In 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 (
This study develops a new Bubble Index to quantify the intensity of 2‐D postsunset equatorial plasma bubbles (EPBs) in the American/Atlantic sector, using Global‐scale Observations of the Limb and Disk (GOLD) nighttime data. A climatology and day‐to‐day variability analysis of EPBs is conducted based on the newly‐derived Bubble Index with the following results: (a) EPBs show considerable seasonal and solar activity dependence, with stronger (weaker) intensity around December (June) solstice and high (low) solar activity years. (b) EPBs exhibit opposite geomagnetic activity dependencies during different storm phases: EPBs are intensified concurrently with an increasing Kp, but are suppressed with high Kp occurring 3–6 hr earlier. (c) For the first time, we found that EPBs' day‐to‐day variation exhibited quasi‐3‐day and quasi‐6‐day periods. A coordinated analysis of Ionospheric Connection Explorer (ICON) winds and ionosonde data suggests that this multi‐day periodicity was related to the planetary wave modulation through the wind‐driven dynamo.
more » « less- NSF-PAR ID:
- 10409245
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 50
- Issue:
- 8
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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