Abstract |
Ensemble data assimilation techniques are of rapidly growing importance. Ensemble techniques allow to describe and forecast uncertainty of the analysis, but they also improve the assimilation result itself, by allowing estimates of the covariance or, more general, the prior and posterior probability distribution of atmospheric states.
In our talk, we will first give a survey about recent activities of the German Meteorological Service DWD. Then, we present recent work on the further development of the ensemble data assimilation towards a particle filter for large-scale atmospheric systems, which keeps the advantages of the LETKF, but overcomes some of its limitations. First snapshots generated by a particle filter for the global ICON model of DWD will be shown.
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