An Ensemble Kalman Filter for the Thermosphere‐Ionosphere. Issue 1 (18th January 2018)

• Record Type: Journal Article
• Authors: Codrescu, S. M.; Codrescu, M. V.; Fedrizzi, M.
• Is Part Of: Space weather. Volume 16:Issue 1(2018)
• Page Start: 57
• Page End: 68
• Publication Date: 2018-01-18
• Subjects: Ensemble Kalman Filter -- data assimilation -- thermosphere -- ionosphere -- CTIPe -- neutral density; Space environment -- Periodicals; 551.509992
• DOI: 10.1002/2017SW001752
• Languages: English
• ISSNs: 1542-7390

Abstract

Abstract: A principal limitation of physics‐based modeling in the Thermosphere‐Ionosphere system is the large uncertainty associated with the implementation of the external forcing of the system, including high‐latitude convection and particle precipitation, solar UV/EUV fluxes, and waves propagating from below. As measuring these quantities with sufficient spatial and temporal resolution is prohibitively costly, a more practical approach to improve model results is to assimilate more readily available measurements of the system. We discuss considerations in implementing an Ensemble Kalman Filter (EnKF) for a strongly forced system versus a chaotic system, overview an EnKF implementation for the strongly forced Coupled Thermosphere, Ionosphere, Plasmasphere, and Electrodynamics model, and present encouraging improvements to neutral density specification obtained by assimilating Challenging Minisatellite Payload (CHAMP) neutral density measurements. The model results show improvement in comparisons with both CHAMP and Gravity Recovery and Climate Experiment (GRACE) measurements during a geomagnetically quiet period at solar minimum. Key Points: Improved Thermospheric neutral density specification using an Ensemble Kalman Filter for quiet conditions An ensemble distributed via randomized forcing produces sufficient covariance for assimilation in quiet conditions Covariance localization unnecessary for an ensemble distributed via randomized system forcing