Effects of sudden stratospheric warmings on the global ionospheric total electron content using a machine learning analysis

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Abstract

A sudden stratospheric warming (SSW) is a breakdown of the winter stratospheric polar vortex. It has atmospheric effects in both the Northern Hemisphere and Southern Hemisphere, leading to disturbances in the whole ionosphere. Previous case studies have shown that SSW effects are observed mainly in the low-latitude ionosphere, and each SSW event may have a different effect on the ionosphere due to complex dynamics from solar and geomagnetic activities and seasonal changes. However, the SSW-induced tidal variability in the mid- to high-latitude ionosphere is only identified for several events, and its behaviour is not well understood. Here we analyse major SSW influences on diurnal/semidiurnal variations of the global ionosphere with global maps of total electron content (TEC) from 1998 to 2022. We use machine learning (ML) with neural networks to establish the TEC (ML-TEC) model related to the solar/geomagnetic activities and seasonal changes from the long-term global TEC data. The TEC variations due to SSWs are extracted by subtracting the ML-TEC from the observed TEC. A comprehensive composite analysis of 18 major SSW events shows for the first time a globally SSW-induced enhancement in diurnal/semidiurnal TEC variations. The enhancement is strongest at equatorial ionospheric anomaly (EIA) crests, moderate at midlatitudes, and vague in the high-latitude ionosphere. It also exhibits hemispheric asymmetry and longitudinal differences. While the semidiurnal enhancement starts earlier and peaks at ∼8d after SSW onset, the diurnal one starts on the SSW onset day and peaks around 20-30 d after SSW onset. The enhancement of both semidiurnal and diurnal TEC variations lasts for about 20-50 d after SSW onset. The SSW-related E-region dynamo is likely the dominant mechanism, which is not strong enough to produce discernible TEC variations in the high-latitude ionosphere. ML-TEC does not contain the SSW effect and is thus a valuable reference for the ionospheric state without an SSW.

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Ma, G., & Hocke, K. (2025). Effects of sudden stratospheric warmings on the global ionospheric total electron content using a machine learning analysis. Atmospheric Chemistry and Physics, 25(9), 5009–5020. https://doi.org/10.5194/acp-25-5009-2025

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