Accelerating Process Understanding for Ecosystem Functioning under Extreme Climates with Physics-Aware Machine Learning

This project will couple the vegetation photosynthesis model (SCOPE) with the soil moisture model (STEMMUS, considering dynamic root growth), synergized with Earth-Observation data, to understand how the water-carbon dynamics of an ecosystem vary with environmental and climate stress. Currently, a hurdle in applying STEMMUS-SCOPE globally is its expensive computational cost. As a first step, both STEMMUS and SCOPE will be exposed to the Basic-Model-Interface, which will be subsequently coupled using Python-Modeling-Toolkit, serving as first level acceleration. Second, a physics-aware machine learning emulator, based on a limited number of STEMMUS-SCOPE runs, will be developed.