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Korean Meteorological Society (한국기상학회)
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An Affordable Implementation of Kalman Filter by Eliminating the Explicit Temporal Evolution of the Background Error Covariance Matrix

칼만필터의 자료동화 활용을 위한 배경오차 공분산의 명시적 시간 진전 제거

  • Lim, Gyu-Ho (Atmospheric Sciences Program, School of Earth and Environmental Sciences, Seoul National University) ;
  • Suh, Ae-Sook (Daejeon Regional Meteorological Administration) ;
  • Ha, Ji-Hyun (Atmospheric Sciences Program, School of Earth and Environmental Sciences, Seoul National University)
  • 임규호 (서울대학교 자연과학대학 지구환경과학부) ;
  • 서애숙 (대전 기상청) ;
  • 하지현 (서울대학교 자연과학대학 지구환경과학부)
  • Received : 2012.11.23
  • Accepted : 2013.01.26
  • Published : 2013.03.31
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Abstract

In meteorology, exploitation of Kalman filter as a data assimilation system is virtually impossible due to simultaneous requirements of adjoint model and large computer resource. The other substitute of utilizing ensemble Kalman filter is only affordable by compensating an enormous usage of computing resource. Furthermore, the latter employs ensemble integration sets for evolving the background error covariance matrix by compensating the dynamical feature of the temporal evolution of weather conditions. We propose a new implementation method that works without the adjoint model by utilizing the explicit expression of the background error covariance matrix in backward evolution. It will also break a barrier in the evolution of the covariance matrix. The method may be applied with a slight modification to the real time assimilation or the retrospective analysis.

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References

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