Patricia de Rosnay

Senior Scientist
Research Department, Earth System Assimilation Section, Coupled Assimilation Group

page tabs


Patricia de Rosnay is a Senior Scientist with the European Centre for Medium-Range Weather Forecasts (ECMWF) where she is leading the Coupled Assimilation Team in the Earth System Assimilation Section.  Her Team is in charge of the development of coupled Earth system assimilation, land surface assimilation and ocean assimilation in the ECMWF NWP systems. 

Professional interests: 

Patricia de Rosnay implemented a new soil moisture analysis scheme based on a point-wise Extended-Kalman Filter (EKF) for the global land surface in the ECMWF Integrated Forecasting System in November 2010. As part of the EKF implementation strategy a new surface analysis structure was implemented in 2009 to separate completely the upper air analysis and the surface analysis. The new EKF surface analysis opens the possibility of investigating the use of active (ASCAT) and passive (SMOS) microwave satellite data for soil moisture analysis in Numerical Weather Prediction.
Concerning snow, she has conducted major research projects in the past few years to improve the quality of the snow analysis, to ensure a better use of the satellite snow cover information (use of the IMS NESDIS snow cover information ) and to improve the SYNOP data quality control. She implemented an Optimal Snow analysis (OI) in operations in November 2010 and further revision of the snow analysis, with improved assimilation of IMS snow cover data, including separate error specification that was implemented in IFS cycle 40r1 in November 2013. Land surface observation monitoring and improved land surface blacklisting system were part of these developments.

Patricia de Rosnay is coordinating the SMOS and H-SAF projects at ECMWF.

More information on How do land surface observations improve weather forecasts?

Career background: 

Patricia received her Ph.D degree in climate modelling from the University Pierre et Marie Curie (Paris 6, France) in 1999. She developed the physically-based multi-layer hydrology, the sub-grid scale representation of vegetation and soil texture and the irrigation parameterisation in the ORCHIDEE land surface model at the Laboratoire de Météorologie Dynamique (LMD/IPSL, Paris, France).

From 1999 to 2002, she worked on global land surface modelling developments and she developed the irrigation parameterisation in the ORCHIDEE land surface model at the Laboratoire de Météorologie Dynamique (LMD/IPSL, Paris, France).

From 2002 to 2007 she worked as research scientist (Chargé de Recherche) for the French CNRS (Centre National de la Recherche Scientifique) at CESBIO (Toulouse). She was inloved in soil moisture and passive microwave radiometry observation field experiments (SMOSREX, AMMA, Nafe2005), in the Soil Moisture and Ocean Salinity (SMOS) satellite mission preparation, and in coordinated land surface modelling experiments (ALMIP).

Since 2007 Patricia has been working at ECMWF in secondment from her CNRS position.

She developed the current version of the Community Microwave Emission Modelling Platform (CMEM) which is used for SMOS monitoring and data assimilation. 

Since 2008 she has been in charge of the ECMWF LDAS used to initialize the land surface prognostic variable for NWP.  Her activities  include developments related to: screen level data assimilation and interface to observations, snow data assimilation and monitoring, ASCAT and SMOS data assimilation, and methodological developments of land surface analysis (OI, SEKF, EDA-EKF). 

Since 2016, Patricia de Rosnay has been the Coupled Assimilation Team Leader.  Her activities are focused on developments of coupled Earth System data assimilation across the ECMWF systems, including reanalysis, and medium and extended range NWP systems (monthly and seasonal forecasts).

External recognitions: 

Latest publications
To see all publications please visit the links on the right-hand side

thumbnail photo of Patricia de Rosnay
Contact Details:
patricia . rosnayecmwf . int
Tel. +44 (0) 118 9499625