Abstract
Aims: The semi-empirical Drag Temperature Models (DTM) predict the Earth’s thermosphere’s temperature, density, and composition, especially for orbit computation purposes. Two new models were developed in the framework of the H2020 Space Weather Atmosphere Models and Indices (SWAMI) project. The operational model is driven by the trusted and established F10.7 andKpindices for solar and geomagnetic activity. The so-called research model is more accurate, but it uses the indices F30 and the hourly Hpo, which are not yet accredited operationally.Methods: The DTM2020 models’ backbone comprises GOCE, CHAMP, and Swarm A densities, processed by TU Delft, and Stella processed in-house. They constitute the standards for absolute densities, and they are 20–30% smaller than the datasets used in the fit of DTM2013. Also, the global daily mean TLE densities at 250 km, spanning four solar cycles, were now used to improve solar cycle variations. The operational model employs the same algorithm as DTM2013, which was obtained through fitting all data in our database from 1967 to 2019. Because of the Hpo index, which is not available before 1995, the coefficients linked to the geomagnetic activity of the research model are fitted to data from 2000 to 2019. The algorithm was updated to take advantage of the higher cadence of Hpo. Both models are assessed with independent data and compared with the COSPAR International Reference Atmosphere models NRLMSISE-00, JB2008, and DTM2013. The bias and precision of the models are assessed through comparison with observations according to published metrics on several time scales. Secondly, binning of the density ratios are used to detect specific model errors.Results: The DTM2020 densities are on average 20–30% smaller than those of DTM2013, NRLMSISE-00, and JB2008. The assessment shows that the research DTM2020 is the least biased and most precise model compared to assimilated data. It is a significant improvement over DTM2013 under all conditions and at all altitudes. This is confirmed by the comparison with independent SET HASDM density data. The operational DTM2020 is always less accurate than the research model except at 800 km altitude. It has comparable or slightly higher precision than DTM2013, despite using F10.7 instead of F30 as solar activity driver. DTM, and semi-empirical models in general, can still be significantly improved on the condition of setting up a more complete and consistent total density, composition, and temperature database than available at this time by means of a well-conceived observing system.
Highlights
A major application of semi-empirical thermosphere specification models is in the computation of the atmospheric drag force in the orbit determination and prediction of spacecraft as well as debris
The thermosphere operational and research Drag Temperature Model (DTM2020) models were developed in the framework of the Space Weather Atmosphere Models and Indices (SWAMI) project, which was
The main objectives of the SWAMI project were updating the DTM2013 thermosphere model (Bruinsma, 2015), extending the upper bound of the altitude range covered by the Met Office Unified Model (MO-UM), creation of a whole atmosphere model by blending of MO-UM output with DTM2020, and taking advantage of the new high-cadence driver for geomagnetic activity Hpo (Jackson et al, 2020)
Summary
A major application of semi-empirical thermosphere specification models is in the computation of the atmospheric drag force in the orbit determination and prediction of spacecraft as well as debris. The models provide low spatial and temporal resolution average (climatological) predictions of the main constituents’ temperature, total and partial densities as a function of location (altitude, latitude, longitude, local solar time), solar and geomagnetic activity, and season. The thermosphere operational and research Drag Temperature Model (DTM2020) models were developed in the framework of the Space Weather Atmosphere Models and Indices (SWAMI) project (http://swami-h2020.eu), which was.
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