4.8 Aspects of the Extended and Ensemble Kalman Filters for Land Data Assimilation in the Nasa Seasonal-to-interannual Prediction Project
نویسندگان
چکیده
Successful climate prediction at seasonal-to-interannual time scales may depend on the optimal initialization of the land surface states, in particular soil moisture (Koster and Suarez 2001). Such optimal initialization can be achieved by assimilating soil moisture observations into the land model prior to the forecast. We assess the performance of the Extended Kalman filter (EKF) and the Ensemble Kalman filter (EnKF) for soil moisture estimation when used with the Catchment Land Surface Model (CLSM) of the NASA Seasonal-to-Interannual Prediction Project.
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