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COVEN: Providing a Variety of Threshold-Based Forecasts for the Outer Radiation Belt

D.J. Weston*, I.J. Rae, A.W. Smith, C.E.J. Watt

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We present a suite of VAMPIRE (Van Allen belt Multi-day Predictions by Implementing a Random Forest for Electrons) models capable of predicting if the outer radiation belt crosses set percentile thresholds. We use Random Forest classification models to predict if the daily ∼2 MeV electron flux level across the outer radiation belt exceeds thresholds from the 60th to the 95th percentiles. Most models show a balanced accuracy of >0.7 (>70%) at nowcasting and ∼0.6 (60%) at forecasting up to 6 days in advance, a longer forecast than current operational models. Using feature importance (mean decrease in impurity), we determine the key inputs that are important in driving increasing flux levels and over what timescales they have an impact. Crucially, we find that only the average AL index from various days beforehand is required to be able to forecast radiation belt fluxes with good skill, meaning that models such as these could be operationally viable for space weather stakeholders. We call this suite a Collection Of VAMPIRE models for Enhanced Notification.
Original languageEnglish
Article numbere2026SW004989
Number of pages21
JournalSpace Weather
Volume24
Issue number6
Early online date4 Jun 2026
DOIs
Publication statusPublished - Jun 2026

Keywords

  • radiation belt
  • forecasting
  • machine learning
  • random forest

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