An Optimal Experimental Design Framework for Adaptive Inflation and Covariance Localization for Ensemble Filters

We develop an optimal experimental design framework for adapting the covariance inflation and localization in data assimilation problems. Covariance inflation and localization are ubiquitously employed to alleviate the effect of using ensembles of finite sizes in all practical data assimilation systems. The choice of both the inflation factor and the... Show more