Adaptive Covariance Hybridization for the Assimilation of SST Observations Within a Coupled Earth System Reanalysis
Sébastien Barthélémy,
François Counillon,
Yiguo Wang
Abstract:Ensemble data assimilation methods, such as the Ensemble Kalman Filter (EnKF), are well suited for climate reanalysis because they feature flow‐dependent covariance. However, because Earth System Models are heavy computationally, the method uses a few tens of members. Sampling error in the covariance matrix can introduce biases in the deep ocean, which may cause a drift in the reanalysis and in the predictions. Here, we assess the potential of the hybrid covariance approach (EnKF‐OI) to counteract sampling err… Show more
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