Localizing the Error Covariance by Physical Distances within a Local Ensemble Transform Kalman Filter (LETKF)

DOI Web Site 被引用文献41件 参考文献8件 オープンアクセス
  • Miyoshi Takemasa
    Numerical Prediction Division, Japan Meteorological Agency
  • Yamane Shozo
    Faculty of Risk and Crisis Management, Chiba Institute of Science Frontier Research Center for Global Change, JAMSTEC
  • Enomoto Takeshi
    Earth Simulator Center, JAMSTEC

書誌事項

公開日
2007
DOI
  • 10.2151/sola.2007-023
公開者
公益社団法人 日本気象学会

説明

An efficient implementation of the local ensemble transform Kalman filter (LETKF) with the error covariance localization by physical distances is introduced and assessed in this study. Instead of using local patches uniform in the model grid space to localize the error covariance, accurate physical distances are computed and used for the localization, so that the problem of analysis discontinuities in the Polar Regions is solved. Data assimilation cycle experiments with real observations are performed, which indicate less discontinuity in the Polar Regions. Moreover, the computational time is shorter and more robust for various localization scales. Thus, the implementation introduced in this study is a promising choice of future LETKF systems.

収録刊行物

  • SOLA

    SOLA 3 89-92, 2007

    公益社団法人 日本気象学会

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参考文献 (8)*注記

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