Abstract
We consider a data assimilation technique for coupled ionospheric and thermospheric dynamics. The Global Ionosphere-Thermo-sphere Model (GITM) is used to simulate the ionospheric and thermospheric dynamics, and evaluate the performance of the data assimilation scheme that estimates the ion densities and flow speeds. This estimation technique is based on the state dependent Riccati equation (SDRE), which uses a frozen linear dynamics matrix for the time update of the error covariance and the evaluation of the Kalman filter gain. We demonstrate the performance of the data assimilation technique on a section of the ionosphere.
This research was supported by the National Science Foundation under grants CNS-0539053 and ATM-0325332.
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© 2006 Springer-Verlag Berlin Heidelberg
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Kim, I.S., Chandrasekar, J., Ridley, A., Bernstein, D.S. (2006). Data Assimilation Using the Global Ionosphere-Thermosphere Model. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science – ICCS 2006. ICCS 2006. Lecture Notes in Computer Science, vol 3993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11758532_65
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DOI: https://doi.org/10.1007/11758532_65
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