Forecast of the Energetic Electron Environment of the Radiation Belts

Different modeling methodologies possess different strengths and weakness. For instance, data based models may provide superior accuracy but have a limited spatial coverage while physics based models may provide lower accuracy but provide greater spatial coverage. This study investigates the coupling of a data based model of the electron fluxes at geostationary orbit (GEO) with a numerical model of the radiation belt region to improve the resulting forecasts/pastcasts of electron fluxes over the whole radiation belt region. In particular, two coupling methods are investigated. The first assumes an average value for L* for GEO, namely L-GEO* = 6.2. The second uses a value of L* that varies with geomagnetic activity, quantified using the Kp index. As the terrestrial magnetic field responds to variations in geomagnetic activity, the value of L* will vary for a specific location. In this coupling method, the value of L* is calculated using the Kp driven Tsyganenko 89c magnetic field model for field line tracing. It is shown that this addition can result in changes in the initialization of the parameters at the Versatile Electron Radiation Belt model outer boundary. Model outputs are compared to Van Allen Probes MagEIS measurements of the electron fluxes in the inner magnetosphere for the March 2015 geomagnetic storm. It is found that the fixed L-GEO* coupling method produces a more realistic forecast. Plain Language Summary Significant increases in the number of energetic electrons within the radiation belts can pose a threat to satellites operating in the vicinity of geostationary orbit (GEO). Their existence can result in wide ranging effects from the disruption of operations to the complete loss of a satellite. Therefore, it is of vital importance to create accurate models for the forecast of the energetic electron environment. Generally speaking, there are two modeling methodologies used. One method creates highly accurate models from data, collected, for example, at GEO. Such models, however, are only valid in the region in which the measurements were made. The second uses simulations that, although less accurate than data-based models, are capable of tracking changes over large volumes of space. In this study, we investigate two methods for the coupling of a data-based and a numerical model to generate accurate forecasts of the electron dynamics within the whole inner magnetosphere. The first coupling method uses a set of fixed parameters to yield more realistic forecasts.