Affiliation:
1. Mullard Space Science Laboratory University College London London UK
2. Department of Physics and Astronomy University College London London UK
3. Department of Mathematics, Physics and Electrical Engineering Northumbria University London UK
4. Department of Atmospheric and Oceanic Sciences University of California at Los Angeles (UCLA) Los Angeles CA USA
5. Haystack Observatory Massachusetts Institute of Technology Cambridge MA USA
6. Southwest Research Institute San Antonio TX USA
Abstract
AbstractIn this study we present AI Prediction of Equatorial Plasma Bubbles (APE), a machine learning model that can accurately predict the Ionospheric Bubble Index (IBI) on the Swarm spacecraft. IBI is a correlation (R2) between perturbations in plasma density and the magnetic field, whose source can be Equatorial Plasma Bubbles (EPBs). EPBs have been studied for a number of years, but their day‐to‐day variability has made predicting them a considerable challenge. We build an ensemble machine learning model to predict IBI. We use data from 2014 to 2022 at a resolution of 1s, and transform it from a time‐series into a 6‐dimensional space with a corresponding EPB R2 (0–1) acting as the label. APE performs well across all metrics, exhibiting a skill, association and root mean squared error score of 0.96, 0.98 and 0.08 respectively. The model performs best post‐sunset, in the American/Atlantic sector, around the equinoxes, and when solar activity is high. This is promising because EPBs are most likely to occur during these periods. Shapley values reveal that F10.7 is the most important feature in driving the predictions, whereas latitude is the least. The analysis also examines the relationship between the features, which reveals new insights into EPB climatology. Finally, the selection of the features means that APE could be expanded to forecasting EPBs following additional investigations into their onset.
Funder
National Aeronautics and Space Administration
National Science Foundation
Publisher
American Geophysical Union (AGU)
Subject
Space and Planetary Science,Geophysics