Massive multi-mission statistical study and analytical modeling of the
Earth’s magnetopause: 1 - A gradient boosting based automatic detection
of near-Earth regions
- Gautier Nguyen,
- Nicolas Aunai,
- Bayane Michotte de Welle,
- Alexis Jeandet,
- Benoit Lavraud,
- Dominique Fontaine
Benoit Lavraud
Institut de Recherche en Astrophysique et Planetologie - CNRS
Author ProfileDominique Fontaine
Laboratoire de Physique des Plasmas (LPP/CNRS), Paris, France
Author ProfileAbstract
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.Jan 2022Published in Journal of Geophysical Research: Space Physics volume 127 issue 1. 10.1029/2021JA029773