Jérôme joined the JCSDA in October 2021. He leads the effort on atmospheric composition data assimilation (DA). Jérôme has experience in operations and research for atmospheric composition applications using variational, ensemble and hybrid systems. He had the opportunity to work on regional and global scale systems for air quality applications and global monitoring of pollutants.

He started his career at Météo-France where he focused on satellite 3D-Variational DA of ozone and carbon monoxide with a specific focus on pollution transport between the troposphere and the stratosphere. He then started to work at NCAR in 2013 focusing on observation simulation system experiments, ensemble DA methods and source inversion techniques. In 2017, he moved back to Europe to work at ECMWF where he maintained and developed the Copernicus Atmosphere Monitoring Service’s greenhouse gases operational 4D-Variational DA system. He also contributed to the development of the source inversion capability in the IFS system. He also served as a technical officer for the CAMS regional operational forecast ensemble that includes 11 models and teams across Europe. He recently developed an interest in machine learning to make the best use of operational products, such as automatic detections and classification of emissions and accurate assessment of air quality changes during pandemic lockdowns.

He now leads the COMPO team at JCSDA which aims to push the frontier of atmospheric composition data assimilation capability for air quality, emission monitoring and numerical weather prediction.