RADHAZ: A RADiation Belt HAZard Model

The rapid expansion of space assets and their susceptibility to the harsh radiation environment of the Van Allen radiation belts poses significant risk to a variety of commercial and military capabilities. As evidence of the government’s concern, the National Defense Strategy cites a key aspect to our deterrence is through resiliency in all domains, but as it relates to this STTR call, resiliency in the space domain. Current operational capabilities in forecasting hazardous environmental conditions focus primarily on the geostationary orbit where there is a continued energetic particle monitoring presence. However, the outer-radiation belts span a much larger space and while the number of satellites orbiting in this area is lower, the dynamics of this region belts can influence both geostationary (GEO) and low-Earth (LEO) orbits. We propose to utilize the Los Alamos National Laboratory (LANL) publicly released energetic particle dataset [1] in combination with other operational datasets (e.g. NOAA GOES data) to build upon previous research and provide a data-driven prediction model the capitalizes on recent progress both in space environment research and machine learning (ML) capabilities. Previous work using GPS data combined with ML techniques have shown good results [] and this effort provides an opportunity to push those efforts further and produce a model capable of predicting hazardous electron fluxes in Phase I. These predictions are viewed as a basis to understand where deficiencies may lie and the starting point for a Phase II effort to decrease error and formalize the ability of our model to perform in a real-time, and operational setting. The LANL energetic particle data provides the largest (> 300 satellite-years of data) and most dense space-based electron database available and has been shown to give comparable results to other scientific space instrumentation.  Being distributed over six orbital planes offers unparalleled sampling of the full outer radiation belts across a wide range of McIlwain L shell. Further, as an Air Force program of record the energetic particle monitoring onboard GPS satellites will continue for decades to provide a reliable source of operational data. By partnering with scientists from LANL we benefit not only from their expertise as the GPS energetic particle dataset owners, but also decades of space physics work including predictive and data assimilation models of the radiation belts.