Seminars / Informal seminars / Lectures by ECMWF Staff and Invited Lecturers

Seminars contribute to our ongoing educational programme and are tailored to the interests of the ECMWF scientific community.

Informal seminars are held throughout the year on a range of topics. Seminars vary in their duration, depending on the area covered, and are given by subject specialists. As with the annual seminar, this may be an ECMWF staff member or an invited lecturer.

The following is a listing of seminars/lectures that have been given this year on topics of interest to the ECMWF scientific community.  See also our past informal seminars


25 July
at 10:30

Room: LT

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

Speaker: Paul Dirmeyer (COLA, USA)


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.

23 July
 at 10:30

Room: LT

JAXA precipitation radars

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


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 constrain microphysical 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 the ECMWF.

19 July
at 14:00

Room: MR1

Model biases and seasonal forecasting

Speaker: Tim Woollings (Oxford University)


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.

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)


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.

2 July
at 13:30

Room: LT

Ocean data assimilation challenges for both reanalysis and regional operational applications

Speaker: Andrea Storto (CMRE, Italy)


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.

20 June
at 10:30

Room: LT

A turbulence scheme with two prognostic turbulence energies

Speaker: Ivan Bastak Duran (Goethe University, Frankfurt)


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.

24 May
at 13:30

Room: LT

Possible future ensemble configurations

Speakers: M Leutbecher and F Vitart (ECMWF)


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.

12 April
at 10:30

Room: LT

Radiosondes and NWP

Speaker: Bruce Ingleby (ECMWF)


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.

10 April
at 10:30

Room: Council

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

Speaker: Andrew Gettelman (NCAR)


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.

6 April
at 11:00

Room: MR1

Towards seamless water forecasting in Australia

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


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 (; A new service for streamflow, sediment and pollutant fluxes to the Great Barrier Reef is currently under development (

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.

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)


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.

20 March
at 14:00

Room: LT

On the dynamical mechanisms governing El Nino-Southern Oscillation regularity

Speaker: Judith Berner (NCAR, USA)


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 Parameterized 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.

20 March
at 10:30

Room: LT

Dynamics and predictability of sudden stratospheric warmings

Speaker: Thomas Birner (LMU)


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.

14 March
at 10:30

Room: MZ

Global Surface Observations of Air Quality

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


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.

26 February
at 11:00

Room: LT

The Joint Effort for Data assimilation Integration

Speaker: Yannick Tremolet (JCSDA, USA)


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.

22 February
at 11:00

Room: Council

Forecasting health hazards linked to heatwaves

Speaker:  Claudia di Napoli (Reading University)


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.

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)


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.

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)


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.

LT = Lecture Theatre, LCR = Large Committee Room, MZR = Mezzanine Committee Room,
CC = Council Chamber


See also - Annual seminar 2018

See also - Past Annual Seminars (under Past Workshops)

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