Associate Research Scientist
Projects: Global Climate Modeling, Atmospheric Composition
For his B.S and M.S in Atmosphere/Ocean/Soil remote sensing at the University of Toulon, he studied the Earth system climate and how to monitor it. He pursued his professional career in the climate research field at the Laboratoire de Météorologie Dynamique [LMD/IPSL] as an engineer and three years later as a Ph.D student (University of Paris 6), during which he used CALIPSO satellite observations to characterize cloud and radiation biases in climate models. As a postdoctoral scientist at the NASA Jet Propulsion Laboratory (JPL), he extended his knowledge of satellite data for model evaluation using other A-train constellation instruments (CloudSat’s cloud profiling radar, Aqua’s CERES instrument among others). Recently, he joined the modeling team of the NASA Goddard Institute for Space Studies (GISS) to help them improve the representation of cloud-climate feedbacks in the GISS model using satellite observations.
His research is focused on improving our understanding of cloud processes and cloud-radiation interactions in the past, present and future climate. In particular, he’s interested in the modifications that clouds and precipitation undergo in response to anthropogenically induced energy imbalances, commonly referred to as “cloud feedbacks”. Reducing the uncertainty caused by these feedbacks is critical to predict the future climate change. To tackle this problem, he currently works on the development and the use of satellite observations to evaluate the representation of cloud-radiation feedbacks in climate models. He specializes in active sensor satellite observations from a-train CALIPSO and CloudSat satellites, which give access to unprecedented cloud-related information such as the detailed vertical structure of clouds and their water phase partitioning, as well as their precise spatial distribution over continents and polar regions. These unique observations bring new perspectives and open the path to new breakthrough in the understanding of the climate system.