Identifying the radiation belt source region by data assimilation

We describe how assimilation of radiation belt data with a simple radial diusion code can be used to identify and adjust for unknown physics in the model. We study the drop-out and the following enhancement of relativistic electrons during a moderate storm on October 25, 2002. We introduce a technique that uses an ensemble Kalman Filter and the probability distribution of the forecast ensemble to identify if the model is drifting away from the observations and to find inconsistencies between model forecast and observations. We use the method to pinpoint the time periods and locations where most of the disagreement occurs and how much the Kalman Filter has to adjust the model state to match the observations. Although the model does not contain explicit source or loss terms, the Kalman Filter algorithm can implicitly add very localized sources or losses in order to reduce the discrepancy between model and observations. We use this technique with multi-satellite observations to determine when simple radial diusion is inconsistent with the observed phase space densities indicating where additional source (acceleration) or loss (precipitation) processes must be active. We find that the outer boundary estimated by the ensemble Kalman filter is consistent with negative phase space density gradients in the outer electron radiation belt. We also identify that specific regions in the radiation belts (L 5 6 and to a minor extend also L 4)where simple radial diusion fails to adequately capture the variability of the observations, suggesting local acceleration/loss mechanisms.

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