Data Assimilation Seminar

Prof. Roland Potthast (Nov. 13, 2018, 10:30-)

Affiliation German Weather Service (DWD) / University of Reading
Title New Observations and Algorithmic Developments for Convective Scale Ensemble Data Assimilation

We first present the setup of the ensemble data assimilation (EDA) and forecasting systems (EPS) which have been developed and are under development at the German Weather Service DWD and its COSMO partners. This is first the ICON global+mesoscale model (two-way nested), 13km/6.5km resolution, with its hybrid ensemble variational data assimilation (LETKF+EnVAR) run on a 3h cycle,and the ensemble prediction system ICON EPS. Second, this system drives the high-resolution ensemble data assimilation system COSMO-KENDA (Kilometer Scale Ensemble Data Assimilation) with 2.2km operational resolution at DWD and up to 1km resolution at further members of the COSMO consortium (Germany, Switzerland, Italy, Russia, Poland, Romania, Greece and Israel) to provide initial conditions for the high-resolution ensemble forecasting systems, e.g. the operational COSMO-D2-EPS or experimental ICON-LAM EPS. The system is also successfully run on GPU based supercomputers.

The core task of the talk is to discuss recent and current developments on new observations and on new algorithmic developments on the convective scale, but many of them relevant for global NWP as well. We discuss recent insight into the importance of quality control, report on the large success and positive impact of Mode-S data assimilation, discuss the assimilation of RADAR radial winds and reflectivity with an ensemble Kalman filter and finally report on some initial tests on the assimilation of visible channels SEVIRI VIS on the convective scale.

Second, we will discuss new algorithmical developments, in particular aspects of 4D-LETKF versus 3D-LETKF and initial tests on the ICON-LAM data assimilation with the KENDA system. Then, we present the particle filter for global or convective scale EDA as well as ultra-rapid data assimilation (URDA) on a scale of minutes imbedded into an operational rapid update cycle (RUC) of a convection resolving model.

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