A Machine‐Learning‐Based Global Thermospheric Density Forecasting Model

Abstract Thermospheric mass density governs aerodynamic drag in low Earth orbit and is a primary source of uncertainty in orbit prediction and conjunction assessment, particularly during geomagnetic disturbances. We present AETHER‐P3 (Accelerometer‐driven Estimation of THERmospheric density–A Physic...

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書誌詳細

主要な著者:	Ruochen Wang, Xiaoli Bai
フォーマット:	Artigo
言語:	Inglês
出版事項:	Wiley 2026-06-01
シリーズ:	Space Weather
主題:	machine learning thermospheric density density forecasting uncertainty estimation space weather physics‐informed framework
オンライン･アクセス:	https://doi.org/10.1029/2026SW004968
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