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Observation bias correction with an ensemble Kalman filter 总被引:1,自引:0,他引:1
ELANA J. FERTIG SEUNG-JONG BAEK BRIAN R. HUNT EDWARD OTT ISTVAN SZUNYOGH JOSÉ A. ARAVÉQUIA EUGENIA KALNAY HONG LI JUNJIE LIU 《地球,A辑:动力气象学与海洋学》2009,61(2):210-226
This paper considers the use of an ensemble Kalman filter to correct satellite radiance observations for state dependent biases. Our approach is to use state-space augmentation to estimate satellite biases as part of the ensemble data assimilation procedure. We illustrate our approach by applying it to a particular ensemble scheme—the local ensemble transform Kalman filter (LETKF)—to assimilate simulated biased atmospheric infrared sounder brightness temperature observations from 15 channels on the simplified parameterizations, primitive-equation dynamics (SPEEDY) model. The scheme we present successfully reduces both the observation bias and analysis error in perfect-model simulations. 相似文献
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