Using analysis state to construct a forecast error covariance matrix in ensemble Kalman filter assimilation
作者： Xiaogu Zheng , Guocan Wu , Shupeng Zhang , Xiao Liang , Yongjiu Dai
DOI: 10.1007/S00376-012-2133-5
关键词:
摘要: Correctly estimating the forecast error covariance matrix is a key step in any data assimilation scheme. If it not correctly estimated, assimilated states could be far from true states. A popular method to address this problem inflation. That is, multiply by an appropriate factor. In paper, analysis are used construct and adaptive estimation procedure associated with inflation technique developed.
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