contrast to coupled climate models, most observed aspects of the PWC show no trend or a strengthening over the last 120 years.

While 20CRv2 is useful, there are opportunities for improvement. A new version (“2c”) currently being generated includes an extension back to 1851 and the specification of new boundary conditions. These come from new fields of monthly COBE-SST2 sea ice concentrations and an ensemble of daily Simple Ocean Data Assimilation with Sparse Input (SODAsi.2c) sea surface temperatures.  SODAsi.2c itself was forced with 20CR, allowing these boundary conditions to be more consistent with the atmospheric reanalysis. Millions of additional pressure observations contained in the new International Surface Pressure Databank version 3 are also included. These improvements result in 20CR version “2c” having comparable or better analyses, as suggested by improved 24 hour forecast skill, more realistic uncertainty in near-surface air temperature, and a reduction in spurious centennial trends in the tropical and polar regions.

24 October 11:00

MR1

OLYMPEX: A Field Campaign in Complex Terrain for Validation of Precipitation Measurements by the NASA Global Precipitation Measurement (GPM) Satellites

Dr. Lynn McMurdie, Department of Atmospheric Sciences, University of Washington

### Abstract

At 18:37 UTC 27 February 2014, the core satellite of the Global Precipitation Measurement (GPM) mission was successfully launched from the Japanese Space Agency (JAXA) Space Center on Tanegashima Island, Japan. Aboard the satellite is the first space-borne Ku/Ka band Dual Frequency Precipitation Radar (DPR) and the GPM passive Microwave Imager (GMI), with channels ranging from 10-183 GHz. The primary objective of the Core satellite is to measure rain and snow globally, determine its 3D structure, and act as the calibration satellite for a constellation of GPM passive microwave satellites in a wide range of precipitation intensities, geographical locations and weather regimes. In order to identify and understand uncertainties in the GPM measurements and to assess how remotely sensed precipitation can be applied to a range of applications (e.g. determining storm structures and monitoring runoff and flooding events, and as input to numerical models), ground validation (GV) field campaigns are crucial.  As such, the Olympic Mountains GV Experiment (OLYMPEX) is planned for November 2015 – February 2016.

The Olympic Peninsula in the northwest corner of Washington State is an ideal location to conduct a GV campaign.  It is situated within an active mid-latitude winter storm track and receives among the highest annual precipitation amounts in North America, ranging from over 2500 mm on the coast to 4000 mm in the mountainous interior. In one compact area, the Olympic peninsula ranges from ocean to coast to land to mountains. It contains a permanent snowfield and numerous associated river basins. This unique venue will enable the field campaign to monitor both upstream precipitation characteristics and processes over the ocean and their modification over complex terrain.

The scientific goals of the OLYMPEX field campaign include physical validation of satellite algorithms, precipitation mechanisms in complex terrain, hydrological applications, and modeling studies. In order to address these goals, a wide variety of existing and new observations and instrumentation are planned. These include in situ surface observing networks of meteorological stations, rain and snow gauges, surface microphysical measurements, and snowpack surveys. Surface-based remote sensing instrumentation will include the existing and planned radars such as the NASA N-Pol S-Band dual-polarimetric and NASA Dual-Frequency Dual-Polarimetric Doppler (D3R) scanning radars and other mobile vertically-pointing radars. Several instrumented aircraft are likely to participate. The NASA DC-8 will be equipped with a Ka/Ku band dual-frequency radar and passive microwave sensors that simulate those on the GPM Core satellite. The University of North Dakota Citation will measure in situ microphysics.  The aircraft measurements will determine upstream thermodynamic and moisture conditions, sample particle types and sizes for comparison with those employed in the satellite algorithm, and act as a proxy for the satellite itself. The ground-based measurements will test how well the satellite proxy measurements determine the rain and snow over complex terrain.

31 October 14:00

WR

Early warning early action: using global weather forecast data trigger humanitarian interventions

Erin Coughlan, Red Cross Red Crescent Climate Centre, USA

### Abstract

There are many short-term actions, such as evacuation, that can be implemented in the period of time between a warning and a potential disaster to reduce likely impacts. However, this precious window of opportunity is regularly overlooked in the case of climate and weather forecasts, which are rarely used to initiate preventative action even though they can provide timely indications of heightened risk. At the Red Cross Red Crescent Climate Centre, we are developing methodologies to use globally-available weather and climate forecasts as an indicator for heightened disaster risk in data-scarce locations. Forecast thresholds are identified that correspond to significantly increased risk of disaster, and appropriate actions are paired with the selected forecasts to reduce impacts in the at-risk communities. We are piloting a novel forecast-based financing system that disburses required funding when these thresholds are reached, allowing humanitarian actors to systematically take action as soon as a relevant forecast is issued.  In this seminar, I will discuss the methodologies we are piloting to estimate forecast-based risk, and provide an overview of considerations when establishing a novel forecast-based financing system. Comments and ideas from all will be encouraged on this new approach.

10 November 14:00

Classroom

Characterization of SSM/T-2 radiances using ERA-Interim and other reanalyses

Shinya Kobayashi, CM-SAF Visiting Scientist from Japan Meteorological Agency (JMA)

### Abstract

The Special Sensor Microwave Water Vapor Profiler SSM/T-2 instrument is a five-channel passive microwave sensor in the 90-190 GHz frequency band. It is the first operational microwave humidity sounder, flown on 4 Defense Meteorological Satellite Program (DMSP) satellites (DMSP 11, 12, 14 and 15), between 1992 and the late 2000s. This instrument predates the microwave water vapor sounding capabilities offered by AMSU-B, MHS, and now ATMS. The SSM/T-2 data record is hence important for climate and reanalysis applications, because it could allow to extend back to 1992 the microwave data record for water vapor profiling, which currently only starts with AMSU-B in the late 1990s.

The CM-SAF has commissioned a study to assess a reprocessed SSM/T-2 dataset, delivered by the ERA-CLIM project. Fast radiative transfer computations are carried out from a variety of reanalyses at the time and location of the observations. The observational dataset is then
augmented by so-called added feedback information: departures between the observations with the simulated brightness temperatures.

This talk will present findings from this study. We will illustrate for example how, years after the fact, we can now conclude with near certainty on some aspects of the instrument design, actually not known for sure at the time, such as instrument polarization. The time consistency of the observations, assessed against reanalyses, will also
be shown to be superior in ERA-20C than in ERA-Interim. Other interesting features will be shown, confirming for example the moist (dry) bias of ERA-Interim (respectively: ERA-20C and JRA-55).

11 November 14:00

WR

Solving partial differential equations using the finite element method efficiently and productively with Firedrake and PyOP2

Florian Rathgeber (ECMWF)

### Abstract

In this talk I will give an overview of my PhD research in computational science at Imperial College London before joining ECMWF, which involved designing and implementing a two-layer domain-specific framework for the efficient solution of partial differential equations from a high-level problem specification. I will present Firedrake, a high-level framework for solving partial differential equations using the finite element method, built on top of PyOP2, a domain-specific language embedded in Python for parallel mesh-based computations. I am going to highlight characteristic features that differentiate this tool chain from existing solutions, reflect on the process of designing and implementing the framework and discuss some lessons learnt in running an academic open source software project.

Firedrake allows scientists to describe variational forms and discretisations for linear and non-linear finite element problems symbolically, in a notation very close to their mathematical models. PyOP2 abstracts the performance-portable parallel execution of local computations over the mesh on a range of hardware architectures, targeting multi-core CPUs, GPUs and accelerators. Thereby, a separation of concerns is achieved, in which Firedrake encapsulates domain knowledge about the finite element method separately from its efficient parallel execution in PyOP2, which in turn is completely agnostic to the higher abstraction layer.

As a consequence of the composability of those abstractions, optimised implementations for different hardware architectures can be automatically generated without any changes to a single high-level source. Performance matches or exceeds what is realistically attainable by hand-written code. Firedrake and PyOP2 are combined to form a tool chain that is demonstrated to be competitive with or faster than available alternatives on a wide range of different finite element problems.

17 November 10:30

LT

Using remote-sensed surface temperature to assess surface heat fluxes over Antarctica

Eric Brun, Météo-France (CNRM/GMGEC/ASTER), France

### Abstract

Snow cover is a key component of the climate system. Its presence on the ground drastically changes the physical properties of the continental surfaces and thus strongly impacts the energy exchanges between the surface and the atmospheric boundary layer. The most important features of snow cover with respect to weather prediction will be presented in details. Its radiative and thermal properties, including its capacity, its conductivity and its melting latent heat, lead to an efficient cooling of the snow surface and to a stabilization of the atmospheric boundary layer.

Numerical snow models are quite efficient tools to simulate snow cover evolution, though they might suffer from the difficulty to derive turbulent heat fluxes under very stable conditions. A new method will be presented to assess turbulent heat fluxes under very stable conditions. It is based on the use of remote-sensed surface temperature from MODIS over Antarctica. Taking advantage of the long polar night during which short-wave radiation is negligible, the method reveals an overestimation of sensible turbulent heat fluxes in IFS under very stable conditions, leading to a widespread warm bias in ERA-interim at the surface of Antarctica.

18 November 10.30

LT

Normal-mode function representation of the global 3D circulation

Nedjeljka Zagar, University of Ljubljana, Slovenia

### Abstract

The goal of the seminar is to present the open-access software MODES, which is now available to atmospheric research community for the analysis of global NWP and climate models, and the software application to the ECMWF reanalysis and ensemble datasets.

The software, developed within the ERC MODES project, allows one to diagnose properties of balanced and inertio-gravity circulation across many scales. In particular, the IG spectrum, which has only recently become observable in global datasets, can be studied simultaneously in the mass field and wind field and considering the whole model depth. The presentation will include theoretical background and basic technical details of the software that been installed and running on both ecgate and c2a computers at ECMWF. Results from the ERA Interim analysis in terms of the normal-mode function (NMF) representation will be presented. In addition, outputs from the NMF analysis of the EPS system operational in 2013 will be discussed in relation to the previously derived properties of time-averaged and time-dependent forecast errors derived from the EDA system.

19 November 10:30

MR1

Improving the Madden-Julian oscillation in the Met Office model: The roles of air-sea coupling and convective entrainment

Dr Nicholas Klingaman, Department of Meteorology, University of Reading

### Abstract

The Madden-Julian oscillation (MJO) is the leading mode of sub-seasonal variability in tropical convection and provides a key source of weekly and monthly predictability globally. In a multi-decadal atmosphere-only simulation, the Met Office Unified Model (MetUM GA3.0) produces roughly one-half the observed level of MJO activity, with events often living for fewer than five days.

We conduct a series of initialised, climate-resolution hindcasts of observed MJO events to test a range of parameterisation and model-configuration changes in MetUM GA3.0. Increasing the rate of entrainment and detrainment in the convective parameterisation is the only change that consistently improves the MJO across the hindcast set. With higher entrainment, MetUM GA3.0 produces near-observed levels of MJO variability. Having improved the MJO in the atmosphere-only model, we investigate the roles of air-sea interaction in the MJO at low and high entrainment rates by coupling to a mixed-layer ocean. At lower rates, with poor atmospheric variability, coupling primarily improves the amplitude of the MJO in the model. At higher rates, when the atmosphere has a reasonable MJO, coupling primarily improves MJO propagation without affecting the amplitude. The seminar will conclude with some comments on how coupled-model SST biases affect not only the representation of the MJO, but also the perceived impact of air-sea coupling.

28 November 10:30

MR1

Does the ECMWF IFS convection parametrization with stochastic physics correctly reproduce relationships between convection and the large-scale state?

Peter Watson, University of Oxford

### Abstract

Important questions concerning parametrization of tropical convection are how should sub-grid scale variability be represented, and which large-scale variables should be used in the parametrizations? Here we compare the statistics of observational data in Darwin, Australia with those of short-term forecasts of convection made by the European Centre for Medium-Range Weather Forecasts Integrated Forecast System. The forecasts use multiplicative-noise stochastic physics that has led to many improvements in weather forecast skill. However, doubts have recently been raised about whether this representation of sub-grid scale variability is consistent with observations of tropical convection. We show that the model can reproduce the variability of convection intensity for a given large-scale state, both with and without stochastic physics. Therefore this representation of sub-grid scale variability is not inconsistent with observations, and much of the modelled variability arises from non-linearity of the deterministic part of the convection scheme. We also show that the model can reproduce the lack of correlation between convection intensity and large-scale CAPE and an entraining CAPE, even though the convection parameterisation assumes that deep convection is more intense when the vertical temperature profile is more unstable, with entrainment taken into account. Relationships between convection and large-scale convective inhibition and vertical velocity are also correctly captured.

05 December 10:30

LT

Greater Accuracy with Less Precision: A New Direction for Weather and Climate Prediction?

Prof T N Palmer, University of Oxford

### Abstract

Weather and climate models are becoming increasingly important tools for making society more resilient to extremes of weather and for helping society plan for possible changes in future climate. These models are based on known laws of physics, but, because of computing constraints, are solved over a considerably reduced range of scales than are described in the mathematical expression of these laws. This generically leads to systematic errors when models are compared with observations, errors which are often as large as the signals we are trying to predict. A new paradigm is proposed for solving these equations which sacrifices precision and determinism as an inverse function of (space-time) scale. It is suggested that this sacrifice may allow the truncation scale of global weather and climate models to extend down to cloud scales in the coming years, leading to more accurate predictions of future weather and climate. The paradigm may help alleviate the twin challenges of scalability and energy efficiency, as computers become more and more parallel and more and more energy intensive.

11 December 14:00

MR1

Differences between land models and their role in
meteorological forecasting

René Orth, ETH Zürich, Switzerland

### Abstract

Land hydrology is an important factor for weather and climate forecasting. This is mainly due to the role of soil moisture in the climate system and because of its memory characteristics. Especially through its impacts on the evapotranspiration of soils and plants, it may influence the land energy and water balance and therefore surface temperature and/or precipitation. Moreover, land surface hydrology in general can play a crucial role during extreme events such as droughts, floods and even heat waves. To assess and understand differences between land models we compare a benchmark dataset derived from a simple water balance model (SWBM) with the ERA-Land dataset and simulations from the Community Land Model Version 4 (CLM4). We validate all three against several independent reference datasets representing soil moisture (or terrestrial water content), evapotranspiration and streamflow. We find clear performance differences across the models. The SWBM performs surprisingly well in terms of soil moisture and runoff. Only in the case of evapotranspiration it is outperformed by the more sophisticated models. To understand these results we compare the role of the forcing used by the land models with the impact of their parameters, and find similar importance for the simulated hydrology.

