EGU21-7439, updated on 04 Jan 2022
EGU General Assembly 2021
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Building a coupled data assimilation system for the atmosphere, land-surface and subsurface on the catchment scale

Bernd Schalge1, Barbara Haese2, Bastian Waldowski3, Natascha Brandhorst3, Emilio Sanchez4, Ching Pui Hung5, Shaoning Lv1, Lennart Schüler6, Harald Kunstmann2,7, Olaf Cirpka4, Sabine Attinger6, Stefan Kollet5,8, Insa Neuweiler2, Harrie-Jan Hendricks Franssen5,8, and Clemens Simmer1
Bernd Schalge et al.
  • 1University of Bonn, Institute for Geosciences, Bonn, Germany
  • 2University of Augsburg, Institute of Geography, Augsburg, Germany
  • 3Leibniz Universität Hannover, Institute of Fluid Mechanics and Environmental Physics in Civil Engineering, Hannover, Germany
  • 4Eberhard Karls Universität Tübingen, Center for Applied Geoscience, Tübingen, Germany
  • 5Forschungszentrum Jülich (FZJ), Institute of Bio- and Geosciences- Agrosphere (IBG-3), Jülich, Germany
  • 6Helmholtz Zentrum für Umweltforschung, Computational Hydrosystems, Leipzig, Germany
  • 7Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK-IFU), Garmisch-Patenkirchen, Germany
  • 8Simulation Laboratory Terrestrial Systems (SimLab TerrSys), Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich (FZJ), Jülich, Germany

We present a data assimilation (DA) system for the atmosphere-land-surface-subsurface system on the catchment scale. The Neckar catchment in SW-Germany served as the specific case where the DA in combination with the coupled atmosphere-land surface-subsurface model TSMP was used. TSMP couples the atmospheric model COSMO, the land-surface model CLM and the hydrological model ParFlow to the DA framework PDAF. We will discuss how the ensemble system is set up in order to work properly and what issues we faced during our initial testing. For the atmosphere we found that it is important to have a good ensemble of lateral forcings as changing internal parameters for various parametrizations does not introduce sufficient variability on its own due to the rather small size of our domain. For the sub-surface the choice of parameters becomes most important and as such parameter estimation will be a valuable tool for improving DA results significantly. Finally, we are showing some first DA results with our system concerning soil moisture with two different assimilation methods with a fully coupled model setup. In the first assimilation scenario in-situ soil moisture data measured by cosmic ray probes are assimilated, while in the second assimilation scenario remotely sensed near surface soil moisture is assimilated. The first results are encouraging and we discuss additional planned simulation scenarios with the fully coupled atmosphere-land surface-subsurface modelling system as well as plans to test strongly coupled DA, where measurements are used to update states across compartments, possibly resulting in additional accuracy gain compared to traditional uncoupled DA.


How to cite: Schalge, B., Haese, B., Waldowski, B., Brandhorst, N., Sanchez, E., Pui Hung, C., Lv, S., Schüler, L., Kunstmann, H., Cirpka, O., Attinger, S., Kollet, S., Neuweiler, I., Hendricks Franssen, H.-J., and Simmer, C.: Building a coupled data assimilation system for the atmosphere, land-surface and subsurface on the catchment scale, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7439,, 2021.