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Empirical Localization Functions for Ensemble Kalman Filter Data Assimilation in Regions with and without Precipitation
2015
Monthly Weather Review
For ensemble-based data assimilation, localization is used to limit the impact of observations on physically distant state variables to reduce spurious error correlations caused by limited ensemble size. Traditionally, the localization value applied is spatially homogeneous. Yet there are potentially larger errors and different covariance length scales in precipitation systems, and that may justify the use of different localization functions for precipitating and nonprecipitating regions. Here
doi:10.1175/mwr-d-14-00415.1
fatcat:r4crzbbeh5ghlmvsjlm6ispxyq