The DTM-2000 empirical thermosphere model with new data assimilation and constraints at lower boundary: accuracy and properties

The drag temperature model (DTM) is a semi-empirical model describing the temperature, density and composition of the Earth's thermosphere. Its first version (Ann. Geophys. 34 (1978) 9) used direct measurements of exospheric temperature and atmospheric densities derived from satellite drag data. It has later been refined (J. Geodesy 72 (1998) 161). However, both models have their lower boundaries at 120 km, which are not constrained by observations. Consequently in the lower thermosphere, the modelled temperature and density structure is uncertain. For predicting satellite orbits in the lower thermosphere, more realistic density models are required. We present a new DTM model having the following improvements: (a) Temperature and its gradient at 120 km are represented in agreement with theory and observation, using incoherent scatter radar and satellite-borne interferometer data. (b) Atmosphere explorer (AE) data, which have not been assimilated in DTM-94, are used as they cover a complete solar activity cycle. (c) The Mg II index is used whenever possible to represent the solar UV and EUV emission intensity instead of the solar decimetre radio flux, since it is more representative of solar instantaneous chromospheric activity than F-10.7 is. The basic DTM mathematical representation of temperature and composition is used, with, however, some additions and modifications to take into account the variations at 120 km altitude. The temperature modelling accuracy has improved by 5-8%, and there is no model bias as a function of solar activity. The oxygen and helium modelling has improved as well, and this is demonstrated by the estimated drag scale coefficients issued from precise orbit computation. The scaling coefficients estimated using DTM-2000 are systematically closer to unity than those resulting from employing DTM-94 and MSIS-86 in the orbit computation. The minor constituents (02 and H) modelling is unchanged. The molecular nitrogen modelling is not improved, but this is, at least partly, caused by the poor data quality. Despite these improvements, semi-empirical thermosphere models still suffer of weaknesses. First, they assume a steady-state equilibrium which is not necessarily reached in any circumstances. Second, the basic process of atmospheric heating by EUV is assumed to be represented by some indices (Mg II, F-10.7), while particle precipitation is represented by an index associated to a latitude without a longitude effect (K-p), although winds that transport energy suggest this effect. Third, the data accuracy and their incomplete geographical and temporal coverage are significant sources of uncertainty. Assimilation of a long time series of data, with a complete geographical coverage, and using the Mg II index will probably increase model accuracy from the present-day RMS of 19% to 10-15%. The complete CHAMP accelerometer data set may allow the achievement of that goal after 5 years of operations in 2005. (C) 2003 Elsevier Ltd. All rights reserved.