Modelling
Land surface processes
Land Surface Models
Land surface models (LSM) are process models which simulate the exchange of water, energy and greenhouse gas fluxes at the Earth surface-atmosphere interface. They are key component of Earth System Models (ESM), but are also used as stand alone models of the biosphere. Resolving nutrient related processes in such models is a key area of my research. Currently, I am leading the development of the phosphorus cycle in the LSM ORCHIDEE-CNP. Since it release in 2017, this version of ORCHIDEE has been used in ~50 scientific publication, including Science and Nature (here, here, here).
Soil biogeochemistry Models
Soil models simulate the storage and transformation of inorganic and organic matter within soils. They are key components of land surface models. Resolving major processes governing soil dynamics is a key area of my research.
Hybrid Modelling / Artificial Intelligence
Machine learning approaches are commonly used to extract patterns and insights from the ever-increasing stream of geospatial data. Currently, we are testing a new hybrid modelling approach, coupling physical process models with the versatility of data-driven artificial intelligence (AI). A prototype of AI-powered acceleration procedure for land surface models has been published and is now adopted for the ORCHIDEE family of land surface models.