Background

Several different methods have been used to estimate , both directly using measurements of the wave fields, and indirectly from observations of the particles diffusion. By assuming a constant , fixed for all time independent of wave activity particle observations over long time intervals (months) have been used to obtain an indirect estimate for (Frank, 1965;Newkirk and Walt, 1968; Lanzerotti et al., 1970, Lyons and Williams, 1975, West et al., 1981; Selesnick et al., 1997). Holzworth and Mozer, (1979) used direct balloon measurements of the wave electic field at L=6 to obtain a Kp-dependent Satellite observations of the wave magnetic power spectral densities at L=4 and L=6.6 have been used to estimate . Brautigam et al., (2005), used the CRRES observations of wave electric field from L=3.0 to L=7.0 to obtained as a function of and Kp. However, these authors state that “given that it is the global structure and variability of the electric and magnetic fields that control the radiation belt particle populations, it will remain near impossible to disentangle the various competing acceleration and loss mechanisms until we can better define what those fields are doing through the deployment of multi-satellite constellations in coordination with ground stations”.

The radiation belt simulation illustrated in Figure 1 (Shprits et al., 2005), was produced using the Brautigam and Albert 2000  as an empirical function of Kp. Only diffusion due to the waves’ magnetic field was considered and the effect of radial diffusion by the waves’ electric field was ignored.

For this space weather forecast, ground-based magnetometer networks are used in conjunction with techniques for mapping the ground wave fields into the wave electric and magnetic fields in space (see e.g., Ozeke, et al., 2007) to obtain the required and diffusion coefficients that control the radiation belt dynamics. Using these diffusion coefficients the diffusion equationis solved in order to produce near real time online simulations of the radiation belt dynamics.

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