Abstract
We present an automatic classification method of the three near-Earth regions, the magnetosphere, the magnetosheath and the solar wind from their in situ data measurement by multiple spacecraft. Based on gradient boosting classifier, this very simple and very fast method outperforms the detection routines based on manually set thresholds. The method is used to identify 15,062 magnetopause crossings and 17,227 bow shock crossings in the data of 11 different spacecraft of the THEMIS, ARTEMIS, Cluster, MMS, and Double Star missions and for a total of 83 cumulated years. These multi-mission catalogs are easily reproducible, can be automatically enlarged with additional data and their elaboration paves the way for future massive statistical analysis of near-Earth boundaries.
| Original language | English |
|---|---|
| Article number | e2021JA029773 |
| Journal | Journal of Geophysical Research: Space Physics |
| Volume | 127 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Jan 2022 |
Keywords
- bow shock
- machine learning
- magnetopause
- magnetosphere
- solar wind
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