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Titel |
Assessment of Forecast Sensitivity to Observation and Its Application to Satellite Radiances Assessment |
VerfasserIn |
Kayo Ide, David Grofff |
Konferenz |
EGU General Assembly 2017
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Medientyp |
Artikel
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Sprache |
en
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 19 (2017) |
Datensatznummer |
250152243
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Publikation (Nr.) |
EGU/EGU2017-17056.pdf |
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Zusammenfassung |
The Forecast sensitivity to observation provides practical and useful metric for the estimation of observation impact without conducting computationally intensive data denial experiments. Quite often complex data assimilation systems use a simplified version of the forecast sensitivity formulation based on ensembles. In this talk, we first present the comparison of forecast sensitivity for 4DVar, Hybrid-4DEnVar, and 4DEnKF with or without such simplifications using a highly nonlinear model. We then present the results of ensemble forecast sensitivity to satellite radiance observations for Hybrid-4DEnVart using NOAA’s Global Forecast System. |
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