These findings are relevant for a range of applications, including weather and climate forecasting. To illustrate this we run the SWBM with forecasted atmospheric forcing from the ECMWF VarEPS re-forecasts to derive soil moisture forecasts across Europe. These are then translated into temperature forecasts using simple linear relationships. The resulting temperature forecasts show skill beyond climatology up to 2 weeks in most of the considered areas. Even if forecasting skills are rather small at longer lead times with significant skill only in some regions at lead times of 3 and 4 weeks, this soil moisture-based approach shows local improvements compared to the monthly ECMWF temperature forecasts at these lead times. Even though a product based on soil moisture information alone is not of practical relevance, our results indicate that soil moisture (memory) is a potentially valuable contributor to temperature forecast skill.

12 December 10.30

LT

Convection-humidity feedbacks and tropical predictability in near-global cloud-resolving simulations

Chris Bretherton, Atmospheric Sciences & Applied Mathematics, University of Washington, USA

### Abstract

Zonally-symmetric aquaplanet simulations with a cloud-resolving model with 4 km resolution extending across a tropical channel from 45S-45N with 20000 km zonal extent are forced by realistic meridional SST gradients.  They are used to study feedbacks between humidity and convection, and also the potential predictability of tropical circulations.  These simulations encompass a wide range of scales while not introducing the uncertainties inherent in cumulus parameterization. Advective stirring in these near-global runs is found to greatly limit the effectiveness of mechanisms of convective self-aggregation in organizing large-scale tropical circulations, compared to results from limited-area cloud-resolving simulations.

## 2013

23 January 10:30

CR

Getting IFS to run on a future Exascale supercomputer

George Mozdzynski, ECMWF

### Abstract

Today we run our 16 km global T1279 deterministic forecast model using just 1,536 cores of an IBM Power7. Following the historical evolution in resolution upgrades, we could expect to be running a 2.5 km global forecast model by about 2030 on an Exascale system that should be available and hopefully affordable by then. To achieve this would require IFS to run efficiently on about 1000 times the number of cores it uses today. This is a significant challenge, one that is being addressed within the CRESTA
1 project. After implementing an initial set of improvements we have now demonstrated IFS running a 10 km global model on over 50,000 cores of HECToR, a Cray XE6 at EPCC, Edinburgh. Of course, getting to over a million cores remains a formidable challenge, and many scalability improvements have yet to be implemented.

Within CRESTA, we are exploring the use of Fortran2008 coarrays; in particular it is possibly the first time that coarrays have been used in a world leading production application within the context of OpenMP parallel regions. The purpose of these optimisations is primarily to allow the overlap of computation and communication, and further, in the semi-Lagrangian advection scheme, to reduce the volume of data communicated. The importance of this research is such that if these developments are successful then the IFS model may continue to use the spectral method to 2030 and beyond on an Exascale sized system.

12 February 15:30

LT

Optimising the number of GNSS Radio Occultation measurements for Numerical Weather Prediction

Florian Harnisch, Hans-Ertel Centre for Weather Research, University Munich

14 February 10:30

LT

The role of simpler models in seasonal forecasting and GCM studies

Prof Brian Hoskins, Imperial College

### Abstract

The proposition will be made that a range of models should be used for diagnosis of real atmospheric behaviour to help in the generation of hypotheses to be tested in GCMs, and in the diagnosis of AGCM biases and results. Support for this view will be provided by discussion of a number of different uses of the Reading spectral baroclinic model applied to understanding of anomalies in the summer of 2007.

25 February 15:30

LT

Is global warming significantly affecting atmospheric circulation extremes?

Prashant Sardeshmukh, Univ of Colorado and NOAA, Boulder, CO

### Abstract

Although the anthropogenic influence on 20th century global warming is well established, the influence on the atmospheric circulation, especially on regional scales at which natural variability is relatively large, has proved harder to ascertain. And yet assertions are often made to this effect, especially in the media whenever an extreme warm or cold or dry or wet spell occurs and is tied to an apparent trend in the large-scale atmospheric circulation pattern.

We are addressing this important issue using the longest global atmospheric circulation dataset currently available, an ensemble of 56 equally likely estimates of the atmospheric state within observational error bounds generated for every 6 hours from 1871 to the present in the 20th Century Reanalysis Project (20CR; Compo et al, QJRMS 2011). We previously presented evidence that long-term trends in the indices of several major modes of atmospheric circulation variability, including the North Atlantic Oscillation (NAO) and the tropical Pacific Walker Circulation (PWC), were weak or non-existent over the full period of record in the 20CR dataset.

We have since investigated the possibility of a change in the probability density functions (PDFs) of the daily values of these indices, including changes in their tails, from the first to the second halves of the 20th century and found no statistically significant change. This was done taking into account the generally skewed and heavy-tailed character of these PDFs, and using both raw histograms and fitted “SGS probability distributions” (whose relevance in describing large-scale atmospheric variability was demonstrated in Sardeshmukh and Sura, J. Climate 2009) to assess the significance of any changes through extensive Monte Carlo simulations. We stress that without such an explicit accounting of departures from normal distributions, detection and attribution studies of changes in climate extremes may be seriously compromised and lead to wrong conclusions.

Our finding of no significant change in the PDFs of the NAO and the PWC has important implications for how global warming is influencing atmospheric circulation variability and extreme
anomaly statistics, and to what extent the latest generation of CMIP5 climate models are correctly representing those influences.

18 March 14:00

MR1

Approach for Diagnostics and Evaluation of Cycling Model Error in Weak-Constraint 4D-Var

Takuya Komori, ECMWF

### Abstract

The extension from Strong-Constraint to Weak-Constraint 4D-Var constitutes a novel approach for using multi-variate observational resources and constraints to identify and characterize systematic model errors.

Based on data assimilation experiments with cycling of model error including Sudden Stratospheric Warming periods, I will discuss some examples of its strengths and weaknesses for representing systematic model errors in the stratosphere, in the context of global medium-range NWP (full observing system assimilation), and also in the related but distinct context of reanalysis (surface pressure only assimilation).

20 March 10:30

LT

Factors influencing skill improvements in the ECMWF forecasting system

Linus Magnusson and Erland Källén, ECMWF

### Abstract

During the past 30 years the skill in ECMWF numerical forecasts has steadily improved. Three major factors contributing are (1) improvements in the forecast model, (2) improvements in the data assimilation and (3) the increased number of available observations. In this study we are investigating the relative contribution from these three components by using the simple error growth model introduced in Lorenz (1982) and extended in Dalcher and Kalnay (1987), together with the results from ERA Interim forecasts where the improvement is only due to an increased number of observations. We are also applying the growth model to ”lagged”-forecast differences in order to investigate the usefulness of the forecast jumpiness as a diagnostic tool for judging improvements in the forecasting system. Our main finding is that the main contribution to the reduction in forecast error is the improvement in initial conditions between 1995 and 2002 together with continuous model improvements. The changes in the available observations contributed to a lesser degree, but we have to remember that the all the ERA Interim forecasts are from the satellite era and that we here focus on the mid troposphere in the extra-tropics. Regarding the jumpiness in the forecasts, this is mainly a function of the error in the initial conditions and is therefore an insufficient tool to investigate improvements in the full forecasting system.

25 March 14:00

LT

Tropical-extratropical interactions of intraseasonal oscillations and equatorial waves

Jorgen Frederiksen, CSIRO Marine and Atmospheric Research, Aspendale, Australia

### Abstract

Tropical-extratropical interactions of northern winter intraseasonal oscillations based on observations and theory are compared. The phase relationships between the tropical signal of the intraseasonal oscillations and the development of PNA-like and AO/NAO teleconnection patterns are determined and compared for eight phases in the cycle of intraseasonal variability. The observational study uses data from 30 northern winters while the theoretical intraseasonal oscillation, with a period of 34.4 days, is obtained from a primitive equation model incorporating closures of Kuo cumulus convection and evaporation-wind feedback and the three-dimensional global flow for January 1979 as basic state. The observed convection of the Madden-Julian oscillation (MJO), quantified by negative OLR, positive precipitation and negative upper troposphere velocity potential anomalies, is focused over the central Indian Ocean at PHASE 3; this is also the case for the upper troposphere velocity potential for the theoretical mode. At that time and up to 4-5 days later (PHASE 4), the upper troposphere streamfunctions, from observations and theory, show wavetrains corresponding to the negative phase of an intraseasonal PNA-like pattern. Subsequently, around 8-10 days later (PHASE 5), both the theoretical mode and observational anomalies exhibit the negative sign of a NAO teleconnection pattern, with large negative anomalies over Greenland. Throughout its evolution the theoretical mode captures the essentials of the complex tropical-extratropical intraseasonal variability associated with the MJO. The fluxes of wave-activity, based on the upper troposphere streamfunction of the theoretical mode, indicate strong tropical-extratropical interactions, and have very similar structures to those obtained by Lin et al. (2009) based on observations of extratropical anomalies associated with MJO convection.

The properties of intraseasonal oscillations are contrasted with those of convectively coupled equatorial waves and the sensitivity of the theoretical intraseasonal oscillations to different basic states is analysed.

9 April 10:30

LT

WIVERN : A WInd VElocity Radar Nephoscope, a satellite for the global measurement of winds and precipitation or a figment of the imagination?

Anthony Illingworth, Dept of Meteorology, Univ of Reading

A proposed satellite to provide global profiles of winds, clouds  and precipitation with 50km horizontal and  1km vertical resolution and daily visits poleward of 50 degrees.

19 April 15:30

MR1

The Global Footprint of Drought and the Monitoring of it

W Pozzi, Group on Earth Observations Hydrometeorological Extremes PoC

### Abstract

That the monitoring technology must match the space and time scales of the phenomenon being observed is a truism in physics. As early as the late 1990s, Byun and Wilhite (1999) made the observation, that part of the difficulty of drought indices, including Standardized Precipitation Index (SPI), was its failure to take into account aggravating effects of evapotranspiration and runoff, compounded by its limited usefulness in monitoring ongoing drought, since the real-time precipitation data were entirely limited to monthly time steps. Twenty years later, this conclusion has been re-iterated again with respect to the Horn of Africa drought: ” At the same time, adequate emergency intervention is also limited by inadequate access to reliable, spatially distributed drought monitoring information available in near real-time.(Anderson et al 2012)” Benjamin Lloyd-Hughes has made a laudable effort developing the first methodology, publicly available, to monitor drought globally, using a uniform data source, the Global Precipitation Climatology Centre (GPCC) global precipitation data; however, this data source, as before, is limited to a monthly time step.

Mark Svoboda of the USA Drought Monitor coined the term “flash drought,” in analogy to flash flood, to describe events observed in August-September 2000, when intense heat waves, accompanied by windy conditions, resulted in high evapotranspiration rates, draining off soil moisture, worsening drought over very short time scales (and increasing the risk of wildfires)--analogous to conditions experienced over the Russian Federation in 2010. Such “flash droughts” do not correspond to the classical, “slow onset” stereotype of droughts, and they require a rapid response monitor for their identification.

Besides the need to providing rapid response, drought monitoring technologies capable of monitoring over short time scales, there is a need to monitor drought over very large spatial scales. Results from dendrochronology studies suggest that drought conditions prior to the instrumental era may have been more extreme, both as “megadroughts,” extending over more than a decade, and “superdroughts,” extending over an entire continental domain, in analogy to a “superstorm” which extends over an entire continental or oceanic domain.

Besides SPI, several new remote sensing-based drought monitoring technologies are being rolled out through the USA National Integrated Drought Information System (NIDIS), the North America Drought Briefing, and the USA Drought Monitor. Each of these technologies can also be extended to the global domain, and these new technologies operate at weekly time steps. NOAA NESDIS uses Vegetation Health Index (VHI) combines Vegetative Index (such as NDVI) with temperature inferred from an instantaneous satellite overpass, and has been extended from vegetation health to a drought measure. The VHI technique may possibly give spurious results in cold regions, such as northern Eurasia or Canada.

Two additional candidate global drought measures are based upon evapotranspiration; both of these latter methodologies employ reanalysis fields to monitor meteorological conditions (winds, etc) to accompany the radiation measurements taken from satellites, combined with vegetation stand density from MODIS (to separate soil and vegetation cover within a pixel). One of these methodologies uses instantaneous land surface temperature (from MODIS), while the other attempts to increase the accuracy of surface temperature measurement by using geostationary satellite coverage for taking at least two temperature observations during the morning temperature rise. There is now the capability to monitor, to some extent, groundwater, soil moisture, and snow pack (water storage), along with precipitation inputs (water supply) to begin providing global coverage of the water cycle (and the propagation of drought within it).

Global patterns of drought are surveyed, along with the abilities of these drought indicators to monitor drought events on different time scales. The ability of these new remote sensing-based drought monitoring technologies to provide reliable monitoring in African and Central Asia areas of sparse ground-based precipitation coverage is the next question to be assessed. These steps will improve drought forecasting ability.

24 April 10:30

LT

Estimating Return Values From EPS Forecasts

Oyvind Breivik, Marine Aspects Section, ECMWF

### Abstract

A method for estimating return values from ensembles of forecasts at advanced lead times is presented.

Return values of significant wave height in the North-East Atlantic, the Norwegian Sea and the North Sea are computed from archived +240-h forecasts of the ECMWF ensemble prediction system (EPS) from 1999 to 2009.

We make three assumptions: First, each forecast is representative of a six-hour interval and collectively the data set is then comparable to a time period of 226 years. Second, the model climate matches the observed distribution, which we confirm by comparing with buoy data. Third, the ensemble members are sufficiently uncorrelated to be considered independent realizations of the model climate. We find anomaly correlations of 0.20, but peak events (>P97) are entirely uncorrelated. By comparing return values from individual members with return values of subsamples of the data set we also find that the estimates follow the same distribution and appear unaffected by correlations in the ensemble. The annual mean and variance over the 11-year archived period exhibit no significant departures from stationarity compared with a recent reforecast, i.e., there is no spurious trend due to model upgrades.

EPS yields significantly higher return values than ERA-40 and ERA-Interim and is in good agreement with the high-resolution hindcast NORA10, except in the lee of unresolved islands where EPS overestimates and in enclosed seas where it is biased low. Confidence intervals are half the width of those found for ERA-Interim due to the magnitude of the data set.

