Challenges and Innovations in Data Assimilation for Radiation Belts

Details Challenges and Innovations in Data Assimilation for Radiation Belts Challenges and Innovations in Data Assimilation for Radiation Belts

Dec 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009agufmsm51a1331k&link_type=abstract

American Geophysical Union, Fall Meeting 2009, abstract #SM51A-1331

Physics

[2788] Magnetospheric Physics / Magnetic Storms And Substorms

Scientific paper

A striking feature of the radiation belts is that values of observed electron fluxes and modeled phase space density vary by several orders of magnitude.. This extremely wide range may present certain problems for standard data assimilation methods, such as the Kalman filter and its various implementations. In this study, we explore innovative ways to make Kalman-filter—type methods more efficient for assimilating data in the radiation belts by using a 1-D diffusion model and observations from multiple satellites. We present sensitivity simulations using synthetic data, as well as actual satellite observations using the conventional data assimilation algorithms, on the one hand, and algorithms developed in this study, on the other.

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