Data assimilation on the neXtSIM sea ice model involving numerical modelling,data assimilation and sea-ice physics.
My work is to develop novel data assimilation methods for numerical models using a time-varying mesh,possibly Lagrangian and non-conservative. In particular,the main task will be the development of an ensemble-based data assimilation system for the state-of-the-art sea ice model,neXtSIM,developed in-house at NERSC. Contribute to studying the probabilistic,ensemblebased,forecast skill of neXtSIM.

My work is in the field of remote sensing, inverse modelling, machine learning and data assimilation. The objective is to propose new methodologies in order to extract knowledge from data and physical systems, more specifically in oceanography.

Those methodologies were apply to estimate and forecast key variables and their associated uncertainty in the ocean such as phytoplankton and surface currents. The methodologies developed were using remote sensing data (satellite sensors).