Annual Seminar 2018
Speakers
Marc Bocquet is senior researcher and deputy director of CEREA, a joint laboratory of École des Ponts ParisTech and EdF R&D and Professor at École des Ponts ParisTech. He co-chairs the Statistics for Analysis, Modelling and Assimilation group of the Pierre-Simon Laplace Institute. He works in the field of data assimilation and inverse problems in the geosciences, as well as in environmental statistics. He develops new mathematical methods to better estimate the state of the atmosphere and the ocean, using large sets of observations and complex models. His current topics of interest are: ensemble Kalman and particle filtering, error estimation techniques, regularisation in ensemble methods, data assimilation and dynamical systems, and nonlinear sampling. Moreover, he applies these methods to dispersion and atmospheric chemical transport models, with a focus on inverse problems. He is Associate Editor for the Quarterly Journal of the Royal Meteorological Society. He teaches data assimilation in the Paris area geoscience master degree MOCIS/WAPE.
Massimo Bonavita received a Master degree in Physics from the University of Rome, Italy, in 1992; a Master degree in Meteorology from the Naval Postgraduate School in Monterey, USA, in 2001; and a PhD in Remote Sensing from the University of Rome, Italy in 2015.
He has worked as a weather forecaster and then as a NWP and Data Assimilation research scientist at the Italian Weather Service. In 2009 he joined the European Centre for Medium Range Weather Forecast (ECMWF) where he has lead the ensemble data assimilation effort. He currently leads the Data Assimilation Methodology Team of ECMWF. His current research interests include ensemble and variational data assimilation, non-linear and non-Gaussian effects in data assimilation methods and error simulation techniques.
Phil Browne trained as an applied mathematician before joining ECMWF to help develop a key aspect of operational numerical weather prediction (NWP): coupled ocean–atmosphere data assimilation. Phil’s previous position was as a postdoc at the University of Reading working on coupled assimilation into climate models using advanced particle filtering techniques.
His role at ECMWF is to use ocean assimilation developments to improve the atmospheric analyses and forecasts. Phil developed and implemented the weakly coupled ocean-atmosphere assimilation currently in operations at ECMWF by linking the ocean and atmospheric assimilation systems together. His current focus is seeking more ways of coupling the ocean and atmospheric analysis systems together into a more coherent Earth system analysis that improves the medium-range forecasts. This includes developing the outer-loop coupling analysis system to get it ready for operational numerical weather forecasting.
Since 2001, Dr. Mark Buehner has been a research scientist in the Data Assimilation and Satellite Meteorology research section of Environment and Climate Change Canada (ECCC). He is responsible for the scientific development of the global deterministic data assimilation system and led the research that resulted in replacing 4D-Var with 4D-EnVar in 2014 for both global and regional operational NWP. He is also the scientific lead for research at ECCC on sea ice data assimilation. In recent years he has performed innovative research on scale-dependent covariance localization, estimation of observation impact in 4D-EnVar, and practical approaches for ensemble data assimilation. Before joining ECCC, he conducted post-doctoral research at the Massachusetts Institute of Technology and obtained his PhD in physical oceanography from Dalhousie University in Nova Scotia, Canada.
Sarah L. Dance is Professor of Data Assimilation at the University of Reading, UK, jointly held in the Department of Mathematics & Statistics and the Department of Meteorology. She completed her PhD in the Division of Applied Mathematics at Brown University, USA in 2002, working on multiphase fluid flow. She changed field to data assimilation when she joined the University of Reading, initially working as a postdoctoral fellow. Her research focus is the development of mathematical aspects of data assimilation, working on applications in hazardous weather and flood prediction. She currently co-directs the NERC Flooding from Intense Rainfall programme and holds an EPSRC Senior Fellowship in Digital Technology for Living with Environmental Change.
Patricia de Rosnay is leading the Coupled Assimilation Team of the European Centre for Medium-Range Weather Forecasts (ECMWF). Her research activities focus on coupled Earth system assimilation and multi-variate land surface data assimilation developments. She received her Ph.D degree in climate modelling from the University Pierre et Marie Curie (France) in 1999. She worked on land surface and climate modelling at LMD/IPSL (1994-2002) and on land surface remote sensing at the Centre d'Etudes Spatiales de la Biosphère (CESBIO) until 2007. She has been at ECMWF since 2007, where she implemented a new Optimal Interpolation snow analysis and an Extended Kalman Filter soil moisture analysis in the ECMWF Integrated Forecasting System. She has been coordinating the SMOS and H-SAF activities at ECMWF, she is member of the HarmoSnow COST action, the SRNWP (Short-Range Numerical Weather Prediction Programme) surface expert team, and the WMO SnowWatch Team of the Global Cryosphere Watch programme.
