Comprehensive Loss and Acceleration Process Identification with Data Assimilation of LWS TR&T Storm on October 25, 2002

Details Comprehensive Loss and Acceleration Process Identification with Data Assimilation of LWS TR&T Storm on October 25, 2002 Comprehensive Loss and Acceleration Process Identification with Data Assimilation of LWS TR&T Storm on October 25, 2002

Dec 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006agufmsm43b1500k&link_type=abstract

American Geophysical Union, Fall Meeting 2006, abstract #SM43B-1500

Physics

2740 Magnetospheric Configuration And Dynamics, 2772 Plasma Waves And Instabilities (2471), 2774 Radiation Belts, 2778 Ring Current, 2788 Magnetic Storms And Substorms (7954)

Scientific paper

Acceleration and loss processes in the radiation belt during geomagnetic storms are important to understand because they are the cause for very dynamic variations threatening our space assets. Moreover, these competing processes have still many open scientific questions. We will present a comprehensive study of a storm on October 25, 2002 that was chosen by the LWS TR&T team for detailed investigation. We use a radiation belt model based on radial diffusion and assimilate multi satellite data compensating for source and loss processes that are, on purpose, absent in the model. This data assimilation technique, with an ensemble Kalman filter at its core, allows us to identify regions and time periods where the model is significantly drifting away from the data enabling us to identify distinctive loss and acceleration periods that cannot be explained by simple radial diffusion. We compare these results with wave excitation predictions from the kinetic ring current model RAM. Specifically we will correlate the time periods of EMIC and whistler chorus wave excitation with the time periods of missing losses and/or accelerations as predicted from the assimilative radiation belt model. It is difficult, if not impossible, to differentiate the various physical processes in the radiation belt and when and where they are acting by studying data and models alone. However, combining data with models with an advanced data assimilation method can facilitate a better physical understanding of the competing processes (acceleration, loss, and transport) in the radiation belt.

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