Abstract
AbstractWe present the recent progress in upgrading a predictive model for megaelectron‐volt (MeV) electrons inside the Earth's outer Van Allen belt. This updated model, called PreMevE 2.0, provides improved forecasts, particularly at outer L‐shells, by adding upstream solar wind speeds to the model's input parameter list that originally includes precipitating electrons observed at low Earth orbits and MeV electron fluxes in situ measured by a geosynchronous satellite. Furthermore, based on several kinds of linear and artificial neural networks algorithms, a list of models was constructed, trained, validated, and tested with 42‐month MeV electron observations from Van Allen Probes. Out‐of‐sample test results from these models show that, with optimized model hyperparameters and input parameter combinations, the top performer from each category of models has the similar capability of making reliable 1‐day (2‐day) forecasts of 1‐MeV electron flux distributions with performance efficiency values ~0.87 (~0.82) averaged over the L‐shell range of 2.8–6.6, significantly outperforming the previous version of PreMevE particularly at L‐shells > ~4.5. Interestingly, the linear regression model is often the most successful when compared to other models, which suggests the relationship between dynamics of trapped 1‐MeV electrons and precipitating electrons is dominated by linear components. Results also show that PreMevE 2.0 can reasonably well predict the onsets of MeV electron events in 2‐day forecasts. PreMevE 2.0 is designed to be driven by observations from longstanding space infrastructure to make high‐fidelity forecasts for MeV electrons, thus can be an invaluable space weather forecasting tool for the future.
Highlights
Man-made satellites operating in medium- and high-altitude Earth orbits are continuously exposed to hazardous space radiation originated from different sources
The linear regression model is often the most successful one when compared to other models, which suggests the relationship between dynamics of trapped 1 MeV electrons and precipitating electrons is dominated by linear components
For 2-day forecasts, LinearReg Performance Efficiency (PE) value in Table 3 suggests that 2-day forecasts from LinearReg model are close to 1-day forecasts from linear2, which can be seen from the entangled LinearReg and linear2 curves as in Panels D-F
Summary
Man-made satellites operating in medium- and high-altitude Earth orbits are continuously exposed to hazardous space radiation originated from different sources. One major contributor is the relativistic electron population—with energies comparable to and/or larger than their rest energy of 0.511 Megaelectron-volt (MeV)—trapped inside Earth’s outer Van Allen belt. Owning to their high penetration capability, these MeV electrons are difficult to be fully stopped by normal shielding. Chen et al (2019) has developed and verified a new predictive MeV electron model called PreMevE to forecast MeV electron events throughout the whole outer radiation belt, using simple linear filters with inputs mainly from low-Earth-orbit (LEO) observations. We further improve PreMevE model by applying and testing several supervised machine learning algorithms with optimized selection of input parameters
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