Clara Draper’s research is focussed on global and continental scale applications of land data assimilation, and coupled land/atmosphere assimilation. She is a Research Scientist at NOAA ESRL PSD and University of Colorado, CIRES in Boulder, CO, where here primary focus in on the development of a coupled land/atmosphere data assimilation system for use in NOAA's operational forecasting suite. Prior to joining NOAA, she has worked at NASA GSFC GMAO, Meteo-France CNRM/GMME, and the Australian Government Bureau of Meteorology CAWCR, developing land data assimilation applications for use in reanalyses, hydrological models, and NWP.
John Eyre has worked in the field of weather satellite data since 1978. He led the Satellite Section at ECMWF from 1990 to 1995 and then the Satellite Applications Section of the Met Office from 1995 to 2014. He is now a Met Office Fellow in Satellite Applications, where he continues to work on improving the exploitation of satellite data for weather and climate applications. His personal research contributions have been mainly on infra-red and microwave radiative transfer modelling, retrieval of atmospheric temperature and composition from satellite observations, and the assimilation of remotely-sensed observations into NWP models. He devotes a significant fraction of his time to working with WMO, on the evolution of global observing systems.
Dr. Sergey Frolov is a data assimilation and coupled model forecasting expert at the US Naval Research Laboratory. Dr. Frolov has 15+ years of experience discovering, implementing, and transitioning advance computing algorithms in support of Earth Science modeling and observation workflows. Dr. Frolov’s work contributed to the negotiation of the US-Canada water sharing treaty, design of the National strategy for harmful algal observations along the US West Coast, and to the implementation of the data assimilation and the ensemble forecast component of the Navy’s seasonal-to-subseasonal forecast model. Dr. Frolov holds his Ph.D. degree in Environmental Information Technology from the Oregon Health and Science University (Portland, OR, USA), M.Sc. degree from the Central European University (Budapest, Hungary); and B.Sc. degree from the International Sakharov Environmental University (Minsk, Belarus).
Antje Inness graduated with a degree in Meteorology from the University of Bonn and then completed a PhD in Meteorology at the University in Reading on 'Quasi-horizontal water vapour transport across the dynamical tropopause'. She has been working at ECMWF since 2000, first in the
Satellite Section to monitoring and assimilate ENVISAT data and later in the EU funded GEMS and MACC projects where she set up the reactive gases data assimilation system. She is now working as Senior Scientist at ECMWF for the Copernicus Atmosphere Monitoring Service (CAMS) and is
involved in the data assimilation of atmospheric composition data for CAMS, the running of the CAMS reanalysis and preparation for the monitoring and assimilation of new data sets such as retrievals from the recently launched Sentinel-5p satellite.
Dr. Marta Janisková is currently a Senior Scientist in the Physical Processes Team of the Earth System Modelling Section at European Centre for Medium-Range Weather Forecasts (ECMWF). She received the Master degree in Meteorology and Climatology in 1987 and the PhD degree in Meteorology from the University of Paul Sabatier in Toulouse (France) in 1998. She joined ECMWF in April 1999 shortly after obtaining her PhD degree. Before joining ECMWF she worked on different NWP research studies for limited area modelling, but mainly on physical parametrization for incremental four-dimensional variational data assimilation during a number of visits at Météo-France (all together 3 years between 1993 and 1999) while being employed by the Slovak Hydrometeorological Institute in Slovakia. Her research at ECMWF is focused in particular on the development of different simplified physical parameterization schemes and their tangent-linear and adjoint versions together with an evaluation of their accuracy and usefulness for data assimilation. She also worked on and managed several projects related to an exploration of feasibility to assimilate space-borne cloud radar and lidar observations in NWP models.
Dr. Jean-François Mahfouf is head of the observation team of the Numerical Weather Prediction research division at Météo-France since 2011. He obtained a PhD in meteorology from the University of Clermont-Ferrand in 1986 and a « PhD advisor » degree from the University of Toulouse in 1994. He has 30 years of experience in the field of atmospheric numerical modelling and data assimilation. He has published more than 100 papers in peer-reviewed scientific journals. He has initiated a number of pioneering developments on land surface assimilation, and on variational assimilation of clouds and precipitation from microwave remote sensing instruments at Météo-France, ECMWF and ECCC.
Chiara Piccolo currently leads Satellite Applications research and development at the UK Met Office to improve exploitation of satellite data in numerical weather prediction and other applications in weather and climate.
