Forecasting and Monitoring of Key Geospace Parameters

Details Forecasting and Monitoring of Key Geospace Parameters Forecasting and Monitoring of Key Geospace Parameters

May 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009agusmsh31a..01k&link_type=abstract

American Geophysical Union, Spring Meeting 2009, abstract #SH31A-01

Physics

2716 Energetic Particles: Precipitating, 2722 Forecasting (7924, 7964)

Scientific paper

The relatively simple but highly-reliable method of modeling of the energetic particles in the Earth's magnetosphere has been developed. This method does not need the special distribution of the variety of specific mechanisms for particle acceleration and their losses, but needs the average time-dependent values of the main sources and losses of these particles. Dependently of the problem under investigation, we solve one or several linked particle balance equations. The coefficients, entering the equations, are found using an optimization method, providing the best fit between the forecasted and actual data. We will demonstrate how this method works for prediction of relativistic electrons at geostationary orbit, and Dst disturbances. In both cases, our method gives extremely high correlation between forecasted and actual magnitudes of the particle fluxes. For instance, we predict the Dst variation for 1-3 hour ahead with correlation coefficient between predicted and actual data to be ~0.9 and more, and predict the relativistic electron fluxes at geosynchronous orbit for one day ahead with the correlation coefficient of about 0.92. Also using the new coupling function and new geomagnetic activity index, PM, we have developed an effective method for near-real-time monitoring the key ionospheric parameters such as the cross-polar-cap potential drop and Joule heating. The computed results are compared with the AMIE model and DMSP satellite observations.

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