Evaluation of SaRIF high-energy electron reconstructions and forecasts

Glauert, S.A. ORCID: https://orcid.org/0000-0003-0149-8608; Horne, R.B. ORCID: https://orcid.org/0000-0002-0412-6407; Kirsch, P. ORCID: https://orcid.org/0000-0003-2482-0217. 2021 Evaluation of SaRIF high-energy electron reconstructions and forecasts. Space Weather, 19 (12), e2021SW002822. 21, pp. 10.1029/2021SW002822

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Official URL: https://agupubs.onlinelibrary.wiley.com/doi/10.102...

Abstract/Summary

Increasing numbers of satellites are orbiting through the Earth's radiation belts, and the range of orbits being commonly used is also growing. As a result, there is an increasing need for services to help protect satellites from space weather. The Satellite RIsk prediction and radiation Forecast (SaRIF) system provides reconstructions and forecasts of the high-energy electron flux throughout the outer radiation belt and translates these predictions into charging currents, dose rates, total ionizing dose and risk indicators. SaRIF both informs satellite operators of current and expected conditions and provides a tool to aid in post-event analysis. The reconstructions and forecasts are provided by the British Antarctic Survey Radiation Belt Model (BAS-RBM) running as part of an automatic system using real-time data to specify the boundary conditions and drive processes within the physics-based model. If SaRIF is to provide a useful tool, then the accuracy of the reconstructions and forecasts needs to be understood. Here we assess the accuracy of the simulations for geostationary orbit by comparing the model output with measurements made by the GOES 14 spacecraft for the period March–September 2019. No GOES 14 data was used to create the reconstruction or forecasts. We show that, with some improvements to the original system, the reconstructions have a prediction efficiency of 0.82 for >800 keV electrons and 0.87 for >2 MeV electrons, with corresponding prediction efficiencies of 0.59 and 0.78 for the forecasts.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1029/2021SW002822
ISSN:	15427390
Additional Keywords:	forecast, reconstruction, SaRIF, evaluation
Date made live:	10 Dec 2021 10:58 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/530544

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1029/2021SW002822

ISSN:

15427390

Additional Keywords:

forecast, reconstruction, SaRIF, evaluation

Date made live:

10 Dec 2021 10:58 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/530544