Previously Chiara managed the NWP SAF (Satellite Application Facilities). The NWP SAF is a European collaboration funded by EUMETSAT. The NWP SAF is led by the Met Office, with partners ECMWF, DWD and Météo-France. It develops software to improve the assimilation of satellite data into NWP models and it also provides monitoring reports on various operational satellite products.
Chiara’s research is focused on the estimation of model errors using data assimilation techniques. Model error is a key factor in forecast uncertainty. In a realistic case, it is unlikely that model error can be represented exactly by physically based schemes. An alternative approach is to treat model error as unknowable and use data assimilation techniques to deduce information about the model error from observations. Chiara is also interested in using adaptive mesh methods to better represent the background error. A particular application is the representation of the background error in the presence of stratocumulus clouds.
Before joining the Met Office, Chiara worked for six years as a postdoc at the AOPP at the University of Oxford on infrared remote sensing from satellite instruments and retrieval theory to get the information content when using multi-channels instruments. This work was a continuation of her PhD in Physics at University of Florence.
After receiving a Ph.D. in Atmospheric Physics at the University of Toronto, Saroja Polavarapu joined Environment and Climate Change Canada as a post-doctoral fellow and embarked in a new direction: data assimilation. Since then, she has explored a variety of assimilation algorithms from optimal estimation to 3D and 4D variational assimilation and, most recently, ensemble Kalman Filtering. From 2001-2010, she focused on data assimilation in the context of stratospheric and mesospheric dynamics. In 2010 the context of her work switched to the carbon cycle. Over the years, Saroja has served on various WCRP and WWRP working groups. In 2005, she was awarded the President’s Prize of the Canadian Meteorological and Oceanographic society and in 2015, the Quarterly Journal Editor’s award.
Roland Potthast is head of the data assimilation section of Deutscher Wetterdienst and Professor for Applied Mathematics at the University of Reading. He has worked on inverse problems and data assimilation for 25 years, where he developed several innovative methods for reconstruction of unknown objects, parameter functions and states based on electromagnetic and acoustic measurements.
Currently, Roland is leading about 30-40 researchers in data assimilation with core applications in weather forecasting and neuroscience, developing the full scale of assimilation and forecasting from high temporal and spatial resolution (e.g. minutes and sub-kilometer-scale) to global weather systems, with a particular focus on the non-linear processes which characterize complex systems such as the atmosphere or the human brain, and the diversity of methods needed in an environment which integrates very diverse scientific and operational communities and user groups such as nowcasting and numerical weather prediction.
Dinand Schepers trained as an Aerospace Engineer specialised in satellite remote sensing before joining ECMWF’s research department in 2015 to work on coupled reanalysis. He worked on the production of the century-long coupled reanalysis CERA-20C and led the development and production of ECMWF's pilot for coupled reanalysis of the satellite era: CERA-SAT.
His current role at ECMWF focuses on research and development for reanalysis, supporting the operational production of ERA5 as well as leading the implementation of technical developments for future, coupled reanalyses. Additionally, he is affiliated with the Copernicus Climate Change Service (C3S) that is implemented by ECMWF supervising third-party activities on the provision of climate data records of Essential Climate Variable (ECV) data records.
Dr. Anthony Weaver is a Senior Researcher at the European Centre for Research and Advanced Training in Scientific Computation (CERFACS) in Toulouse. Dr. Weaver’s main area of interest has been ocean data assimilation. He has also worked on general algorithmic aspects of variational data assimilation, ensemble data assimilation, and covariance modelling. He has worked with ECMWF for many years, in recent years giving help and guidance on the NEMOVAR ocean data assimilation system, a collaborative project between ECMWF, the Met Office, CERFACS and INRIA (French National Institute for computer science and applied mathematics). NEMOVAR is the backbone of ECMWF’s ocean reanalysis ORAS4 and the new ocean reanalysis ORAS5, and is used to initialise the S4 seasonal forecasts and the coupled ensemble forecasts. Dr. Weaver is a member of several international committees and panels as well as a Principal Investigator on a number of European projects.
Dr. Nils P. Wedi joined ECMWF in 1995. He received his PhD degree from the LMU München. His career at ECMWF encapsulates a diverse range of work both technical and scientific. He leads ECMWF's Earth System Modelling section that addresses all aspects of scientific and computational performance relating to ECMWF's forecast model and the ensemble forecasting system. He develops strategies to secure the scalability of the model on future high-performance computing systems. He is the scientific coordinator of the European H2020 projects ESCAPE and ESCAPE-2 to address the challenges of rising energy cost for computing towards affordable, exascale high performance simulations of weather and climate, and he is a member of the WMO working group on numerical experimentation (WGNE).