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| Titel |
Typhoon Track Forecast with a hybrid GSI-ETKF data assimilation system |
| VerfasserIn |
Hong Li, Jingyao Luo, Baode Chen, Xiaofeng Wang |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250073205
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| Zusammenfassung |
| A hybrid Grid-point Statistical Interpolation-Ensemble Transform Kalman Filter (GSI-ETKF) data assimilation system for the WRF was developed and applied to typhoon track forecast with simulated dropsonde observations. By examining the analyses and the follow-up forecasts, a significant improvement of this hybrid system over the GSI system on tropical cyclone track forecast was found in the cases of Muifa in 2011. Further analyses revealed that the flow-dependent ensemble covariance is the major contributor to make the performance of the GSI-ETKF better than the standard GSI through systematically adjusting the position of the typhoon vortex and better updating the environmental field.
Keywords: data assimilation, hybrid, tropical cyclone |
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