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Abstract We investigate the applicability and performance of the plasma physics based WINDMI model to the analysis and identification of substorm onsets. There are several substorm onset criteria that have been developed into event lists, either from auroral observations or from auroral electrojet features. Five of these substorm onset lists are available at the SuperMAG website. We analyze these lists, aggregate them and use the WINDMI model to assess the identified events, emphasizing the loading/unloading mechanism in substorm dynamics. The WINDMI model employs eight differential equations utilizing solar wind data measured at L1 by the ACE satellite as input to generate outputs such as the magnetotail current, the ring current and the field‐aligned currents (FACs). In particular, the WINDMI model current output represents the westward auroral electrojet, which is related to the substorm SML index. We analyze a decade of solar wind and substorm onset data from 1998 to 2007, encompassing 39,863 onsets. Our findings reveal a significant correlation, with WINDMI‐derived enhancements in FAC coinciding with the identified substorm events approximately 32% of the time. This suggests that a substantial proportion of substorms may be attributed to solar wind driving that results in the loading and unloading of energy in the magnetotail.
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Statistical Analysis of Substorm Events Using the WINDMI Model
The SuperMAG magnetic index called the SML index characterizes variations in the Earth's magnetic field due to significant external geomagnetic activities resulting from substorms. This index serves as a crucial parameter for detecting substorm onsets, as utilized by several authors ([1]–[5]). The outputs from the low-order physics-based model WINDMI can also be employed to analyze substorm onsets. In this paper, we evaluate the outputs from the model against the aforementioned techniques to derive criteria for the field-aligned current (FAC) I 1 and its time derivative, both of which are outputs from the model. These criteria hold potential significance in predicting substorm onsets from solar wind data.
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- PAR ID:
- 10549716
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-1710-7
- Page Range / eLocation ID:
- 1151 to 1156
- Format(s):
- Medium: X
- Location:
- Atlanta, GA, USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/SoutheastCon52093.2024.10500052
