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Abstract The auroral substorm has been extensively studied over the last six decades. However, our understanding of its driving mechanisms is still limited and so is our ability to accurately forecast its onset. In this study, we present the first deep learning‐based approach to predict the onset of a magnetic substorm, defined as the signature of the auroral electrojets in ground magnetometer measurements. Specifically, we use a time history of solar wind speed (Vx), proton number density, and interplanetary magnetic field (IMF) components as inputs to forecast the occurrence probability of an onset over the next 1 hr. The model has been trained and tested on a data set derived from the SuperMAG list of magnetic substorm onsets and can correctly identify substorms ∼75% of the time. In contrast, an earlier prediction algorithm correctly identifies ∼21% of the substorms in the same data set. Our model's ability to forecast substorm onsets based on solar wind and IMF inputs prior to the actual onset time, and the trend observed in IMFBzprior to onset together suggest that a majority of the substorms may not be externally triggered by northward turnings of IMF. Furthermore, we find that IMFBzandVxhave the most significant influence on model performance. Finally, principal component analysis shows a significant degree of overlap in the solar wind and IMF parameters prior to both substorm and nonsubstorm intervals, suggesting that solar wind and IMF alone may not be sufficient to forecast all substorms, and preconditioning of the magnetotail may be an important factor.
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Control of the East‐West Component of the Interplanetary Magnetic Field on the Occurrence of Magnetic Substorms
Abstract We study the effects of the east‐west (y) component of the interplanetary magnetic field (IMF) on the occurrence of substorms by analyzing 16,743 magnetic substorm events identified with the SuperMAGSMLindex from 1995 to 2016. It is found, surprisingly, that substorm occurrence rates depend highly on the sign of IMFBy, with, on average, ~1/3 more substorms for IMFBy> 0 than for IMFBy< 0. We attribute this asymmetry to the enhanced convection (e.g., more energy in the tail) under IMFBy> 0 conditions. A superposed epoch analysis of the IMF indicates that the average IMFByprior to onset is positive but becomes less positive ~15 min prior to the onset, indicating that the release of the stress associated with a clockwise twisted magnetotail may be an important onset trigger. We conjecture that an asymmetry in the dayside merging efficiency may be the cause.
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- Award ID(s):
- 1743118
- PAR ID:
- 10455531
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 47
- Issue:
- 5
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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