Sebastien joined ECMWF in March 2012 as a scientist on the assimilation of the greenhouse gases for the MACC (Monitoring Atmospheric Composition and Climate) projects. He then continued this activity as part of the Copernicus Atmosphere Monitoring Service (CAMS).
Sebastien moved to the data assimilation methodology team in December 2016. His main focus is the sustenance of ECMWF assimilation system. He also participate to the development of the OOPS project and helps on its scientific validation.
- Data assimilation methodology
- Ensemble methods
- Atmospheric chemistry
Master Degree in Engineering, ENSEEIHT, Toulouse 1999
PhD on Earth Science, Environment and data assimilation, INP Toulouse, France, 2003
- December 2002 to March 2012: CERFACS
- March 2012 to December 2016: ECMWF CAMS
- From December 2016: ECMWF DAM
Summary of experience:
I have been working with data assimilation methods for more than sixteen years. My experience includes the implementation and use of data assimilation for various models (mostly geosciences models) and with various methods.
Between 2003 and 2012, I have been developing in Fortran the Valentina chemical data assimilation system. Valentina is a flexible and modular variational assimilation suite allowing global and regional chemical transport models to assimilate data with a 3D-Var, a 3D-FGAT or a 4D-Var method (see publications list). I further develop this activity within the framework of the series of the Monitoring Atmospheric Composition and Climate (MACC) European projects. These projects helped me to build a team of three people around Valentina, team I managed during several years.
Together we coupled Valentina with the global and the regional versions of the Meteo-France/CNRM Mocage chemistry transport model. The regional version of this coupled system is currently used operationally in the Copernicus Atmosphere Monitoring Service (CAMS) to produce regional air quality analyses.
Although I have mainly focused on variational assimilation methods for the development of Valentina, I am also very familiar with Kalman filter methods and ensemble methods. Part of my studies are based on hybrid methods and aimed to diagnose and formulate the covariance matrix of the background error, both for a global system assimilating satellite data (Pannekoucke and Massart, 2008, Massart et al., 2011) and a regional system assimilating in situ data (Jaumouille et al., 2011). My experience also covers some more methodological aspects of data assimilation like highlighting some issues of the 3D-FGAT method for transport models (Massart et al., 2010).
Apart from atmospheric chemistry, my work concerned several other components of the Earth system. I used to work with Nemo-Var, the assimilation system which is used for the ocean reanalysis ORAS5. I also participated to the development of an assimilation system for the French National Hydrometeorological and Flood Forecasting Center (SCHAPI) to further improve their operational flood forecast over France.
I joined ECMWF in 2012 to further develop the assimilation of the greenhouse gas satellite data as part of the MACC projects and then CAMS. In parallel, I explored and expanded hybrid assimilation methods similar to the ones used in the Research Department. I first adapted ECMWF Ensemble of Data Assimilations (EDA) to the CAMS greenhouse gases in collaboration with the Data Assimilation Methodology Team of the Earth System Assimilation Section (Massart and Bonavita, 2016). I also explored the use of ECMWF Ensemble Kalman Filter (EnKF) for the greenhouse gases in collaboration with the Numerical Methods team of the Earth System Modelling Section.
Since end of 2016 I moved to the data assimilation methodology team to work mainly on hydrib 4D-Var.
