Preprints
https://doi.org/10.5194/egusphere-2024-3177
https://doi.org/10.5194/egusphere-2024-3177
28 Oct 2024
 | 28 Oct 2024
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

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

Guanyi Ma and Klemens Hocke

Abstract. A sudden stratospheric warming is a breakdown of winter stratospheric polar vortex. It has atmospheric effects in both the Northern and Southern hemispheres, leading to disturbances in the whole ionosphere. Previous works with case studies have shown that SSW effect is mainly in low-latitude ionosphere and each SSW event may have a different effect on the ionosphere due to complex dynamics from solar/geomagnetic activities and seasonal changes. However, the SSW induced tidal variability in mid to high-latitude ionosphere is only identified for several events and its behaviour is not well understood. Here we analyze SSWs’ influences on diurnal/semidiurnal variations of global ionosphere with the global maps of total electron content (TEC) from 1998 to 2022. We use machine learning (ML) with neural network to establish the TEC (ML-TEC) model related to the solar/geomagnetic activities and seasonal change from the long-term global TEC data. The TEC variations due to SSWs are extracted by subtracting the ML-TEC from the observed TEC. Comprehensive composite analysis of 18 SSW events shows for the first time a globally SSW-induced enhancement in diurnal/semidiurnal TEC variations. The enhancement is the strongest at equatorial ionospheric anomaly (EIA) crests, moderate in mid-latitude and vague in high-latitude ionosphere. It also exhibits hemispheric asymmetry and longitudinal differences. While the semidiurnal enhancement starts earlier and peaks at ~8 days after SSW onset, the diurnal one starts on the SSW onset day and peaks around 20–30 days after SSW onset. The enhancement of both semidiurnal and diurnal TEC variations lasts to about 50 days 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 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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Guanyi Ma and Klemens Hocke

Status: open (until 06 Jan 2025)

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Guanyi Ma and Klemens Hocke
Guanyi Ma and Klemens Hocke

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Short summary
We analyze the influences of sudden stratospheric warming (SSW) on diurnal/semidiurnal variations of ionosphere with the global total electron content (TEC) from 1998 to 2022. We use machine learning (ML) to establish the TEC (ML-TEC) model related to the solar/geomagnetic activities and seasonal change from the TEC data. Subtracting the ML-TEC from the observed TEC, we find a globally SSW-induced enhancement in diurnal/semidiurnal TEC variations.