[MGI28-P09] Implicit thinning and localization of dense observation data in the LETKF: A case of phased array weather radar
Keywords:localization, thinning, LETKF, dense observation, radar assimilation
We point out that, when using an ensemble data assimilation method, another important, but likely neglected reason to thin the data is to stay in the range that all observations can be effectively assimilated by the limited ensemble size. This issue has been usually addressed by covariance localization methods, but probably not in an optimal way. Recently, the LETKF systems at European Centre for Medium-Range Weather Forecasts (ECMWF) and Deutscher Wetterdienst (DWD) have adopted an “implicit localization” method that significantly reduces the assimilated observation numbers while preserving high-resolution information, by selecting N nearest neighbors of observations from the analyzed grid point. We demonstrate the usefulness of this method on the assimilation of very dense phased array weather radar data, and explain it as an ideal combination of thinning and localization.