- Tony McNally, Philip Browne, Marcin Chrust, David Fairbairn, Sebastien Massart, Kristian S. Mogensen, Hao Zuo (July 2022) Progress on developing a new coupled sea-surface temperature analysis, ECMWF Newsletter, issue 172, pp. 17-22. DOI: 10.21957/tm4913hs8d
- Massimo Bonavita, Alan Geer, Patrick Laloyaux, Sebastien Massart, Marcin Chrust (May 2021) Data assimilation or machine learning? , ECMWF Newsletter, issue 167, pp. 17-22. DOI: 10.21957/ut51mb7c39
- Sebastien Massart, Niels Bormann, Massimo Bonavita, Cristina Lupu (August 2020) Skin Temperature Analysis for the Assimilation of Clear-Sky Satellite Radiances, ECMWF Technical Memoranda n. 870. DOI: 10.21957/goe0ads8z
- Barré J., Sebastien Massart, Melanie Ades, Luke Jones, Richard Engelen (July 2019) Emission optimisations first attempt based on Ensemble of DA for atmospheric composition, ECMWF Technical Memoranda n. 848. DOI: 10.21957/4grkg5ga0
- Sebastien Massart (December 2019) A new hybrid formulation for the background error covariance in the IFS: evaluation, ECMWF Technical Memoranda n. 856. DOI: 10.21957/3ad31a1ey
- Rossana Dragani, Angela Benedetti, Johannes Flemming, Gianpaolo Balsamo, Michail Diamantakis, Alan Geer, Robin Hogan, Timothy Stockdale, Melanie Ades, Anna Agusti-Panareda, Barré J., Peter Bechtold, Alessio Bozzo, Hans Hersbach, Elias Hólm, Zak Kipling, Antje Inness, Julie Letertre-Danczak, Sebastien Massart, Marco Matricardi, Tony McNally, M. Parrington, irina sandu, Cornel Soci, Frederic Vitart (December 2018) Atmospheric Composition priority developments for Numerical Weather Prediction, ECMWF Technical Memoranda n. 833. DOI: 10.21957/5e0whui2y
- Sebastien Massart (October 2018) A new hybrid formulation for the background error covariance in the IFS: Implementation aspects, ECMWF Technical Memorandum n. 832. DOI: 10.21957/6gdjcd4j3
- Sebastien Massart, Anna Agusti-Panareda, Johannes Flemming (March 2017) Evidence of a stratospheric methane bias in the IFS against MIPAS data, ECMWF Technical Memorandum n. 814. DOI: 10.21957/3syruetb9
- Sebastien Massart, Massimo Bonavita (March 2016) Ensemble of Data Assimilations applied to the CAMS' greenhouse gases analysis, ECMWF Technical Memoranda n. 780. DOI: 10.21957/rvnt8iz3s
- Anna Agusti-Panareda, Sebastien Massart, F. Chevallier, Gianpaolo Balsamo, Souhail Boussetta, Emanuel Dutra, Anton Beljaars (March 2015) A biogenic C02 flux adjustment scheme for the mitigation of large-scale biases in global atmospheric CO2 analyses and forecasts, ECMWF Technical Memorandum n. 773. DOI: 10.21957/ylfzoi6i1
- (March 2014) Forecasting global atmospheric CO2, Atmos. Chem. Phys. DOI: 10.5194/acp-14-11959-2014
- (March 2014) Combined assimilation of IASI and MLS observations to constrain tropospheric and stratospheric ozone in a global chemical transport model, Atmos. Chem. Phys. DOI: 10.5194/acp-14-177-2014
- (March 2014) Data assimilation applied to combustion, Comptes Rendus Mecanique. DOI: 10.1016/j.crme.2012.10.011
- (March 2014) Assimilation of atmospheric methane products into the MACC-II system: from SCIAMACHY to TANSO and IASI, Atmos. Chem. Phys. DOI: 10.5194/acp-14-6139-2014
- Anna Agusti-Panareda, Sebastien Massart, Souhail Boussetta, Gianpaolo Balsamo, Anton Beljaars, F. Chevallier, Richard Engelen, Vincent-Henri Peuch, Miha Razinger (March 2013) The new MACC-II CO2 forecast, ECMWF Newsletter, issue 135, pp. 8-13. DOI: 10.21957/ajm47w6h
- (March 2011) A thermal infrared instrument onboard a geostationary platform for CO and O3 measurements in the lowermost troposphere: Observing System Simulation Experiments, Atmos. Mes. Tech.. DOI: 10.5194/amt-4-1637-2011
- (March 2007) The Assimilation of Envisat data (ASSET) project, Atmos. Chem. Phys.
- (March 2006) The ASSET intercomparison of ozone analyses: method and first results, Atmos. Chem. Phys.