Statistics – Applications
Scientific paper
May 2007
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007agusmsm52a..04s&link_type=abstract
American Geophysical Union, Spring Meeting 2007, abstract #SM52A-04
Statistics
Applications
2716 Energetic Particles: Precipitating, 2720 Energetic Particles: Trapped, 2753 Numerical Modeling, 3315 Data Assimilation, 4260 Ocean Data Assimilation And Reanalysis (3225)
Scientific paper
Data assimilation models combine measurements and first principles models to provide the most realistic possible picture of the present condition or updates and corrections to the propagation of conditions forward in time. The Kalman filter incorporates measurements and physics based model according to underlined error structure of the model and data. It provides a powerful framework to estimate the state of the system in a way that minimizes mean of the squared errors. In particular for applications in the radiation belts, data at different L- shells can be combined with the model and will affect the forecasted fluxes at all radial locations. We present analysis of the phase space density measured on CRRES using Kalman filter and the radial diffusion model. The results indicate the presence of the local acceleration source at L~5.5. We also present results of the parameter estimation using extended Kalman filtering.
Chen Yafeng
Ghil Michael
Kondrashov Dmitry A.
Shprits Yuri Y.
Thorne Robert
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