30 April 10:30

LT

Calibration of medium-range weather forecasts

Prof Tilmann Gneiting, Univ of Heidelberg

9 May 10:30

MR1

Precipitation and snowpack in Hindu-Kush Karakoram Himalaya: Current features and future projections

Silvia Terzago, SAC-Institute of Atmospheric Sciences and Climate, CNR, Torino, Italy

### Abstract

The Hindu-Kush Karakoram Himalaya (HKKH) is the largest mountain region in the world and feeds some of the major rivers in Southeast Asia supplying water to more than 1.5 billion people. Despite its importance, the current precipitation, the snowpack dynamics and their possible changes in the coming decades are still a major challenge due to difficult and sporadic surface observations in such remote areas.

In this work we analyze the precipitation and its mechanisms in the Hindu-Kush Karakoram Himalaya(HKKH) region using currently available data sets, including satellite estimates, reanalyses, gridded in situ rain gauge data, and we compare them to the simulations from the global climate model EC-Earth. The results are related to the characteristics of the snowpack investigated using the output of the global climate models and the ERA-Interim/Land reanalysis. Finally we explore the possible effects of climate change in the HKKH region by using the available future projections in different climate change scenarios.

14 May 15:30

LT

The Soil Moisture Active Passive (SMAP) Mission Application Program Pre Launch Efforts

Vanessa Escobar, NASA/GSFC

### Abstract

NASA’s Soil Moisture Active Passive (SMAP) mission is due to launch October of 2014. SMAP is a combined active/passive microwave instrument, which aims to produce a series of soil moisture products and soil freeze/thaw products with an accuracy of +/-10%, a nominal resolution between 3 and 40km, and latency between 12 hours and 7 days. These measurements will be used to enhance the understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. SMAP is NASA ’s first decadal survey mission to implement a rigorous applications program that seeks to integrate soil moisture derived data into decision making applications fields of weather, climate, drought, flood, fire and human health, prior to launch.

The focus of the SMAP Applications Program is to (1) improve the missions understanding of the SMAP user community requirements, (2) document accuracies and biases of remote sensing derived-soil moisture and communicate the perceived challenges and advantages to the mission scientists (3)facilitate the movement of science into policy and decision making arenas and 4) strive to provide a clear path to access proxy data (both in terms of accessibility and format). Since 2007, the SMAP Applications Program has provided new concepts, definitions and activities to promote SMAP applications. Executing this effort is the SMAP Applications Team, composed of key individuals from within the SMAP project, SMAP Science Definition Team (SDT), and NASA Headquarters.

The driving success of the SMAP applications program has been the joining of mission scientists to thematic end users and leveraging the knowledge base of soil moisture data applications, increasing the ingestion speed of future SMAP data product into critical processes and improving the societal benefits to science. Understanding how users will apply SMAP data, prior to the satellite’s launch, is an important component of SMAP Applied Sciences. Successfully achieving this requires bridging scientific research and thematic user communities’ operational decision making priorities and data requirements.

Through our pre launch applications work with the SMAP community and the SMAP Early Adopter program, we have learned that there are challenges the SMAP mission can address prior to launch, that will increase the applications and utility of post launch data. Because application requirements are different for each user, we focus on understanding the individual resolution, access and accuracy concerns of SMAP data by thematic discipline. This understanding in the pre launch stages of the mission’s development is an integral part of converting the data collected into actionable knowledge that can be used to inform policy and improve societal applications.

13 June 14:00

LT

Flow dependent predictability in the North Atlantic sector

John Methven, Department of Meteorology, University of Reading

### Abstract

The predictability of the atmosphere is believed to be flow-dependent in the sense that it is easier to make skillful predictions from some flow configurations than others. However, identifying the configurations with greater predictability and quantifying the enhanced skill in these situations is difficult. A key aspect in identification of flow-dependent predictability is that the definition of flow "configuration" must occur sufficiently frequently that statistics of ensemble forecast spread can be gathered. Two distinct phenomena in the extratropical atmosphere are discussed.

The first relates to the variability of the westerly jet across the Atlantic and medium-range ensemble predictions for the evolution of the jet. It is found that when the jet weakens or splits (in latitude) it enters into a state more sensitive to small differences between ensemble members and is therefore less predictable.

The second concerns the link between the predictability of "weather variables" (precipitation and surface winds) with the occurrence of mesoscale structures within extratropical storms. The predictive skill of mesoscale features, identified in ensemble forecasts using the Hewson method, is explored. Some illustrations are given of phenomena where the skill in finescale forecast variables is linked to the skill of the forecast for mesoscale features.

26 June 14:00

LT

DICast : The Dynamic Integrated Forecast System

Bill Myers, Global Weather Corporation & National Center for Atmospheric Research Boulder, Co

### Abstract

In the past 15 years, operational weather forecasting advancements in the post-processing of numerical weather models have significantly improved weather forecasts provided to the public and to industry. The development of consensus forecasting techniques has probably led to the largest reduction in forecast errors since the advent of Model Output Statistics (MOS) in the 1960s. DICast, developed in the late 1990s at NCAR, is a completely automated consensus forecast system that was modeled on the human forecast process. It considers multiple forecast inputs and continually compares its forecasts to observations in a machine learning approach that generates objective forecasts that outperform its ingredient forecasts, including NWS and ECMWF products, by 10-15%. DICast now drives the forecast engines of the largest weather forecast providers in the United States and, to an increasing degree, internationally.

27 June 10:00

MR-NB

The role of atmospheric rivers in British winter floods

David Lavers, University of Iowa

### Abstract

Damage from flooding in the winter and autumn seasons has been widespread in the United Kingdom and Western Europe over recent decades. In this seminar the connection between atmospheric rivers (ARs) and the largest winter floods in a range of British basins will be discussed from a hydrological and atmospheric stand-point. Firstly, an analysis of the hydrological time series is used to evaluate atmospheric fields before the largest floods to show the AR-flood link. Secondly, an algorithm is introduced that screens for ARs in climate model output; this is followed by showing the strong connection between the identified ARs and British winter floods. Future changes to ARs under climate change will also be considered.

David has a BSc (Meteorology) from the University of Reading UK, an MSc (Applied Meteorology) from the University of Birmingham UK and a PhD from the Centre of Ecology and Hydrology Wallingford / University of Birmingham UK. He has worked on seasonal climate prediction at Princeton University and has also been a weather forecaster in the Middle East. He recently completed a post-doctoral appointment at the University of Reading on using hydrologically-relevant processes for the assessment of climate model output. He is currently a post-doctoral researcher at the University of Iowa working in the broad area of hydrometeorology.

9 July 14:00

LT

Composition-climate interactions: What can we (already) learn from global models?

Prof Peter Braesicke, Karlsruhe Institute of Technology, Germany & University of Cambridge, UK

### Abstract

The talk will introduce the UMUKCA composition-climate modelling system, a joint Met Office/NCAS development. It will discuss the models performance and introduce some sensitivity studies that reveal composition-climate interactions. I will show that the climate system (as represented by the model) can respond quite sensitively to small chemical perturbations in ozone. I will argue that some modelled circulation adjustments in response to a chemical change can occur in reality and will illustrate this point using MIPAS data. I will finish with an outlook towards smaller scale features that are currently not represented in this climate model set-up, even though they are potentially important for composition-climate interactions. My example will be the Borneo vortex (BV), an important source of extreme weather for Malaysia, and a factor in creating a dry, ozone rich layer in the upper troposphere/lower stratosphere.

11 July 14:00

LT

Using Earth-system science at ECMWF

Erland Källén, Director of Research, ECMWF

### Abstract

In order to continue to deliver improved forecast performance the ECMWF forecast model and assimilation system will have to include additional parts of the Earth-system. Today we include the atmosphere, the land surface and, for extended range forecasts, also the ocean. A forecast system for atmospheric composition is under development and will be an integral part of the future ECMWF forecast system. Coupling to the ocean will be extended to start from day zero and the interaction between ocean waves, upper ocean mixing and sea-ice will be further developed. Reanalyses will also be extended to include additional parts of the Earth-system, both atmospheric composition, the land surface and the ocean will gradually be integrated to form a fully coupled reanalysis system. Some recent examples of progress in Earth-system modelling at ECMWF will be shown in order to demonstrate the capabilities and future potential of Earth-system modelling.

25 July 10:30

LT

Medium-range probabilistic verification and predictability of tropical cyclogenesis using the ECMWF EPS

Sharan Majumdar, Meteorology and Physical Oceanography (MPO) Rosenstiel School of Marine and Atmospheric Science (RSMAS), University of Miami

### Abstract

As part of the NSF PREDICT project, ensemble-based products have been developed with a goal to improve probabilistic predictions and our understanding of the predictability of tropical cyclogenesis. The probabilistic verification of quantities based on ECMWF ensemble forecasts out to 6 days will be presented for the 2010-12 Atlantic Hurricane seasons. Calibrated threshold values of metrics including a low-layer average circulation and a local thickness anomaly are used to determine the onset of cyclogenesis in each ensemble member. Reliability diagrams suggest a mostly increasing relationship between the predicted probability and frequency of actual genesis cases. However, there has been a tendency, particularly in 2012, for the ensemble to under-predict the development of the warm core. Some case illustrations will be presented. Finally, a series of metrics to investigate the predictability of fields associated with genesis such as wind shear and circulation will be introduced.

27 August 10:30

MR1

### Abstract

The Madden-Julian oscillation (MJO) is the dominant mode of variability in the tropics on the intraseasonal time scale (say, 20-90 day periods) and one of the most important coherent, quasi-periodic modes of natural variability in the global climate system altogether. Though it was discovered over 40 years ago, we still do not understand the MJO, in the sense of being able to state a simple mathematical model that explains its basic features.

I will present evidence that the MJO is what some of us now call a "moisture mode", best analyzed by examining the budget of moist static energy or moist entropy. I will argue that cloud-radiative feedbacks are important to the maintenance of the MJO, while horizontal advection of moisture is important to its eastward propagation. I will present evidence from observations, theory, general circulation models, and cloud-resolving models to this effect.

6 September 15:30

MR1

Statistical prediction of Atlantic basin hurricane activity

Dr Phil Klotzbach, Colorado State University

### Abstract

This presentation will begin by examining multi-decadal variability in the Atlantic basin, which provides the background physics for the development of statistical modeling of Atlantic basin hurricane activity. The statistical models currently used by Colorado State University to forecast Atlantic basin tropical cyclone activity will be discussed in detail. Hindcast skill of these models as well as real-time forecast skill since 1984 will be presented. The outlook for the 2013 Atlantic hurricane season along with an update on the 2013 hurricane season to date will be included. Lastly, the methodology behind CSU's two-week forecasts, based upon model guidance as well as the Madden-Julian Oscillation, will be discussed.

16 October 14:00

LT

Total energy norm of forecast error in model optimization

Heikki Järvinen, Univ Helsinki

### Abstract

This is a joint work with Peter Bauer, Peter Bechtold, Pirkka Ollinaho and Heikki Haario. I will present our recent results in model parameter estimation, now including the total energy norm as a target for model selection (or, optimization). We have applied the Ensemble prediction and parameter estimation algorithm (EPPES) to ECHAM5 atmospheric GCM at low resolution, and tuned four of its cloud and precipitation formation parameters so that the optimized model outperforms the default model in terms of total energy norm of forecast error at day three. The improvement is distributed across nearly all model variables, and interestingly, the optimized model continues to outperform the default model up to 10-day range. We conclude that the total energy norm of forecast error constitutes a promising target in model tuning and since it is an integral over the entire model domain, it is not selective to some particular model variables, areas, or layers. We are continuing to test the idea using the OpenIFS.

21 October 10:30

LT

IFS on Intel Xeon Phi

Sami Saarinen, CSC Finland

### Abstract

ECMWF IFS forecast model (including WAM-coupling) has been successfully migrated to the Intel Xeon Phi (aka MIC alias KNights Corner KNC) 'manycore' architecture at CSC in Finland. In the near future such systems could potentially provide a cost effective computing alternative to the existing server systems, and unlike GPGPU-cards enable standalone mode of execution. The presentation includes brief introduction to the MIC-hardware available at CSC, migration issues, and results of T255L91/24h model in hybrid MPI + OpenMP on one to several MIC-cards. Comparisons to the Intel Sandy Bridge servers as well as to CSC's Cray XC30 are briefly mentioned, too.

21 October 15:30

LT

Global model-data-fusion estimates of ecosystem carbon fluxes

Mathew Williams, University of Edinburgh

### Abstract

Large uncertainties preside over terrestrial carbon flux estimates on a global scale. In order to gain an improved understanding of ecosystem C fluxes, we implement a Monte Carlo based model-data-fusion approach: we assimilate MODIS LAI, plant-trait data, and the Harmonized World Soil Database(HWSD) into the Data Assimilation Linked Ecosystem Carbon (DALEC) Model, and we implement our approach on an 8-day timestep 1 x 1 degree resolution for the period 2001-2010. In addition to observational constraints, we implemented a novel Bayesian parameter inter-dependence network in order to impose ecological and dynamic constraints on DALEC parameter values. We determined the spatial and temporal dynamics of major terrestrial C fluxes and model parameter values on a global scale (GPP = 123 +/-8 Pg C yr-1 & NEE =-1.8 +/-2.7 Pg C yr-1). In order to validate our approach, we also implemented our model-data-fusion setup at flux-tower scale, and compared DALEC NEE fluxes against in-situ NEE measurements (AMERIFLUX network) across multiple biomes and plant-functional types (NEE daily bias = +/-0.83 gC m-2 day-1). In anticipation of the BIOMASS mission, we examine the additional uncertainty reduction resulting from above-ground biomass data assimilation. We anticipate that our global model-data-fusion approach will be an important step towards bridging the gap between globally spanning remotely-sensed biometric data and the full ecosystem C cycle.

25 October 11:00

LT

Eugenia Kalnay, Dept of Atmospheric and Oceanic Science, University of Maryland

### Abstract

In recent years, Ensemble Kalman Filter has become the most popular approach for advanced data assimilation. I will present several algorithms that extend its potential applications, including studies of the application of these algorithms to real and simulated observations using the Local Ensemble Transform Kalman Filter. They include effective assimilation of precipitation (Lien et al., 2013), LETKF-RIP applied to typhoon Sinlaku (Yang et al, 2012) and to 7 years of global ocean data assimilation (Penny et al, 2013), estimation of surface carbon, heat and moisture fluxes from atmospheric data assimilation (Kang et al., 2012), Ensemble Forecast Sensitivity to Observations (Kalnay et al., 2012, Ota et al., 2013) and its applications to “proactive QC” (Hotta et al., 2013). Our plans on coupled ocean-atmosphere data assimilation will also be discussed.

