Abstract
This review focusses strictly on existing plasma density models, including ionospheric source models, empirical density models, physics-based and machine-learning density models. This review is framed in the context of radiation belt physics and space weather codes. The review is limited to the most commonly used models or to models recently developed and promising. A great variety of conditions is considered such as the magnetic local time variation, geomagnetic conditions, ionospheric source regions, radial and latitudinal dependence, and collisional vs. collisionless conditions. These models can serve to complement satellite observations of the electron plasma density when data are lacking, are for most of them commonly used in radiation belt physics simulations, and can improve our understanding of the plasmasphere dynamics.
| Original language | English |
|---|---|
| Article number | 1096595 |
| Journal | Frontiers in Astronomy and Space Sciences |
| Volume | 10 |
| DOIs | |
| State | Published - 2023 |
Funding
NSF-GEM grant 2040708. NASA grant 80NSSC20K1324. Horizon 2020 PITHIA-NRF grant agreement No. 101007599. EURAMET’s European Partnership on Metrology project 21GRD02 BIOSPHERE. US DOE DE-AC05-00OR22725. LANL project 20220453ER, ANR ASTRID project “PACTE-ESPACE”. The authors thank the EFW and EMFISIS teams of the Van Allen Probes mission for their support. This research was supported by the International Space Science Institute (ISSI) in Bern, through ISSI International Team project #477 (Radiation Belt Physics From Top To Bottom: Combining Multipoint Satellite Observations And Data Assimilative Models To Determine The Interplay Between Sources And Losses). The work of J-FR and GC was performed under the auspices of an agreement between CEA/DAM (Commissariat a l’Energie Atomique, Direction des Applications Militaires) and NNSA/DP (National Nuclear Security Administration, Defense Program) on cooperation on fundamental science. J-FR thank the Direction Générale de l’Armement (DGA) and the Agence pour l’Innovation de Défense (AID) for funding the ASTRID project “PACTE-ESPACE”. DH, GC, and J-FR acknowledge NSF-GEM grant 2040708. DH acknowledges NASA grant 80NSSC20K1324. VP acknowledges the Horizon 2020 PITHIA-NRF grant agreement No. 101007599 and the EURAMET’s European Partnership on Metrology project 21GRD02 BIOSPHERE. SD acknowledges support by the US DOE under contracts DE-AC05-00OR22725. GD was supported by the Laboratory Directed Research and Development program at Los Alamos National Laboratory (LANL) under project 20220453ER.
Keywords
- electron density
- empirical models
- machine learning
- physical models
- plasmapause
- plasmasphere
- radiation belts