Land surface and sub-surface data assimilation
Dr. Anne Springer
University of Bonn | +49 228 73-6149 |
Dr. Carsten Montzka
Forschungszentrum Jülich | +49 2461 613289 |
In C01 we will develop a coupled multi-scale, multi-source data assimilation (DA) system at the continental scale, where remotely sensed surface soil moisture, total water storage changes from the GRACE/-FO missions and land surface temperature data will constrain a coupled reanalysis from groundwater to the land surface. We will evaluate to what extent the reanalysis exhibits skill to represent observed trends, reproduce interannual variability, and to simulate extreme events. A special focus is laid on investigating strategies to correct for anthropogenic impacts on the hydrological system (irrigation, groundwater abstraction) through DA.
Contribution to the CRC
With respect to the CRC’s central hypothesis that human land management, land and water use changes have modified the regional atmospheric circulation and related water transports, we will add the related observations (e.g., soil moisture and land surface temperature for irrigation, total water storage anomalies for groundwater abstraction) to the central modeling system TSMP. This information is a prerequisite to adequately investigate the human role in the Eurasian climate system. To a certain extent, we are also able to support the formulation of criteria for sustainable trajectories by a differentiation between open loop simulations (the natural case) and observations (the reality case including human activities). Therefore, C01 adds knowledge with respect to all water balance equations, especially to evapotranspiration, runoff, as well as sinks and sources of terrestrial water fluxes.
We start from the central scientific hypothesis of this sub-project that surface soil moisture, total water storage anomalies and land surface temperature observations are useful to constrain coupled reanalysis from groundwater via the land surface to the lower atmosphere. Therefore, we need to run the coupled land surface - subsurface DA system at the continental scale and tune it regarding ensemble spread, mismatch between the measurement and model grid scale, possible bias correction procedures, and the choice of DA configurations addressing localization and inflation. This tuning procedure will involve the analysis of a large amount of output data. In this project, we will develop a coupled multi-scale, multi-source Ensemble Kalman Filter DA system for the whole Eurasian continent for the time span 2002 - 2022ff at a spatial resolution of 12 km. The DA system is based on TSMP-PDAF in the surface-subsurface mode, i.e., coupling the models CLM and ParFlow and using external atmospheric forcing data like the reanalysis COSMO-REA6.
Main results in 2022
We started the simulation of surface and subsurface fluxes with the TSMP model system and performed initial comparison towards in-situ measurements and remote sensing observations. This is necessary to identify adequate assimilation strategies that consider the observation error structures.