31 October 15:30

LT

A role for continuous grid adaptivity in climate and weather prediction

Joe Prusa (Teraflux Corp., Boca Raton, Fl)

### Abstract

The value of curvilinear coordinates is well established in climate and weather prediction. Such coordinate systems can offer clarity in physical insights about meteorological phenomena of interest as well as simplicity of computational approach. This talk will present the case that extension of curvilinear coordinates with fully continuous dynamic grid adaptivity is a natural generalization for the next generation of NWP models. Continuous GA can offer further enhancements such as increased resolution on targeted regions and/or dynamical–moist structures of interest. Locally enhanced resolution can have global impact. Continuous GA also enables a practical way to test interactions between regions characterized by different meteorological processes via the mechanism of adjustable grid resolution that would otherwise be difficult or impossible to make.

This talk will briefly summarize the basic ideas underlying continuous dynamic grid adaptivity in large–scale computation. In general, the desired grid structure is non-uniform and/or moving. A mapping between two distinct spaces is applied, and in the transformed space the structured computational grid is uniform, stationary, and the boundaries “straight” irregardless of the deformations occurring in the physical space. The chosen map must satisfy the typical continuity constraints and also two types of transformation rules. These transformation rules are intrinsically geometrical in nature and vital for maintaining conservation and the parallel transport property.

Examples are presented ranging from idealized regional and global tests to aqua-planet and African climate simulations. They are chosen to illustrate how GA can improve model efficiency; demonstrate advantages from locally improved resolution that produce regional/global as well as local impact; or help to illuminate the role of different types of global dynamics in moist processes.

14 November 10:30

LT

Climate modeling with super-parameterization and beyond

Marat Khairoutdinov (School of Marine & Atmospheric Sciences Stony Brook University, NY)

### Abstract

Clouds play a key role in the Earth's climate system. Yet, they are not generally resolved by general circulation models (GCMs), but rather, parameterized using cloud parameterizations. An alternative approach to cloud parameterizations in GCMs is a so-called super-parameterization(SP), which is a small-domain cloud-resolving model inserted into each grid-column of a GCM to replace cloud parameterizations. The first GCM with the SP, the SP-CAM, based on the NCAR's Community Atmosphere Model (CAM), has been used since about 2001 to better simulate phenomena such as the Madden-Julian Oscillation, and to study cloud feedbacks in the climate system. The details of the SP approach and key results will be discussed. Recently, the SP has been implemented in the OpenIFS model. Some preliminary SP-IFS model results will be presented.

26 November 10:30

LT

Arctic sea ice, modelling and predictability

Matthieu Chevallier, CNRM-GAME, Météo-France/CNRS and Mercator-Océan, Toulouse, France

### Abstract

This presentation will focus on activities related to Arctic sea ice modelling and forecasting at CNRM-GAME(Météo-France/CNRS) and Mercator-Océan (Toulouse, France).

The GELATO sea ice model will be presented. This state-of-the-art multicategory model is coupled to the NEMO (version 3.2) model and included in CNRM-CM5 coupled atmosphere-ocean model (1°x1° horizontal resolution). CNRM-CM5 has been used for IPCC AR5 climate scenarios and decadal prediction experiments. CNRM-CM5 is also planned to be used as the next system of seasonal forecasting at Météo-France. The skill of CNRM-CM5 in forecasting the Arctic sea ice has already been assessed in 1990-2010 hindcasts initialized from a forced ocean-sea ice reconstruction with NEMO-GELATO.

Skill scores of summer and winter forecasts of the Arctic sea ice extent are promising, and show that at a 5-month lead time, sea ice predictability is mainly an initial value problem. These hindcasts also help to identify some mechanisms responsible for sea ice predictability at such time scales. Plans for improvements (data assimilation, increase in resolution) and future work planned at CNRM-GAME on sea ice modelling and seasonal predictability in the polar regions will be presented.

Part of the presentation will also be about high-resolution ocean-sea ice modelling at Mercator-Océan, and collaborative plans between Météo-France, Mercator-Océan and the Canadian Meteorological Centre (Environment Canada) for the development of a regional Arctic ocean-sea ice model at 1/12° using the NEMO platform and Mercator-Océan's data assimilation system.

26 November 15:30

MR1

DEWFORA Seminar:

How useful are ECMWF precipitation forecasts over Africa for drought applications?

### Programme

• Presentation of DEWFORA and main results from ECMWF’s involvement - Emanuel Dutra/Fredrik Wetterhall
• Forecasting droughts in East Africa  - Emmah Mwangi, KMA, Kenya
• Exploring the potential of adapting to climate change through seasonal prediction of meteorological drought indicators - Hessel Winsemius, Deltares, The Netherlands
• Developing a Pan-African map viewer for drought - Paulo Barbosa, JRC, Italy

6 December 9:30

Classroom

JRC tropical cyclones simulation in support to the Global Disasters Alerts and Coordination System

Alessandro Annunziato and Delilah Al Khudhairy, Joint Research Centre, EC

### Abstract

The Joint Research Centre developed, in collaboration with the United Nation Office for Coordination of Humanitarian Affairs (UN-OCHA) the Global Disasters Alerts and Coordination System aimed at providing the humanitarian community of a pre-alert for possible large disasters event which may need the assistance of large international teams on the field. The area of interest includes Earthquakes, Tsunami, Tropical Cyclones and Floods.

For Tropical Cyclones GDACS provide early estimation of winds, rainfall and storm surge effects by using information provided by international typhoon centers and performing online calculations whose results are then published automatically in the GDACS web site (www.gdacs.org). The cyclone calculations are performed by reconstructing the pressure and wind file using the data present in the bulletins and computing, with a Monte Carlo simulation, the Holland parameters to have the whole wind/pressure profile. The method has been so far successful in identifying the major events worldwide, including the Philippines case.

Recently a new activity has been initiated in order to explore the possibility to use ECMWF wind and pressure estimates from the Medium Range deterministic model as boundary conditions to the storm surge calculations. The reason was the announcement and the availability of finer estimates (16 km) respect to the previous one (50 km) and thus enabling a better resolution, as required by the hydraulic calculations. The results of this pilot activity are extremely interesting for several reasons that will be discussed in the presentation: in some cases the agreement with measured storm surge are really very good while in other cases the forcing is not enough to generate sufficient surge as measured. In any case this method has the advantage to make possible the analysis of extra tropical cyclones which are normally not analysed in GDACS.

10 December 10:30

LT

Preconditioning Saddle Point Formulation of 4D-VAR

Selime Gurol, ECMWF

### Abstract

In this talk we will address the numerical solution of the saddle point system arising from four dimensional variational (4D-Var) data assimilation with an emphasis on a study of preconditioning with low-rank updates. The saddle point formulation of 4D-Var allows parallelization in the time dimension. Therefore, it represents a crucial step towards improved parallel scalability of 4D-Var. We will present numerical results obtained from the Object Oriented Prediction System (OOPS) developed by ECMWF.

12 December 10:30

LT

Diabatic processes in extratropical cyclones: Dynamics and relevance for forecast accuracy

Heini Wernli, Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland

### Abstract

The prediction of the track, intensity and structure of extratropical cyclones is of key importance for accurately forecasting intense winds and precipitation associated with these weather systems. In addition to the primary agents of baroclinic instability, i.e., the horizontal temperature gradient and typically an upper-level cyclonic vorticity disturbance, moist diabatic processes that occur in saturated ascending airstreams are essential for the evolution of cyclones, the associated surface weather, and the downstream flow evolution. A potential vorticity perspective helps explaining how diabatic processes impact on the dynamics of extratropical cyclones and tropopause-level Rossby waves. Results from complementary studies in our group, mainly based upon ECMWF (re)analysis and forecast data, will be shown to illustrate that (i) the diabatic PV production in the low troposphere is essential for the formation of intense extratropical cyclones, (ii) diabatic processes are particularly intense in so-called warm conveyor belts, i.e., in moist ascending airstreams associated with extratropical cyclones, (iii) a major part of precipitation extremes occurs in associating with extratropical cyclones and/or warm conveyor belts, (iv) exceptionally poor global model medium-range weather forecasts in Europe are often associated with errors in the representation of warm conveyor belts, (v) during the previous 10 years, the accuracy in predicting the intensity and location of these moist ascending airstreams has improved for the ECMWF high-resolution model, and (vi) that a combination of different microphysical processes occurring within these conveyor belts is responsible for the overall latent heating and associated potential vorticity modification. The presentation will also emphasise (a) the usefulness of investigating dynamical processes in ensemble predictions, (b) the need for field experiments dedicated to observing diabatic processes in mid-latitude weather systems, and (c) the value of a systematic feature-based forecast validation of weather systems with NWP and climate models.

12 December 11:30

LT

Weather regime project at ETH

Christian Grams, Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland

## 2012

9 January 14:00

MR1

On the North Pacific reduced skill in near-term climate predictions of sea surface temperatures

Virginie Guemas, IC3 - Institut Català de Ciències del Clima CFU, Climate Forecasting Unit, Barcelona, Spain

### Abstract

Near-term climate prediction relies both on the predictability of the internal climate variability, by initializing climate models from estimates of the observed state, and on the externally forced predictability (by greenhouse gases, aerosols, solar activity). This exercise shows that the North Pacific region is where the current generation of climate forecasting systems performs the worst worldwide. In this presentation, we look for the major events missed by the forecasting systems and we investigate the reasons for this failure.

27 January 14:00

LT

Atmospheric composition monitoring from the geostationary orbit: US plans and the international context

David Edwards, NCAR Earth System Laboratory, Deputy Director

30 January 15:30

LT

When will the Arctic become ice free?

Seymour Laxon, Centre for Polar Observation and Modelling, University College London

### Abstract

Changes in Arctic sea ice cover are perhaps the most visible evidence for the Earths changing climate. Satellite records have shown a 30% decrease in the September ice extent over the last 30 years and submarines have found a similar decline in thickness over limited regions. However model predictions of the date at which the Arctic might become ice free in summer vary widely. This seminar will discuss the key issues involved and present new data, in particular from the CryoSat mission, which can shed light on this question. We will also describe the fieldwork which is ongoing to validate the CryoSat measurements.

6 March 15:30

LT

Sub-seasonal predictability and dynamical processes: the two-way MJO and NAO interaction

Gilbert Brunet, Meteorological Research Division (MRD), Environment Canada

### Abstract

The Madden-Julian Oscillation (MJO) is the dominant mode of intraseasonal variability in the tropics [Madden and Julian, 1971], which has a direct impact on the weather in the tropical region, as it organizes convection and precipitation. It also has a significant influence on the extratropical atmospheric variability, possibly through Rossby wave propagation [Lin et al., 2009], and thus provides an important signal source for the extratropical weather forecasts on subseasonal timescales. A skilful prediction of the MJO is of great importance. The North Atlantic Oscillation (NAO) is one of the most important modes of variability in the Northern Hemisphere extratropical atmosphere [Hurrell, 1996]. In the work of Lin et al. [2009], it was found that there is a significant two-way interaction between the MJO and the NAO. On the one hand, the MJO, through extratropical Rossby wave propagation associated with its anomalous tropical convection and diabatic heating, influences the extratropical circulation and the NAO amplitude. On the other hand, the NAO variability results in changes in the tropical upper zonal wind and the initiation of the MJO. By analyzing the output of an intraseasonal hindcast, Lin et al. [2010] have shown that the MJO has a significant impact on the intraseasonal forecast skill of the NAO. In Lin and Brunet [2011], it was demonstrated that the NAO also has an important influence on the forecast skill of the MJO. Intraseasonal forecasts would benefit from such an interaction if such a process can be resolved in forecasting system.

1.Lin, H., and G. Brunet, 2011: Impact of the North Atlantic Oscillation on the forecast skill of the Madden-Julian Oscillation. Geophys. Res. Lett., VOL. 38, L02802, doi:10.1029/2010GL046131.

2. Lin, H., G. Brunet and J. S. Fontecilla 2010: Impact of the Madden-Julian Oscillation on the intraseasonal forecast skill of the North Atlantic Oscillation. Geophys. Res. Lett., 37, L19803.

3. Lin, H.,G. Brunet, and J. Derome, 2009: An observed connection between the North Atlantic Oscillation and the Madden-Julian Oscillation. J. Climate, 22, 364-380.

4. Madden, R. A., and P. R. Julian, 1971: Description of a 40-50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702–708.

7 March 10:30

LT

Experimental 4D-Var assimilation of SYNOP rain gauge data at ECMWF

Philippe Lopez, ECMWF

### Abstract

The potential benefits of assimilating worldwide SYNOP rain gauge 6-hour rainfall accumulations in both data-sparse reanalysis-like and high-resolution operations-like experiments have been investigated using ECMWF's 4D-Var system.

Results clearly indicate that rain gauge assimilation can lead to significant improvements in global analysis and forecast scores when the coverage in other observation types is sparse (as would be the case in early-20th-century reanalyses). In contrast, when SYNOP rain gauges are assimilated together with the full modern-day coverage of surface, radiosonde and satellite observations, their impact on analysis and forecast quality remains much more modest, as expected.

A description of the method used to assimilate rain gauge measurements will be given, which will cover the issues of screening, error specification and bias correction. Examples of the impact on analysis and forecast scores will then be presented and finally remaining issues as well as the potential for future improvements will be addressed.

14 March 10:30

LT

Aerosol-Cloud-Radiation Interactions and their Impact on ECMWF/MACC forecasts

Jean-Jacques Morcrette, ECMWF

### Abstract

Prognostic aerosols were experimentally introduced in the ECMWF Integrated Forecasting System as part of the GEMS project in 2005. Their representation was refined as part of the MACC project, starting in 2009. Here, the MACC aerosol system is used to explore the impact of different levels of interactions between the aerosols and either the radiation and/or the cloud processes on cloudiness, radiation and precipitation fields, and on objective scores.

Ten-day forecasts including fully interactive aerosols are also compared to forecasts with aerosols specified from the analysis and kept constant thereafter.

Whereas the temporal variability of the prognostic aerosols is shown to have strong local effects on surface parameters, the impact on objective scores is much smaller.

21 March 10:30

LT

Challenges of a sustained Climate Observing System

Kevin Trenberth, National Center for Atmospheric Research, Boulder

### Abstract

Observations of planet Earth and especially all climate system components and forcings are increasingly needed for planning and decision making related to climate services in the broadest sense. Although significant progress has been made, much more remains to be done before a fully functional climate observing system exists. Observations are needed on all spatial scales from local to global, and all time scales, especially to understand and document changes in extremes. Climate change from human activities adds both a new dimension and an imperative: to acquire climate observations of sufficient quality and coverage, and analyze them into products for multiple purposes to inform decisions for mitigation, adaptation, assessing vulnerability and impacts, geo-engineering, and predicting climate variability and change and their consequences. A major challenge is to adequately deal with the continually changing observing system, especially from satellites and other autonomous platforms such as in the ocean. Even with new computational tools, further challenges remain to provide adequate analysis, processing, meta-data, archival, access, and management of the resulting data and the data products. As volumes of data continue to grow, so do the challenges of distilling information to allow us to understand what is happening and why, and what the implications are for the future.

