Improving the representation of water, energy and carbon cycles in land surface modelling: Assimilation of MAGIC TWSA data

The upcoming MAGIC (Mass Change and Geoscience International Constellation) mission aims to extend the current record of mass change observations with higher spatiotemporal resolution data. This study evaluates the potential of terrestrial water storage (TWS) observations from MAGIC in improving our understanding of the coupled water, energy, and carbon cycles.   

Using a synthetic data assimilation experiment, we integrate simulated MAGIC TWS data into a high-resolution (3 km) land surface model over two European study areas. These regions are selected for their strong land-atmosphere coupling, providing suitable test cases for investigating whether and how improvements in soil moisture profiles and snow cover from TWS assimilation translate to improved estimates in energy and carbon cycle variables. Our research addresses two primary objectives: (i) quantifying the added benefit of assimilating TWS changes in constraining model states, such as land surface temperature and vegetation growth, relative to a known reference, and (ii) investigating how the increased resolution of MAGIC supports an improved representation of land-atmosphere coupling, particularly during extreme drought events, using ecosystem-scale water use efficiency (the ratio of gross primary productivity to evapotranspiration) as a diagnostic of vegetation response.