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Massive Multi‐Mission Statistical Study and Analytical Modeling of the Earth's Magnetopause: 1. A Gradient Boosting Based Automatic Detection of Near‐Earth Regions

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.
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https://hal-cnrs.archives-ouvertes.fr/hal-03841293
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Submitted on : Monday, November 7, 2022 - 9:32:42 AM
Last modification on : Tuesday, November 15, 2022 - 3:36:02 PM

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G. Nguyen, N. Aunai, B. Michotte de Welle, Alexis Jeandet, B. Lavraud, et al.. Massive Multi‐Mission Statistical Study and Analytical Modeling of the Earth's Magnetopause: 1. A Gradient Boosting Based Automatic Detection of Near‐Earth Regions. Journal of Geophysical Research Space Physics, 2022, 127 (1), pp.e2021JA029773. ⟨10.1029/2021JA029773⟩. ⟨hal-03841293⟩

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