22 March 10:30

LT

The new Fortran coding standard for IFS

Mike Fisher, ECMWF

29 March 15:30

LT

Project SimulAMV2: Using geostationary imagery from high resolution model simulations to improve the characterization of current Atmospheric Motion Vectors

Angeles Hernandez and Niels Bormann

### Abstract

In this seminar we will present the main results of SimulAMV2, a 13-month project funded by EUMETSAT and carried out by the ECMWF and EUMETSAT, with the collaboration of CIMSS.

The overall objective of the project is to improve the characterization of Atmospheric Motion Vectors (AMVs) and their errors to improve the use of AMVs in Numerical Weather Prediction. This study approaches the analysis of AMV errors by using geostationary imagery generated from high resolution NWP model simulations. AMVs are derived from sequences of simulated images, using a derivation system similar to the one used operationally by EUMETSAT. The NWP model provides a "ground truth", which allows a detailed study of AMV errors, bypassing the usual difficulty of the scarcity of collocated observations of cloud and wind.

First, cloud structures from observed and simulated images will be compared; this is an important step, as findings from simulated imagery can be extended to observed imagery only if the cloud structures produced from model simulations are realistic. Then we will present evaluations of AMVs by comparing them to the model truth, first interpreting AMVs as point, single level observations of wind, and then as horizontal and vertical averages. We will also show results regarding horizontal, vertical and temporal correlations of errors, and finally we will discuss the role of clouds, focussing on the impact of vertical cloud profiles and cloud evolution on systematic AMV errors.

17 April 10:30

LT

Ensemble forecasts of spring flood in Sweden

David Gustafsson and Jonas Olsson, SMHI

### Abstract

Part 1: Snow-melt runoff predictions assimilating seasonal weather forecasts and ground penetrating radar measurements of snow water equivalent

Uncertainties in snow melt runoff predictions with regard to the amount of snow and timing of melt typically emerge from uncertainties in the meteorological input data. These uncertainties can be reduced by data assimilation to update the simulated snow water storage using snow survey data and remotely sensed snow extent data. The objectives of this study are (1) to evaluate seasonal snow and snow melt runoff simulated by the hydrological model HYPE when forced by the ECMWF seasonal weather forecasts, and (2) to evaluate to what extent the seasonal snow melt predictions can be improved by assimilation of observations of snow water equivalent at the time of peak accumulation and discharge observations during the snow melt period.

Snow and runoff observations were assimilated into the HYPE model using the Ensemble Kalman filter data assimilation method. The study was conducted using data from two mountain basin in northern Sweden over the winters 2007-2011. Distributed snow cover data was sampled using ground-penetrating radar (GPR) from snow mobiles at the time of the maximum snow cover.

Simulations for the years 2007-2011 were performed with meteorological forcing data either based on station data or seasonal weather prediction data, with and without assimilation of the SWE data, respectively. The results show that the assimilation of GPR-data strongly improves the simulated results of snow melt runoff, especially for the simulations driven by the seasonal weather forecasts. It is suggested that the assimilation of the snow and runoff data can be used in the development of the bias corrections of the seasonal weather forecasts.

Part 2: A comparison of different approaches for forecasting spring floods in Sweden and the feasibility of a multi-model forecast system

In this study, three different ensemble forecast approaches to spring flood forecasting were compared with the state-of-the-art operational hydrological model implemented at SMHI. The methods consisted of (1) a reduced historical ensemble approach, where analogue years from the historical dataset, (2) using seasonal forecasts from ECMWF and (3) statically downscaling large-scale circulation variables from ECMWF seasonal forecasts to accumulated discharge using Singular Value Decomposition. The different approaches were evaluated for forecasts issued on 1/1, 1/3 and 1/5 for the spring floods 2000-2010 in three Swedish rivers. The evaluation was mainly performed in terms of the mean absolute error (MAE) of accumulated discharge with the state-of-the-art forecast as a reference. MAE was reduced in two catchments using the different approaches, whereas no effect was seen in the third catchment. However, a combination of all methods gave the largest error reduction on average.

20 April 10:30

LCR

Medium-range and seasonal river forecasting in China

Dr. Liu Zhiyu and Ms. Yue Zhihui, Ministry of Water Resources, China

25 April 10:30

LT

Assessing the impact of SST forcing on the forecast of past MJO events

Eric de Boisseson

### Abstract

Several past Madden-Julian Oscillation (MJO) events are simulated using the ECMWF monthly forecasting system. Several ocean-atmosphere coupled experiments and atmosphere only experiments are conducted. The impact of the different strategies on the MJO forecast skill is investigated through diagnostics and additional experiments.

26 April 10:30

MR1

Optimization and utility of TAMDAR aircraft observations for NWP

Neil Jacobs, AirDat LLC, Morrisville, NC

### Abstract

Lower and middle-tropospheric observations are disproportionately sparse, both temporally and geographically, when compared to surface observations. The limited density of observations is likely one of the largest constraints in numerical weather prediction. Atmospheric observations collected by a multi-function in-situ atmospheric sensor on aircraft, called the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) sensor, contain measurements of humidity, pressure, temperature, winds aloft, icing, and turbulence, along with the corresponding location, time, and altitude from built-in GPS are relayed via satellite in real-time to a ground-based network operations center. The TAMDAR sensor was originally deployed in December 2004 on a fleet of 63 Saab 340s operated by Mesaba Airlines in the Great Lakes region as a part of the NASA-sponsored Great Lakes Fleet Experiment (GLFE).Over the last eight years, the equipage of the sensors has expanded beyond CONUS to include Hawaii, Alaska, Mexico, UK, and western Europe on 13 fleets of regional airlines. In addition to the standard commercial airline program, a miniaturized version of the sensor has been deployed on several unmanned aerial vehicles (UAVs). Upon completion of the 2012 installations, more than 7000 daily sounding will be produced globally. An overview will be provided on the status of the TAMDAR sensor network deployment and data availability, as well as an update on data quality, error statistics, and operational forecasting utility, both from soundings and various data assimilation techniques. Current data assimilation optimizations include splitting the ascent, descent, and cruise observations into different phases of flight, correcting for the magnetic deviation bias in heading instrumentation, and isolating wind speed versus wind direction errors.

2 May 10:30

LT

Atmospheric predictability at the convective scale

Giovanni Leoncini, Met Office

### Abstract

The current availability of computing power allows weather services, to run ensemble forecasts at resolutions that ensure at least a partial representation of convection and thunderstorms (i.e. the convective scale). The representation of severe weather is much more realistic at this scale and there is an increasing interest in this kind of forecast from emergency services, aviation and industry. However, at these scales (~ 1km and smaller) the predictability of the atmosphere is very different from the predictability at larger and better known scales of the order of 100 or 1000 km and it poses several fundamental challenges to the scientific community. The aim of this presentation is to provide an overview of such challenges, describing current research efforts and discussing future ones. The first part of the talk focuses on the basics differences between atmospheric predictability at the convective scale and larger ones. The second part is a quick overview of the current efforts and implementations at the major weather services. Finally I'll discuss future research directions.

9 May 15:30

LT

What do good weather forecasters do - and how can they do it even better?

### Abstract

We are today in a situation where not only operational weather forecasters at the national meteorological services make use of our products but also an increasing number of meteorological consultants and private weather services, hydrologists and other non-meteorologists enthusiastically trying to make the best use of the enormous amount of freely and commercially available meteorological information from a multitude of sources. How can they make the best use of ECMWF products, in particular the Ensemble Prediction System?

The presentation takes off from the "ECMWF User Guide" and the discussion in the autumn "Newsletter". It further develops the notion that skilled weather forecasters, in the heat and frenzy of operational activity, in the name of "experience", make use of "intuitive statistics". A recent "best-seller" by the Nobel Laureate in economics, Daniel Kahneman, devoted to the problem of the use intuitive statistics", might provide valuable insights how a current intuitive work practice can be put on a more reasoned basis, in particular with respect to the statistically geared Ensemble Prediction System.

28 May 10:30

LT

Report on stochastic physics progress

Glenn Shutts

29 May 14:00

LT

Using climatological information in ensemble data assimilation through observations and through stochastic parametrizations

Dr Georg Gottwald, Sydney University, Australia

### Abstract

We investigate how to incorporate climatological information in ensemble data assimilation schemes. This can be done either on the level of providing additional observational, or on the level of parametrized forecast models. In a first part, we consider the problem of an ensemble Kalman filter when only partial observations are available. For small ensemble sizes this leads to an overestimation of the error covariances. We show that by incorporating climatic information of the unobserved variables the variance can be controlled and superior analysis skill is obtained. We then employ this Variance Controlling Kalman Filter to control model error when the model is allowed to be void of stabilizing artificial numerical viscosity. In a second part, we consider a deterministic multiscale toy model in which a chaotic fast subsystem triggers rare transitions between slow metastable regimes, akin to weather or climate regimes in the context of climate dynamics. Using homogenization techniques we derive a reduced stochastic model as a stochastic parametrization model for the slow dynamics only. We show that the stochastic reduced model can outperform the full deterministic model as forecast model in an ensemble data assimilation procedure, in particular in the realistic setting when observations are only available for the slow variables. We relate the observation intervals for which skill improvement can be obtained to the time scales of the system. We then set out to explain why stochastic climate models produce superior skill in an ensemble setting. The improvement in skill is due to the finite size of the ensemble, and we show that there is no skill improvement in very large ensembles or when the forecast variance is artificially and unreasonable inflated. We corroborate this with numerical simulations. This is joint work with Lewis Mitchell and Sebastian Reich.

8 June 11:00

MR1

Correcting for conditional bias in hydrometeorological and hydrologic ensemble predictions: a nonparametric approach

James D. Brown, Hydrologic Solutions Limited, Southampton

### Abstract

Ensemble forecasts generally contain biases in the mean, spread, and higher moments of their predictive probability distributions. Practical applications of hydrometeorological and hydrologic ensemble forecasts are sensitive to bias. For example, the tendency to overestimate light precipitation or streamflow and underestimate heavy precipitation or streamflow can reduce the value of hydrologic predictions for drought and flood forecasting. Statistical post-processors have traditionally focused on “calibrating” raw predictions, in order to improve reliability or reduce conditional bias given the predicted outcomes (Type-I conditional bias). However, the Type-II conditional biases are equally important in operational forecasting, as the impacts of decisions about weather and water variables are sensitive to observed outcomes (e.g. flooding being observed to occur, as opposed to simply forecast with given probability).

This paper evaluates a non-parametric technique for bias-correction and uncertainty estimation of hydrologic and hydrometeorological predictions. The technique employs Bayesian optimal linear estimation of indicator variables, and is analogous to indicator cokriging (ICK) in geostatistics. The coefficients of the predictors can be chosen to minimize the conditional error variance of the estimator (Brier Score) or, without loss of analytical tractability, a combination of the conditional error variance and the square bias conditional upon the observed outcome, i.e. Type-II conditional bias.

21 June 10:30

MR1

Hidden error variance theory and its potential use in Hybrid data assimilation

Craig Bishop, Naval Research Laboratory, Monterey

### Abstract

A conundrum of predictability research is that while the prediction of flow dependent error distributions is one of its main foci, chaos fundamentally hides flow dependent forecast error distributions from empirical observation. Empirical estimation of such error distributions requires that one obtain a large sample of error realizations given the same flow and the same observational network. However, chaotic elements of the flow and the observing network make it practically impossible to observe and collect the conditioned sample of errors required to empirically define such distributions and their variance. These variances are “hidden”. Here, an exposition of the problem is developed from an ensemble Kalman filter data assimilation system applied to a 10 variable non-linear chaotic model and 25,000 replicate models. The output from this system motivates a new analytical model for the distribution of true error variances given an imperfect ensemble variance. This model is defined by 6 parameters that also determine the optimal weights for the static and flow dependent parts of Hybrid error variance models. Two of the 6 parameters are trivial to estimate. The other four parameters are comprised by the variance and minimum of the climatological distribution of true error variances, parameter that defines the mean response of ensemble variances to changes in the true error variance and the climatological minimum of true error variance. These parameters are hidden because they are defined in terms of the flow dependent forecast error variance– which is unobservable in systems exhibiting aperiodic chaos. Six new equations enable these hidden parameters to be accurately estimated from a long time series of (innovation or observation minus forecast, ensemble variance) data pairs. This new-found ability to estimate hidden parameters provides new tools for assessing the quality of ensemble forecasts, tuning Hybrid error variance models and for post-processing ensemble forecasts. Preliminary results from attempts to use the theory to speed the tuning of Hybrid data assimilation schemes will also be presented.

22 June 14:00

Classroom

EFAS and its links to ECMWF research

Florian Pappenberger, ECMWF

4 July 10:30

LY

Characteristic features of rainfall mechanism over Korea inferred from satellite measurements

B.J. Sohn, School of Earth and Environmental Sciences Seoul National University Seoul, Korea

### Abstract

Heavy rainfall over the Korean peninsula is often thought to be associated with the convection system with high and cold cloud top and strong updrafts. By contrast, the analysis of satellite observations including TRMM, MODIS, and CloudSat indicates that heavy rainfall over the Korean peninsula can also be related to relatively low-level clouds whose cloud top temperature is warmer. Prevalent water clouds are also evident. Large-scale weather conditions related to such low-level warm-type clouds causing heavy rainfall over the Korean peninsula (and/or surrounding areas) were deduced from a clustering analysis of MODIS cloud products and by relating obtained results to ECMWF reanalysis fields. It is found that low-level warm-type clouds producing heavy rainfall over Korea appear to be associated with large-scale conditions in which a feature like 'water vapor transporting channel' is established along the northwestern periphery of the North Pacific high. Much of water vapor is transported through the channel and converges on the area of Korea and surrounding regions. Because of excessive water vapor, it may be possible to produce heavy rainfall even with a small updraft within the lower tropospheric layer. This is much different from what can be expected from the typical convective clouds causing flash flood over the Great Plains of US. Realizing the fact that cloud/precipitation algorithms in the state-of-art weather prediction models have been developed targeting the convectively active weather common in US, it is important to recognize a new type of cloud-rain system over the humid East Asian environment.

