Yoichiro Ota
Japan Meteorological Agency
The 8th EnKF Data Assimilation Workshop
Localization methods for assimilating dense observations in the global LETKF
Talk:
20180509_EnKFWS_ota_v2.pptx
The number of observations available for the operational numerical weather prediction (NWP) is growing rapidly due to the introduction of highly dense observations such as the hyper spectral sounders. The ensemble-based data assimilation has a limitation on assimilating such dense observations since the degree of freedom available for the assimilation is confined to the ensemble size. Several ideas are proposed recently for assimilating such spatially dense observations in the ensemble Kalman filters. Among those methods this study focuses on limiting the number of observations assimilated locally in the Local Ensemble Transform Kalman Filter (LETKF). This is equivalent to shortening the localization cutoff radius for spatially dense observations. In this presentation, the result of this experiment and comparison of observation-based statistics in the pure global LETKF will be presented. Also, the potential application of the model space vertical localization in the framework of the operational global LETKF will be discussed.
The number of observations available for the operational numerical weather prediction (NWP) is growing rapidly due to the introduction of highly dense observations such as the hyper spectral sounders. The ensemble-based data assimilation has a limitation on assimilating such dense observations since the degree of freedom available for the assimilation is confined to the ensemble size. Several ideas are proposed recently for assimilating such spatially dense observations in the ensemble Kalman filters. Among those methods this study focuses on limiting the number of observations assimilated locally in the Local Ensemble Transform Kalman Filter (LETKF). This is equivalent to shortening the localization cutoff radius for spatially dense observations. In this presentation, the result of this experiment and comparison of observation-based statistics in the pure global LETKF will be presented. Also, the potential application of the model space vertical localization in the framework of the operational global LETKF will be discussed.
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