EGU21-15603, updated on 14 Jan 2022
EGU General Assembly 2021
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

EnVAR for ICON-LAM: observations and quality control

Mareike Burba1, Sven Ulbrich1, Stefanie Hollborn1, Roland Potthast1, and Peter Knippertz2
Mareike Burba et al.
  • 1Deutscher Wetterdienst, Forschung und Entwicklung, Offenbach, Germany (
  • 2Karlsruhe Institute of Technology, Karlsruhe, Germany

The German Weather Service (DWD) introduces the regional NWP model ICON-LAM (ICON Limited Area Mode) in 2021 to replace the COSMO model. For the ICON-LAM data assimilation, a novel EnVAR (Ensemble VARiational data assimilation) setup is currently evaluated in comparison to the operational deterministic run of KENDA-LETKF (Local Ensemble Transform Kalman Filter). This requires special care as the observation handling differs for the global assimilation (via EnVAR) and the regional assimilation (KENDA). Furthermore, the variational quality control for the regional EnVAR may require a setup differing from the global setup. We will give an introduction to the observation processing in DWD's data assimilation framework (DACE).

For future development, we give an outlook on how a regional EnVAR can be used for a regional deterministic analysis by using a global ICON ensemble in combination with a regional deterministic ICON-LAM run. This is potentially of interest for DWD's partners with smaller computational capacities, because a regional EnVAR analysis is computationally less expensive than running a full KENDA ensemble assimilation cycle.

How to cite: Burba, M., Ulbrich, S., Hollborn, S., Potthast, R., and Knippertz, P.: EnVAR for ICON-LAM: observations and quality control, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15603,, 2021.

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