17 July 10:30

LT

Scientific challenges in remote sensing of soil moisture

Prof. Wolfgang Wagner , Institute of Photogrammetry and Remote Sensing (I.P.F.), Vienna University of Technology (TU Wien)

### Abstract

Remote sensing of soil moisture is a rapidly evolving research field that has achieved several critical achievements in the last few years. Among those are the launch of SMOS in 2009 and the establishment of the International Soil Moisture Network (ISMN) in 2010/11. In this presentation outstanding scientific challenges are discussed.

The discussion is organized around the following six themes:

1. Do L-band sensors outperform higher-frequency sensors?
2. Is there a scientific consensus on best practices in validation?
3. How to improve error characterisation?
4. Where are advances in data assimilation needed?
5. It is worth to investigate applications that appear to be impossible at first sight?

Are we ready to tackle scientific frontiers in climate change research?

23 July 10:30

LT

Modernisation of the observation interpolation operator (GOM)… and thoughts on the quality of code in the IFS

Alan Geer, ECMWF

### Abstract

After twenty years of incremental development, the GOM interpolation code has become very difficult to maintain, let alone to extend for new science. There have been attempts to tidy the code but these proved difficult and ultimately a complete rewrite was the quickest solution. By starting from scratch, it was possible to use modern coding techniques, and to make the new GOMs modular and as nearly object-oriented as Fortran 90 allows. This talk will show how to use the new GOMs, including how to get new variables into the observation operator. Further, what goes for the GOMs goes for much of the rest of the IFS: twenty years' accretion of new features and the sometimes old-fashioned or plain bad programming makes it hard to maintain the code or to add new science. It is hoped to provoke plenty of discussion, to present some examples of good and bad practice, and to make suggestions for improving code quality in the context of OOPS and COPE.

25 July 15:30

LT

Paths to accuracy in radiation parameterization for large-scale models

Robert Pincus, University of Colorado/NOAA Earth System Research Lab

25 July 10:30

LT

The Suomi National Polar-Orbiting Partnership (NPP) CalVal Overview

Fuzhong Weng, Satellite Calibration & Data Assimilation Branch at NOAA/NESDIS

### Abstract

The Suomi NPP (SNPP) satellite was launched successfully on October 28, 2011 and is a pathfinder for the future US Joint Polar Satellite System (JPSS) operational satellite series. The primary objectives of the SNPP mission provide a continuation of the group of Earth system observations initiated by the Earth Observing System Terra, Aqua, and Aura missions; and prepare the operational forecasting community with pre-operational risk reduction, demonstration, and validation for selected JPSS instruments and ground processing data systems. The SNPP satellite is now flying with the following five instruments:

1. Visible/Infrared Imager/Radiometer Suite (VIIRS) has multi-band imaging capabilities to support the acquisition of high-resolution atmospheric imagery and generation of a variety of applied products including visible and infrared imaging of hurricanes and detection of fires, smoke, and atmospheric aerosols.
2. Cross-track Infrared Sounder (CrIS) is the the first in a series of advanced operational sounders that provide more accurate, detailed atmospheric temperature and moisture observations for weather and climate applications.
3. Advanced Technology Microwave Sounder (ATMS) operates in conjunction with the CrIS to profile atmospheric temperature and moisture. Higher (spatial, temporal and spectral) resolution and more accurate sounding data from CrIS and ATMS support continuing advances in data assimilation systems and NWP models to improve short-to medium-range weather forecasts.
4.  Ozone Mapping and Profiler Suite (OMPS) measures the concentration of ozone in the atmosphere, providing information on how ozone concentration varies with altitude. Data from OMPS continue three decades of climate measurements of this important parameter used in global climate models. The OMPS measurements also fulfill the U.S. treaty obligation to monitor global ozone concentrations with no gaps in coverage.
5. Cloud and Earth Radiant Energy System (CERES) seeks to develop and improve weather forecast and climate models prediction, to provide measurements of the space and time distribution of the Earth's Radiation Budget components. The observations from CERES are essential to understanding the effect of clouds on the energy balance (energy coming in from the sun and radiating out from the earth), which is one of the largest sources of uncertainty in our modeling of the climate.

The Suomi NPP instruments are now undergoing a period of intensive calval and their performances in orbit are stable and meet or exceed the specifications. The SNPP SDR products are all reaching a provisional level at which users can order the data from NOAA archival and perform in-depth scientific research. NOAA is also operationally using the ATMS data in its global forecast system (GFS) and generating a suite of EDR products from the NPP ground system. During the past 8 months of intensive calval, NPP/JPSS SDR teams have developed many innovative techniques for characterizing the instrument performance (e.g. noise and bias), fixed numerous SDR processing bugs and improved the quality control flags in the data streams. The critical SNPP calval tasks have been completed and the most recent calval results will be reported in this presentation.

30 July 15:30

LT

Fighting Hunger – How ECMWF Forecasting Platforms have been supporting WFP Operations

Thomas Petroliagis, ECMWF

### Abstract

The World Food Programme (WFP) is the United Nations frontline agency in the global fight against hunger. WFP aims to get food to where it is needed as quickly as possible, saving the lives of victims of war, civil conflict and natural disasters. Being well prepared to respond to disasters is a top priority for WFP. To accomplish its mission WFP has been depending heavily on all ECMWF forecasting platforms (operational high-resolution forecast–ensemble prediction system–monthly and seasonal systems) and ERA–Interim reanalysis data. The graphical forecasting environment ecCharts is also utilized to fulfil WFP’s daily operational needs and requirements.

29 August 10:30

LT

Bayesian Statistics – the Emperor's New Clothes or the Solution to Everything?

### Abstract

For almost 200 years there has been intense controversy surrounding the Rev. Thomas Bayes (1702-61) simple formula for conditional probability

prob(A|B) = [prob(A)·prob(B|A)] / prob(B)

Until quite recently a minority among statisticians have declared themselves devoted “Bayesians” against a majority of fervent Anti-Bayesian "Frequentists". The seminar tries to explore the historical roots of this conflict, which shows sign of abating partly thanks to improved computer technology.

It will also suggest that a lot of Bayesian applications have been concealed in the literature, sometimes because the scientists wanted to avoid the “B-word”, sometimes because they didn’t know that they were applying Bayesian principles. The latter might be the case among meteorologists and hydrologists working with forecast model development.

8 October 14:00

LT

Time-parallel algorithms for weather prediction and climate simulation

Jean Cote, ESCER Center, Earth and Atmospheric Sciences
Universite du Quebec a Montreal (UQAM)

### Abstract

The forecast of weather relies on computer models that need to be executed in real-time, meaning that a forecast needs to be disseminated to users well before the time period for which it is made. A challenge in the future will be to succeed in using the computing power available in massively parallel high-performance computers and meet the real-time requirement. Until now weather forecast and related climate simulation models have taken advantage of the parallelism of the computers by dividing the task to be performed in the horizontal space dimensions.

The purpose of this work is to develop algorithms that allow also parallelism in the time dimension. This increased parallelism should allow an acceleration of the execution time of weather and climate models. This acceleration in turn permits an increase in the space accuracy of models while still meeting the real-time requirement. The talk will present our preliminary work on the "Parareal" algorithm that has been developed for that purpose (Lions et al., 2001) and whose applications to date have included among others air quality, but ignored weather forecasting.

Weather forecasting presents a challenge for the method because of the presence of waves and advection. An important question is to examine how the traditional way to accelerate models with the semi-implicit semi-Lagrangian methodology can be advantageously blended with the Parareal approach.

9 October 14:15

LT

Seasonal forecasting of meteorological droughts

Emanuel Dutra. ECMWF

### Abstract

Vast parts of Africa rely mainly on the rainy season for livestock and agriculture. Droughts can have a severe impact in these areas which often have a very low resilience and limited capabilities to mitigate their effects. The predictive capabilities of an integrated meteorological drought monitoring and forecasting system based on the Standard precipitation index (SPI) are investigated. The system is firstly constructed by temporally extending near-real time precipitation fields with forecasted fields as provided by the ECMWF seasonal forecasting system and then is evaluated over four basins in Africa: the Blue Nile, Limpopo, Upper Niger, and Upper Zambezi.

This skill and reliability depends strongly on the SPI time-scale, and more skill is observed at larger time-scales. The ECMWF seasonal forecasts have predictive skill which is higher than using climatology for most regions. Poor quality precipitation monitoring products can reduce the potential skill of SPI seasonal forecasts in two to four months lead time.

10 October 10:30

MR2

The Science and Practice of Operational River Forecasting Systems: Lessons Learned from a World Tour

Tom Pagano (CSIRO)

### Abstract

Operational river forecasts have been long produced to support water resources management, covering a range of timescales from flash flooding (e.g. minutes to hours ahead) to seasonal (e.g.months ahead). They are generated by a range of statistical (e.g. regression-based) and dynamical (e.g. rainfall-runoff) model based techniques.

The extent of human control over the forecasts, such as by adjusting model inputs and outputs, varies from nearly completely automated systems to those where forecasts are generated after discussion among a group of experts. Historical and real time data availability, the complexity of hydrologic processes, forecast user needs, and forecasting institution support/resource availability (e.g. computing power, money for model maintenance) influence the character and effectiveness of operational forecasting systems. Although it is an active research topic, nearly all operational forecasting systems struggle to make quantitative use of Numerical Weather Prediction model-based precipitation forecasts.

Similarly, global-scale and spatially distributed hydrologic information, informed by remotely sensed measurements (e.g. radar and satellite) are available experimentally but suffer from biases and other limitations. Forecast uncertainty is commonly estimated operationally by using an ensemble of future precipitation scenarios and/or a measure of historical model error. However, probabilistic forecast communication and use remains a stumbling block for many. The flexibility of the water manager’s operating procedures and the size of the reservoir relative to incoming streamflow determine the relevance of forecasts to hydropower operations; moderately-sized reservoirs that can draw down in anticipation of high flows or slow releases in anticipation of drought stand to benefit the most.

11 October 14:15

LT

Using ECMWF long range forecast for health applications: The prototype Malaria Early Warning System of ECMWF and ICTP (MEWS)

F. Di Giuseppe, ECMWF

### Abstract

Temperatures determine the life cycle development rates of mosquitos that spread malaria and the malaria parasite itself.

Rainfall is required for the mosquito larvae. Skilful malaria predictions thus require skilful climate predictions weeks to months ahead, to drive malaria models that incorporate both climate and non-climate factors such as population density and migration, host immunity, treatment and interventions.

In the last years ECMWF have developed a latest generation of the monthly and seasonal forecast system that has predictive skill in the tropic weeks ahead. Building of these new tools a new seamless prediction system which concatenates bias corrected outputs from the monthly and seasonal forecasts has therefore been developed for the purposes of driving sectoral applications. ICTP has developed the VECTRI dynamical malaria model that accounts for climate, surface hydrology and population.

Within the framework of the EU-FTP7 projects QWECI, ECMWF and ICTP are working with partners in the Ministry of Health in Malawi and Uganda to evaluate and validate the MEWS for past outbreaks in highlands areas, before rolling out the pilot MEWS system.

A description of the prototype Malaria Early Warning System of ECMWF and ICTP (MEWS) along with a preliminary performance evaluation is presented.

25 October 10:30

Classroom

Soil moisture validation activities at ECMWF

Clement Albergel

### Abstract

After a brief overview of the different available soil moisture products, the validation methodology is presented. Then in situ soil moisture measurements for more than 200 stations from five networks across the world (USA, France, Spain, China and Australia) are used to determine the reliability of three soil moisture products:

1. a revised version of ERA-Interim reanalysis from ECMWF
2. a revised version of MERRA reanalysis from NASA-GMAO and
3. a new multi-satellite surface soil moisture dataset for 2007–2010.

Also, global trends in soil moisture from the revised versions of ERA-Interim and MERRA were analysed for the period 1988–2010.

26 October 10:30

Classroom

A comparison of 4D-Var and an Ensemble Kalman Filter method (LETKF) for assimilation of surface pressure observations

Pau Escribà, AEMET and ECMWF

### Abstract

ECMWF has recently developed an Ensemble Kalman Filter (EnKF) for experimental purposes. This enables us to do a fairly clean comparison of 4D-Var and EnKF, and to compare background error estimates from the Ensemble of Data Assimilations (EDA) and EnKF. One of the configurations implemented is the Local Ensemble Transform Kalman Filter (LETKF). Several methods for additive and multiplicative inflation and localization of observations have been implemented. Because of the assumption about linearity in the LETKF equations, a six hours assimilation window is used to ensure that the background ensemble propagation is reasonably linear.

In this seminar five of the analysis systems available at ECMWF are compared for assimilations that only use surface pressure observations. This has relevance for the on-going ECMWF 1900-2010 reanalysis among other activities. It also provides a more stringent test of the quality of background error estimates. The five methods are LETKF, 4DVAR with static background error using 12-hour and 24-hour assimilation windows, hybrid 4DVAR-EDA, and hybrid 4DVAR-LETKF. The comparison looks at the quality of the five analysis states, taking as the truth the operational 4DVAR analysis that runs at ECMWF with the full observing system.

Initial results for a Kalman Smoother LETKF extension will be presented. This technique recomputes the analysis at one assimilation on cycle by using the weights computed in the next cycle. Using the Kalman Smoother LETKF assimilation method allows the analysis to benefit from observations in the subsequent 6 hours, in a way so the assumption about linearity is respected.

Using only surface pressure data in the assimilation, along with the fact that the IFS forecast model used is the same for all the analysis schemes, ensures a quite clean comparison between LETKF and the variational techniques. This avoids the problems related to localisation for satellite radiances which is still an issue for EnKF systems.

This work was performed during a six month period in 2012 when Pau was a visiting scientist in the Research Department. The work was done in collaboration with Massimo Bonavita, Mats Hamrud, Lars Isaksen and Paul Poli.

31 October 10:30

MR1

Water resources in France : reanalysis, trends, seasonal forecasting and climate projections

Jean-Philippe Vidal, Irstea, formerly CEMAGREF

### Abstract

This talk will present the outputs from a set of recent research projects related to the assessment of water resources, droughts and low flows in France. First, past trends in low flow characteristics for a benchmark network of stations have been studied and linked to large-scale climate indices: NAO, AMO, and weather types. Second, a seasonal predictability study has been set up over the whole of France in order to assess the potential for forecasting soil moisture and river flows in spring and summer with the Safran-Isba-Modcou (SIM) hydrometeorological suite. Third, a spatio-temporal reanalysis and characterisation of meteorological, agricultural and hydrological droughts in France over the last 50 years has been performed with the same SIM suite. The evolution of such spatio-temporal characteristics under downscaled climate projections has then been studied, by considering a range of emissions scenarios and theoretical adaptation scenarios. Some research outlook linked to the R2D2 project, a fully integrated global change project focused on the Durance catchment (Southern Alps), will close the talk.

