第56回 ESCセミナー
Adaptive localization and adaptive inflation methods with the LETKF
- 日時
- 2010年6月9日 (水) 14:00-14:45
- 場所
- 横浜研究所 交流棟2F 小会議室1&2
- 講演者
- Takemasa Miyoshi (Research Assistant Professor, Department of Atmospheric and Oceanic Science, University of Maryland)
- 使用言語
- 日本語または英語
要旨
In ensemble Kalman filters with high-dimensional systems, the error covariance estimated by ensemble members is usually rank deficient and contains inevitable sampling errors. Moreover, it is known that the error covariance is underestimated due to various sources of imperfections such as the limited ensemble size and model's nonlinearity. These are the typical reasons of filter divergence and are usually treated by empirical covariance localization and inflation techniques. However, it is prohibitive to optimize the parameters of localization and inflation, since they would depend on geographical locations, vertical levels, and even seasons. In this study, adaptive methods for covariance inflation and localization, which are particularly efficient with the Local Ensemble Transform Kalman Filter (LETKF), are proposed. The methods are tested with a low-resolution AGCM and show promising results.
問い合わせ先
地球シミュレータセンター榎本 剛
TEL: 045-778-5867
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