PhD position offer: « Contribution of machine learning to the integration of satellite observations into a global land surface model »

The PhD work will be cosupervised by J.-C. Calvet (CNRM) and Nemesio Rodriguez-Fernandez (CESBIO). The thesis will take place at the CNRM.

In the context of climate warming, the frequency and the intensity of extreme events such as droughts is increasing, and better modelling the response of vegetation to climate is needed. Monitoring the impact of extreme events on terrestrial surfaces involves a number of variables of the soil-plant system such as surface albedo, the soil water content and the vegetation leaf area index (LAI). These variables can be monitored by either using the unprecedented amount of data from the Earth observation satellite fleet, or using land surface models. Another solution consists in combining all available sources of information by integrating satellite observations into models. More informations and submission modalities…

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