12 November 14:00

LT

Impact of various observing systems on NWP

### Abstract

The 5th WMO workshop on the impact of various observing systems on NWP was held 22-25 May 2012 in Sedona, Arizona. The WMO expert team on the evolution of the Global Observing System (ET-EGOS) had proposed topics for impact studies and participants were encouraged to present results on those topics in particular. The workshop was attended by 59 experts on data assimilation and observation impact, representatives from space agencies and managers of observing networks from 13 countries. Several of the global NWP centres presented detailed assessments of the impact on forecast skill of the main meteorological observing systems. In this talk I will present the main results and what they mean in terms of recommendations to WMO, space agencies and other data producers.

14 November 10:30

LT

A novel variable resolution global spectral method on the sphere

Dr S. Janakiraman, Centre for Development of Advanced Computing, (C-DAC), Bangalore, India

15 November 10:30

Classroom

Externalization of observation screening tasks within the context of the COPE project

Tomas Kral

### Abstract

Presently, most of the observation screening tasks, including quality control, observation error assignment and redundancy checks, are executed in the time critical path of the first IFS trajectory run. In this talk we will describe a new observation processing system developed within the context of the COPE project and explain its benefits for the future observation related applications. It will be discussed how these changes will simplify the design and coding of observation related software in ECMWF's assimilation system.

16 November 10:30

MR1

Australia's water information initiative and achievements to date

Dr Dasarath (Jaya) Jayasuriya, A/g Deputy Director Climate and Water Bureau of Meteorology, Melbourne, Australia

### Abstract

To address the threat of future water scarcity, the Australian Government in 2007 decided to invest $12.9 billion in Water for Future, a 10-year plan to secure long-term water supply to all Australians. The plan will help secure water supplies for Australian households, businesses and farmers, and provide water to restore the health of Australia’s stressed river systems. Through the Commonwealth Water Act 2007, the Australian Government has given the Bureau of Meteorology responsibility for compiling and delivering comprehensive water information across the water sector. As part of Water for the Future, the Bureau has been allocated$450 million to administer the Improving Water Information Program. To achieve this, the Bureau is working with water managers across Australia to deliver high quality, national water information to government, industry and the community. The Bureau will deliver a range of products designed to meet the needs of users engaged in emergency services, water policy development, planning, operations, public enquiry, education and research including:

• Flood warnings and forecasts
• Annual national water resources assessments
• An annual National Water Account
• Real-time water reporting services
• Real-time and extended water availability forecasts; and

Improved accessibility, integration and use of national water resources information will yield huge benefits. The integration of data sets, their improved quality and currency, and the introduction of new reporting, analysis and forecasting products and services will lead to more informed policy and infrastructure decisions. They will also enable evaluation of water sector reforms, leading to greater confidence in Australia’s water management.

Dr Jayasuriya will be introducing the Bureau’s Water Information Initiative and sharing outcomes to date with the Audience. He will conclude the presentation by sharing future challenges and the approach adopted by the Bureau to meet these head-on.

22 November 15:30

LT

Challenges in designing a multi-purpose Nonhydrostatic Unified Model of the Atmosphere (NUMA)

Francis Giraldo, Department of Applied Mathematics Naval Postgraduate School, Monterey, US

### Abstract

In this talk, I would like to discuss the challenges faced by operational centers in designing unified regional/global atmospheric models. In particular, I will describe the numerical methods that our model relies on which include: high order continuous and discontinuous Galerkin methods, implicit-explicit time-integrators, iterative solvers,pre-conditioners, and adaptive mesh refinement.

I would like to discuss the pros and cons of each of these methods and explain why we have selected these methods to build a new model. I will end a talk with a timeline for the model that is currently under development.

For details please visit the project website.

26 November 14:00

LT

Predicting high-impact weather based on the COSMO-DE ensemble prediction system

Dr Petra Friederichs, University of Bonn

### Abstract

Extremes in weather such as high wind speeds or heavy precipitation are associated with high impacts on both environment and society. It is thus of great importance to improve the quality of extreme wind and heavy precipitation forecasts. Numerical weather forecast models provide information about the general conditions in which extremes occur. However, strength, timing and location of such extremes are determined by small scale processes that are not, or only partly, resolved even by high-resolution weather forecast models. Thus, probabilistic prediction is likely to be the best choice of forecasting high-impact weather.

The study uses a mesoscale ensemble prediction system based on COSMO-DE (COSMO-DE-EPS) operated by the German Meteorological Service. The sources of uncertainty and predictability-initial and boundary conditions, and physical parameterizations-within the COSMO-DE-EPS are investigated, and the influence of the uncertainty components on the predictive performance is assessed including a scale dependent spread analysis.

We will present ensemble postprocessing that provides area-wide forecasts of extreme wind and heavy precipitation. We show that fairly simple postprocessing for precipitation provides considerable improvement of the predictive performance. Finally, a spatial Bayesian postprocessing for wind gusts is presented that employs extreme value theory and aims at providing a complete spatial statistical model for the wind gust process.

5 December 10:30

LT

Satellite observations of dust and their assimilation at the Met Office

Dr Bruce Ingleby, UK MetOffice, Exeter

### Abstract

At the Met Office mineral dust has been included in the operational global forecast model for just over a year-but without any assimilation. We have been testing a system in which Aerosol Optical Depth (AOD) values are obtained from two satellites and assimilated. Retrievals from the SEVIRI instrument on Meteosat Second Generation (MSG) are performed at the Met Office using a method proposed by Brindley and Russell. Retrievals from the MODIS instrument on the Aqua satellite are obtained from GSFC (USA). Only daytime AOD values over land are currently assimilated. An early assimilation experiment omitted low AOD values on the basis that other aerosols might make up a large fraction of the AOD-however this was found to give a high bias to the analysis values, it is better to use most of the SEVIRI AOD values over Africa. We have also modified different aspects of the background error estimates.

Overall the results of data assimilation trials show an improved short range fit to satellite AOD and to the sparse AERONET network-by day five of the forecast the benefit has largely disappeared. Operational implementation is planned for March 2013. The results and the major issues will be discussed as will future development options.

10 December 10:30

LT

Stochastic processors for modelling weather and climate

Dr Peter Dueben, Dept of Physics, Univ Oxford

### Abstract

Today’s processors are designed to calculate all operations exactly. If we can tolerate errors of processors it is possible to increase the performance and reduce the power consumption of a given processor significantly. The use of faulty, or stochastic processors, could therefore bring us closer towards global cloud resolving models in weather and climate science.

To explore the use of stochastic processors we emulate processor errors in numerical simulations of toy models, such as Lorenz63, but also in a spectral dynamical core (IGCM). Since a spectral core allows scale separation between large and small scales, we apply the stochastic processors to the small scales that possess inherent uncertainty due to insufficient resolution and parametrization, while we calculate the crucially important large scales on exact processors. Results are promising.

19 December 11:00

LT

A new formulation of the spectral energy budget of the atmosphere with application to two high-resolution general circulation models

Erik  Lindborg (Department of Mechanics - KTH, Stockholm, Sweden)

### Abstract

A new formulation of the spectral energy budget of kinetic and available potential energies of the atmosphere is derived, with spherical harmonics as base functions. Compared to previous formulations, there are three main improvements:

1. the topography is taken into account,
2. the exact three-dimensional advection terms are considered and
3. the vertical flux is separated from the energy transfer between different spherical harmonics.

Using this formulation, results from two different high resolution GCMs are analyzed: the AFES T639L24 and the ECMWF IFS T1279L91. The spectral fluxes show that the AFES, which reproduces realistic horizontal spectra with a k^{-5/3} inertial range at the mesoscales, simulates a strong downscale energy cascade. In contrast, neither the k^{-5/3} vertically integrated spectra nor the downscale energy cascade are produced by the ECMWF IFS.

## 2011

16 February 10:30

LT

Land Surface Analysis at ECMWF: soil moisture and snow, some evaluations

Clement Albergel

22 February 10:30

LT

Does higher resolution provide more accurate forecasts?

Nigel Roberts, Met Office, JCMM, Reading

### Abstract

The Met Office now routinely runs a Numerical Weather Prediction models with a grid spacings of 4 and 1.5km. At these 'storm-permitting' resolutions convective showers can be explicitly represented on the model grid and there is also the capability to represent small-scale meteorological features such as local convergence lines, narrow frontal rainbands and valley fog.

The forecasts from the 1.5km (UKV) model in particular, are astonishingly realistic, but are they accurate? There are certainly high expectations along with increased computational cost.

This talk will examine whether increased resolution produces more skilful forecasts and consider how this determines the way we should present the output (at all resolutions).

3 March 14:00

LT

Phase 2 of the IBM HPCF (POWER7)

Isabella Weger

### Abstract

Phase 2 of the IBM HPCF contract, based on POWER7 technology, will be installed in 2011. A performance upgrade in mid 2012 is part of a contract extension until mid 2014 which was concluded with IBM in late 2010.

The presentation will give an overview over the new POWER7 system, outlining system configuration, technical specifications and time lines for implementation of the Phase 2 system.

4 March 10:30

LT

An investigation of systematic model error using a quasi-geostrophic weak-constraint 4D-Var system

Harri Auvinen

### Abstract

Even the most sophisticated numerical weather prediction model is not perfect. Although some errors may be entirely random, many will result from systematic misspecification of parameters, or deficiencies in parametrizations. In this work we estimate the covariance structure of systematic error a quasi-geostrophic (QG) model using the OOPS assimilation framework. We use this estimate in a Long-Window Weak-Constraint 4d-Var analysis system, and demonstrate that method is successful in taking model error into account.

10 March 15:30

LT

Scalable elliptic solvers and their application in numerical weather prediction

Robert Scheichl, University of Bath

### Abstract

Large ill-conditioned elliptic systems are at the heart of applications in many areas of science and engineering where diffusive processes are important. Due to the global nature of the solution operator, any iterative solver that scales efficiently to large problem sizes needs to incorporate not only local but also global exchange of information. Multilevel iterative solvers provide such a global exchange (at a negligible cost), by using a hierarchy of auxiliary problems of lower spatial resolution. However, the robust construction of such a hierarchy in the context of strong anisotropies and/or coefficient variations requires some care and insight. In this talk I will give an introduction to multilevel iterative solvers for elliptic problems and discuss robustness issues, as well as their application in meteorology.

4 March 10:30

LT

An investigation of systematic model error using a quasi-geostrophic weak-constraint 4D-Var system

Harri Auvinen

### Abstract

Even the most sophisticated numerical weather prediction model is not perfect. Although some errors may be entirely random, many will result from systematic misspecification of parameters, or deficiencies in parametrizations. In this work we estimate the covariance structure of systematic error a quasi-geostrophic (QG) model using the OOPS assimilation framework. We use this estimate in a Long-Window Weak-Constraint 4d-Var analysis system, and demonstrate that method is successful in taking model error into account.

10 March 15:30

LT

Scalable elliptic solvers and their application in numerical weather prediction

Robert Scheichl, University of Bath

### Abstract

Large ill-conditioned elliptic systems are at the heart of applications in many areas of science and engineering where diffusive processes are important. Due to the global nature of the solution operator, any iterative solver that scales efficiently to large problem sizes needs to incorporate not only local but also global exchange of information. Multilevel iterative solvers provide such a global exchange (at a negligible cost), by using a hierarchy of auxiliary problems of lower spatial resolution. However, the robust construction of such a hierarchy in the context of strong anisotropies and/or coefficient variations requires some care and insight. In this talk I will give an introduction to multilevel iterative solvers for elliptic problems and discuss robustness issues, as well as their application in meteorology.

24 March 10:30

LT

Observation Impact Diagnostic: Use of Observation Influence and Forecast Sensitivity Tools (OI and FSO)

Carla Cardinali

This seminar intends to illustrate the use of the sensitivity tools developed. In particular:

• how to compute OI in the analysis experiment
• how to run  FSO
• use of OBSTAT to display the observation impact in the analysis and forecast

6 April 10:30

LT

The Angular Momentum Paradox - Understanding the general circulation of the atmosphere from Halley and Hadley to Held and Huo

### Abstract

George Hadley's erroneous but popular 1735 explanation of the Trade Winds, based on conservation of absolute velocity, yields far too strong winds, which has always been explained away by the effects of "friction". When the correct principle of conservation of angular momentum was applied from the 1880's it turned out that the excessive winds doubled in strength. This "Angular Momentum Paradox" has marred meteorology since then and attempts to explain it away by invoking even more "friction", for example by Held, Hou and Lindzen, has not been quite convincing. The seminar will suggest that there is no "paradox" at all and that the dynamics of the general circulation of the atmosphere can be understood as easily (?) as the dynamics of the solar system.

14 April 10:30

LT

Tropical cyclogenesis

Roger Smith and Michael Montgomery, Meteorological Institute, University Munich, Germany

10 May 10:30

LT

The Surface Water Ocean Topography satellite mission: prospects for climatology and hydrology science

Prof. Paul Bates, Bristol University

### Abstract

In 2019 NASA and CNES will launch the Surface Water Ocean Topography satellite mission (see swot.jpl.nasa.gov) which will measure surface water height to centimetric accuracy every 10 days with complete global coverage at 1km resolution over the oceans and for all rivers above 100m wide. Over oceans, current altimeter constellations can only resolve the ocean circulation at resolutions larger than 300 km. Fundamental questions on the dynamics of ocean variability at scales shorter than 300 km, the mesoscale and submesocale processes, such as the formation, evolution, and dissipation of eddy variability (including narrow currents, fronts, and quasi-geostrophic turbulence) and its role in air-sea interaction, are to be addressed by the new observations. Over land the SWOT mission will provide measurements of water storage changes in terrestrial surface water bodies and will provide estimates of discharge in large (50 m-100 m width) rivers, globally. These data sets will provide a quantum improvement on our current understanding of surface water dynamics. Beyond improved characterization of the water cycle, meeting these measurements will enable numerous applications of great scientific, social, and political importance.

