Open Access
The Impact of Assimilating Ionosphere and Thermosphere Observations on Neutral Temperature Improvement: Observing System Simulation Experiments Using EnKF
Author(s) -
He Jianhui,
Yue Xinan,
Ren Zhipeng
Publication year - 2021
Publication title -
space weather
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.254
H-Index - 56
ISSN - 1542-7390
DOI - 10.1029/2021sw002844
Subject(s) - thermosphere , data assimilation , ensemble kalman filter , ionosphere , environmental science , kalman filter , satellite , total electron content , atmospheric sciences , meteorology , extended kalman filter , physics , computer science , geophysics , tec , astronomy , artificial intelligence
Abstract Accurate specification of the thermosphere states is crucial to the low Earth orbit satellite operation. In this work, the impact of different ionosphere and thermosphere observing systems on the improvement of neutral temperature of the data assimilation model has been investigated by a series of observing system simulation experiments. The selected observations include the Global Navigation Satellite System total electron content (e.g., MIT vertical total electron content [VTEC]) and the daytime Global‐scale Observations of the Limb and Disk (GOLD) level‐2 disk temperature ( T disk ). Such observations are ingested into the coupled ionosphere and thermosphere model based on our developed ensemble Kalman Filter data assimilation systems on the basis of the ensemble Kalman filter algorithm and the National Center for Atmospheric Research Thermosphere Ionosphere Electrodynamics General Circulation Model. The main findings are as follows: (a) A considerable improvement of the neutral temperature estimation of the physical‐based model can be obtained in the global region by assimilating either the MIT VTEC or the GOLD T disk observations; (b) the assimilation of the GOLD can further contribute to temperature improvement in the lower thermosphere (<200 km), relative to the MIT VTEC assimilation; and (c) simultaneously assimilating both observation types can better improve the quality of neutral temperature estimation over the global area during the whole data assimilation process. The current results demonstrate that assimilating GOLD observations is important to improve the forecast capability of the physical‐based model for the lower thermosphere states and can provide a possible reference for the joint assimilation of the ionosphere and thermosphere observations to better thermosphere specification.