A Stochastic Covariance Shrinkage Approach in Ensemble Transform Kalman Filtering
The Ensemble Kalman Filters (EnKF) employ a Monte-Carlo approach to represent covariance information, and are affected by sampling errors in operational settings where GARDENIA SHAMPOO the number of model realizations is much smaller than the model state dimension.To alleviate the effects of these errors EnKF relies on model-specific heuristics suc