25 May 10:30

LT

The new "User Guide to ECMWF forecast products"

### Abstract

Abstract: Since 1988 the ECMWF has provided a "User Guide" for users interested in an overview of our forecast system, forecast products and how to make best use of them. The 2011 edition is thoroughly revised and the main topics will be presented:

1. In the introduction users are recommended not to try to compete with the computer but do the  o p p o s i t e : not be detailed, avoid forecast "jumpiness" and, above all, make use of uncertainty.
2. When presented the forecast and data assimilations system users tend to be more interested in the deficiencies of the system rather than to be reminded how good it is. The same applies to the EPS.
3. The use of the deterministic and probabilistic products on their own and in combination. To what degree are the users able to modify the output?
4. A know-how of verification and validation methods and, above all, their interpretation, is important not only for specialists, but also for NWP modellers and operational forecasters.
5. In an Epilogue recommendations are made in an attempt to narrow the gap between mathematical-scientific rigour of NWP modelling with the empirical-intuitive practises of operational forecasting.

2 June 10:30

LT

A new method for estimating analysis and forecast error variance

Zoltan Toth, GSD/ESRL/OAR/NOAA, Boulder, CO. and Malaquias Pena, EMC/NCEP/NWS/NOAA

### Abstract

Accurate estimates of error variances in numerical analyses and forecasts are critical for the evaluation of forecasting systems, the tuning of data assimilation systems, and the proper initialization of ensemble forecasts. A number of issues, however, hinder related efforts. A new approach is introduced for the unbiased estimation of analysis and forecast errors. The method is independent of any assumption or tuning parameter used in data assimilation schemes. In a functional analysis, it combines information from differences between forecast and analysis fields (“perceived errors”) with prior knowledge regarding the time evolution of (a) forecast error variance and (b) correlation between errors in analyses and different lead-time forecasts. In a simulated forecast environment, the method is demonstrated to reproduce the true analysis and forecast error within the predicted error bounds. The method is then applied to forecasts from four leading Numerical Weather Prediction centers to assess the performance of their corresponding data assimilation and modeling systems.

7 June 09:15

Classroom

Observation Handling and Monitoring Tutorial

Drasko Vasiljevic, Anne Fouilloux, Manuel Fuentes, Peter Kuchta, Mohamed Dahoui and Sandor Kertesz

5 July 10:30

Classroom

On a Gain Initialization and Optimization of Adaptive Filter by Simultaneous Perturbation Stochastic Approximation

Hong Son Hoang, Service Hydrographique et Oceanographique de la Marine, Toulouse

### Abstract

Initialization of the filter gain plays an important role to provide a high performance of the filter. In this work, it is shown that the error covariance matrix (ECM) of the prediction error can be well estimated using simulated samples of the dominant Schur vectors of the system dynamics. This allows to well initialize the filter gain. By an appropriate parametrization, the adaptation can be applied to minimize the prediction error of the system output. It will be demonstrated that one efficient tool to optimize the performance of an AF is the simultaneous perturbation stochastic approximation (SPSA) algorithm. The main results show that the SPSA is capable of yielding the high filter performance similar to that produced by classical optimization algorithms, with better performance for non-linear filtering problems as more and observations are assimilated. The advantage of the SPSA is that at each iteration it requires only two measurements of the objective function to approximate the gradient vector regardless of the dimension of the control vector. The SPSA approach is thus free from the need to develop a discrete adjoint of tangent linear model and offers promising perspectives on developing optimal assimilation systems encountered in the field of data assimilation in meteorology and oceanography. Numerical results on data assimilation based on MICOM and HYCOM ocean models, in academic and realistic configurations, will be given to show the efficiency of the proposed filter.

7 July 10:30

LT

Use of ensemble forecasts in predicting the supply and demand of European energy

Warwick Norton, Cumulus Funds PCE Investors, London

### Abstract

The use of ECMWF ensemble forecasts is illustrated from the perspective of an end user who is a risk taker in the European energy market. This involves not only forecasting temperatures which drives consumption of energy, but the growing renewables sector means there is also large weather sensitivity in the supply of energy. This includes forecasting wind, surface solar radiation, precipitation and runoff. In order to calculate future energy prices, it is necessary to have an evolving view, at daily resolution, of these weather variables. This is accomplished by combining medium range forecasts with monthly forecasts and then with reanalysis data. However decision making using ensemble forecasts is not always straightforward because of the day-to-day changes in the forecasts. Some issues in forecasting these variables is discussed as well as the general performance of the EPS system over recent months.

13 July 9:15

LT

Training sessions on C++ object oriented programming techniques:  Effective Advanced C++

Michael Wong, IBM

### Abstract

This course will focus on effective C++ design based on the last 20 years of collective wisdom of C++ gurus worldwide. It will discuss coding guidelines, as well as how C++ is implemented under the cover to help truly understand what features costs. Topics of interest will include how language features are implemented by the C++ compiler, understanding inlining, code bloat, interface-based programming, and dynamic memory management.

13 July 9:15

LT

Training sessions on C++ object oriented programming techniques: Trends and futures of C++

Michael Wong, IBM

### Abstract

Over the last decades, C++ has become one of the most widely used languages supporting object-oriented programming by making abstraction techniques affordable and manageable for mainstream projects. Using C++ as his tool, Prof. Bjarne Stroustrup pioneered the use of object-oriented and generic programming techniques in application areas where efficiency is a premium; examples include general systems programming, switching, simulation, graphics, user-interfaces, embedded systems, and scientific computation. The influence of C++ and the ideas it popularized are clearly visible far beyond the C++ community. Languages including C, C#, Java, and Fortran99 provide features pioneered for mainstream use by C++.

C++ is a general purpose programming language with a bias towards systems programming which supports multiple styles of programming. Since 1998 C++ is an ISO standard. In these days a new version of the language is about to become a new ISO standard. This seminar will start by introducing the new features of the language and showing the challenges of evolving an existing programming language with a huge code base. This will enable students to truly come to understand C++ and the foundation of its design. We will cover some language concepts but also expand to describe aspects of STL, Boost and C++0x, the next version of C++.

19 July 14:00

MR1

Impact of the European Russia drought in 2010 on the Caspian Sea Level

Klaus Arpe

### Abstract

The Caspian Sea (CS) basin has no outlet to the oceans. The inflow from rivers, mainly the Volga River is compensated by evaporation over the Caspian Sea itself, imbalances lead to changes in the CS Level (CSL). It is therefore an ideal test area for investigating the water budget of an area using a variety of observational and reanalysis data. The period 1993 to 2010 was investigated with emphasis on summer 2010 when a severe drought developed over European Russia, the catchment of the Volga River. Precipitation and evaporation from the ECMWF interim analysis are compared with Volga River discharge and the CSL observations.

A drop in precipitation over the Volga basin (VB) in July 2010 occurs simultaneously with a decrease in evaporation for the same area, an increase of evaporation over the CS itself and a drop of the CSL. The drop in the precipitation over the VB cannot have led to an instantaneous drop of the CSL because the precipitated water needs some months to reach the CS. However, the evaporation over the CS itself is considered to be responsible for a simultaneous drop of the CSL in July to September 2010. The impact on the CSL from the precipitation deficit over the VB occurs in the months following the drought. The water deficit for June to September 2010 calculated from the anomalous precipitation minus evaporation over the VB would decrease the CSL by 22 cm, of which only 2.5 cm had been observed until end of September (observed Volga River discharge anomaly), 7 cm from October to the end of 2010 and another 5 cm to the end of May 2011. The remaining 7 cm may be compensated by excessive precipitation from October to February. In previous studies the precipitation over the VB has been identified as the main cause for CSL changes, but here a 10 cm drop from beginning of July to end of September can be directly assigned to the enhanced evaporation over the CS itself (6 cm) and due to reduced precipitation over the CS (2cm).
Further periods with strong changes of the CSL are investigated as well which provide some estimates concerning the accuracy of the data.
The consistency between the different components of the water budget over the Caspian Sea basin based on independent data gives a high confidence in the quality of the ERA interim data.

This investigation provides some scope for making forecasts of the CSL few months ahead to allow for mitigating societal impacts.

20 July 10:30

Classroom

Decadal climate variability and change in the Mediterranean region

Annarita Mariotti, NOAA, USA

### Abstract

The Mediterranean region is among the “Hot Spots”  projected to experience major climatic changes in the twenty-first century as a result of the global increase in greenhouse gas (GHG) concentrations. However  the way in which these changes may initially become manifest in the Mediterranean will also depend on internal decadal variability and its impacts on climate in this region.  Here, we present an analysis of the main decadal climate variations that have influenced past climatic conditions in the Mediterranean/South Europe region since the mid-nineteenth century. Decadal variability is discussed in the context of forced climatic changes from increased GHG. Results point to significant connections between Mediterranean climate and decadal and multi-decadal variability in the Atlantic. Namely, a significant influence of the North Atlantic Oscillation on Mediterranean precipitation and a relationship between regional temperatures and the Atlantic Multi-decadal Oscillation which may imply a certain degree of decadal regional predictability. CMIP3 projections indicate that in the longer term “forced” regional climatic changes from GHG increases would bring significantly drier conditions over land and major changes in Mediterranean Sea water cycle.

5 September 15:30

LT

Variational data assimilation without nonlinear models

Roel Stappers and Jan Barkmeijer, KNMI

### Abstract

The use of tangent linear and, in particular, adjoint models has been very useful in several applications in numerical weather prediction. For example, at ECMWF these linear models play a crucial role in the computation of initial condition perturbations used in the ensemble prediction system and in their 4D-VAR data assimilation system. The greatest limitation to the application of linear models is that the results are useful only when the linear approximation is valid. As a result the usage of tangent linear and adjoint models is restricted to 'short' time spans.

In this presentation we show that by linearizing the tangent linear model around an ensemble of trajectories the nonlinear growth of perturbations can be described exactly by the tangent linear model. We show that in a three level quasi geostrophic model the tangent linear model can be used for more than 200 days (with increments much larger than typical analysis increments, using only a single linearization trajectory).

Based on this result we introduce a new incremental 4D-VAR method that

1. Does not require the nonlinear model to update the linearization trajectory in the outer loops (these updates are responsible for a significant fraction of the computational cost in the current ECMWF implementation).
2. Does not modify the innovation vector in the outer loops. To demonstrate the advantage of this we derive the exact equations for adjoint based observation impact including the effect of using multiple outer loops in 4D-VAR.
3. Does not require the strict distinction between inner/outer loops. The linearization trajectory can be updated in the inner loops at no additional computational cost.

28 September 10:30

LT

Need for Caution in Interpreting Extreme Weather Statistics

Prashant. D. Sardeshmukh, University of Colorado, Boulder and NOAA

11 November 10:30

MR1

Earth's Radiation Imbalance from a Constellation of 66 Iridium Satellites

Warren Wiscombe, NASA Goddard

### Abstract

Because of the "global warming hiatus" since the 1998 El Nino, and because of the deployment of the Argo float array, a new view of climate change is becoming possible that is more fundamental than surface air temperature.  That view is based on two variables:  the rate of change of ocean heat content;  and Earth radiation imbalance (ERI) at the top of the atmosphere.  The two are tightly related.  Argo takes care of the first requirement, especially since 2007 or 2008 when the major bugs were fixed.  But we have no measurement of ERI.  The existing CERES system cannot measure ERI to even one significant digit.

This talk will overview a proposed constellation of 66 Earth radiation budget instruments, hosted on Iridium satellites, that has been proposed to NASA.  This system represents a quantum leap over CERES in providing ERI to at least one significant digit, thus enabling a crucial test of climate models, and furthermore in providing ERI at three-hourly time scales without suspicious extrapolations from narrowband geostationary instruments.  This would make ERI into a synoptic variable like temperature, and allow studies of ERI's response to fast-evolving phenomena like dust storms and hurricanes -- studies which are impossible in the CERES world of monthly averages.

17 November 10:30

LT

WATCH and WaterMIP Global Hydrological Models: inter-model comparison for hydrological extremes of Europe

Christel Prudhomme and Tanya Warnaars, Centre for Ecology & Hydrology

### Abstract

Within the WATCH project, a new methodology for assessing the ability of gridded global hydrological models (GHM) to reproduce large-scale hydrological high and low flow events (as a proxy for hydrological extremes) was developed and applied in Europe. It was first applied to develop a European catalogues of historical droughts (using the Regional Deficiency Index, RDI) and high flows (Regional High Flow Index, RHFI) previously derived from river flow measurements across Europe.  Using the same methods, total runoff simulated by seven global hydrological models from WaterMIP run with the same meteorological input (Watch Forcing Data) at the same spatial 0.5º grid was used to calculate simulated RDI and RHFI for the period 1963-2001 in the same European regions, directly comparable with the observed catalogues.  Results show that GHMs can broadly reproduce the spatio-temporal evolution of hydrological extremes in Europe to varying degrees, but the length and strength of the spatial coherence of events can vary significantly between GHMs.  The same method was also applied to total runoff generated using GCM driving climate for both baseline and future time slices. Results then show that GHMs have different sensitivity to the climate, and that GHM uncertainty can be as large (or larger for some regions) than climate model (GCM) uncertainty. Overall, the study has demonstrated that RDI and RHFI are powerful tools which can be used to assess how well large-scale hydrological models reproduce large-scale hydrological extremes - an exercise rarely undertaken in model inter-comparisons. It also showed that global hydrological model uncertainty can be large and should be accounted for hydrological extreme simulation and climate change impact assessments.

21 November 15:00

LT

The Regional Integrated Multi-Hazard Early Warning System for Africa and Asia (RIMES): The Third Way

Peter Webster and Subbiah Arjunapermal, School of Earth and Atmospheric Sciences, Georgia Tech

22 November 15:30

LT

A new layout for the Daily Report?

### Abstract

The layout of the Met Ops Section's Daily Report has not changed significantly since its introduction in 1992. A suggestion for a new layout will be presented where the contents is organized in five parts. The first and the last (Operational status and Additional comments) will remain. The other three will address "NOW", "FUTURE" and "HISTORY" i.e. all problems with the definition of the initial state, the forecast performance and verifications (both for the deterministic and ensemble system, including e-suites). When deciding on the new layout we need feedback from the RD-staff about which parameters or problems they think the Daily Report should focus on. A preliminary version will be tested 7-11 November.

13 December 14:00

LT

Reflections on the past 25 years - and some speculations on the next

Tim Palmer, ECMWF and University Oxford

21 December 15:30

LT

Sound-proof simulations of atmospheric wave phenomena

Piotr K. Smolarkiewicz, NCAR, Boulder, CO

### Abstract

We investigate the performance of several sound-proof models, including the anelastic Lipps-Hemler and the pseudo-incompressible Durran nonhydrostatic equations. Physics wise, our primary interests are with the dynamics of inertia-gravity waves, an important element of weather and climate. Our numerical developments are based on a class of non-oscillatory forward-in-time methods and are applicable to global and limited area models. Challenging simulations of atmospheric wave phenomena involve structured-grid and unstructured-mesh discretizations.