Assessing the performance of thermospheric modeling with data assimilation throughout solar cycles 23 and 24

• Published in: Space Weather Vol. 13; no. 4; p. 220
• Main Authors: Murray, S A, Henley, E M, Jackson, D R, Bruinsma, S L
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 01.04.2015
• Subjects: Data assimilation; General circulation models; Solar cycle
• ISSN: 1539-4964; 1542-7390
• DOI: 10.1002/2015SW001163

Data assimilation procedures have been developed for thermospheric models using satellite density measurements as part of the EU Framework Package 7 Advanced Thermosphere Modelling of Orbital Prediction project. Two models were studied: one a general circulation model, Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM), and the other a semiempirical drag temperature model, Drag Temperature Model (DTM). Results of runs using data assimilation with these models were compared with independent density observations from CHAMP and GRACE satellites throughout solar cycles 23 and 24. Time periods of 60days were examined at solar minimum and maximum, including the 2003 Hallowe'en storms. The differences between the physical and the semiempirical models have been characterized. Results indicate that both models tend to show similar behavior; underestimating densities at solar maximum and overestimating them at solar minimum. DTM performed better at solar minimum, with both models less accurate at solar maximum. A mean improvement of 4% was found using data assimilation with TIEGCM. With further improvements, the use of general circulation models in operational space weather forecasting (in addition to empirical methods currently used) is plausible. Future work will allow near-real-time assimilation of thermospheric data for improved forecasting. Key Points Data assimilation methods developed for thermospheric models Model results compared to satellite observations at solar max and min Data assimilation improved general circulation model by 4%