Seminars/Lectures by ECMWF Staff and Invited Lecturers

Date

Time and place

Details

10:30 - Lecture Theatre

THIS SEMINAR HAS BEEN CANCELLED

Dr Guoxiong Wu (LASG, Institute of Atmospheric Physics Chinese Academy of Sciences, Beijing, China)

Multi-Scale Forcing and the Formation of Subtropical Desert and Monsoon

Abstract: This study investigates three types of atmospheric forcing across the summertime subtropics that are shown to contribute in various ways to the occurrence of drought and wet climates in the subtropics. To explain the formation of desert over the western parts of continents and monsoon over the eastern parts, we propose a new mechanism of positive feedback between diabatic heating and vorticity generation that occurs via meridional advection of planetary vorticity and temperature. Monsoon and desert are demonstrated to coexist as twin features of multi-scale forcing, as follows.
First, continent-scale heating over land and cooling over ocean induce the ascent of air over the eastern parts of continents and western parts of oceans, and descent over eastern parts of oceans and western parts of continents. Second, local-scale sea-breeze forcing along coastal regions enhances air descent over eastern parts of oceans and ascent over eastern parts of continents. This leads to the formation of the well-defined summertime subtropical LOSECOD quadruplet-heating pattern across each continent and adjacent oceans, with long-wave radiative cooling (LO) over eastern parts of oceans, sensible heating (SE) over western parts of continents, condensation heating (CO) over eastern parts of continents, and double dominant heating (D: LO+CO) over western parts of oceans. Such a quadruplet heating pattern corresponds to a dry climate over the western parts of continents and a wet climate over eastern parts. Third, regional-scale orographic-uplift-heating generates poleward ascending flow to the east of orography and equatorward descending flow to the west.
The Tibetan Plateau (TP) is located over the eastern Eurasian continent. The TP-forced circulation pattern is in phase with that produced by continental-scale forcing, and the strongest monsoon and largest deserts are formed over the Afro-Eurasian Continent. In contrast, the Rockies and Andes are located over the western parts of their respective continents, and orography-induced ascent is separated from ascent due to continental-scale forcing. Accordingly, the deserts and monsoon climate over these continents are not as strongly developed as those over the Eurasian Continent.
A new mechanism of positive feedback between diabatic heating and vorticity generation, which occurs via meridional transfer of heat and planetary vorticity, is proposed as a means of explaining the formation of subtropical desert and monsoon. Strong low-level longwave radiative cooling over eastern parts of oceans and strong surface sensible heating on western parts of continents generate negative vorticity that is balanced by positive planetary vorticity advection from high latitudes. The equatorward flow generated over eastern parts of oceans produces cold sea-surface temperature and stable stratification, leading in turn to the formation of low stratus clouds and the maintenance of strong in situ longwave radiative cooling. The equatorward flow over western parts of continents carries cold, dry air, thereby enhancing local sensible heating as well as moisture release from the underlying soil. These factors result in a dry desert climate. Over the eastern parts of continents, condensation heating generates positive vorticity in the lower troposphere, which is balanced by negative planetary vorticity advection of the meridional flow from low latitudes. The flow brings warm and moist air, thereby enhancing local convective instability and condensation heating associated with rainfall. These factors produce a wet monsoonal climate. Overall, our results demonstrate that subtropical desert and monsoon coexist as a consequence of multi-scale forcing along the subtropics.
Keywords: Multi-Scale Forcing, Local Positive Feedback Mechanism, Subtropical Desert, Subtropical Monsoon

NEW DATE

9 May

NEW TIME

15:30 - Lecture Theatre

Anders Persson (SMHI)

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.

Giovanni Leoncini (Met Office)

Atmospheric predictability at the convective scale

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.

Neil Jacobs (AirDat LLC, Morrisville, NC)

Optimization and utility of TAMDAR aircraft observations for NWP

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.

Eric de Boisseson

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

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.

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

Medium-range and seasonal river forecasting in China

David Gustafsson and Jonas Olsson (SMHI)

Ensemble forecasts of spring flood in Sweden

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

Angeles Hernandez and Niels Bormann

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

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.

Mike Fisher (ECMWF)

The new Fortran coding standard for IFS

Kevin Trenberth (National Center for Atmospheric Research, Boulder)

Challenges of a sustained Climate Observing System

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.

Jean-Jacques Morcrette (ECMWF)

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

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.

Philippe Lopez (ECMWF)

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

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.

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

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

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 time scales. 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.

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

When will the Arctic become ice free?

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.

David Edwards (NCAR Earth System Laboratory, Deputy Director)

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

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

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

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.