Localized adaptive inflation in ensemble data assimilation for a radiation belt model

Abstract

In this work a one-dimensional radial diffusion model for phase space density, together with observational satellite data, is used in an ensemble data assimilation with the purpose of accurately estimating Earth's radiation belt particle distribution. A particular concern in data assimilation for radiation belt models are model deficiencies, which can adversely impact the solution of the assimilation. To adequately address these deficiencies, a localized adaptive covariance inflation technique is implemented in the data assimilation to account for model uncertainty. Numerical results from identical-twin experiments, where data is generated from the same model, as well as the assimilation of real observational data, are presented. The results show improvement in the predictive skill of the model solution due to the proper inclusion of model errors in the data assimilation. © 2012. American Geophysical Union. All Rights Reserved.