Abstract

Solar irradiance is the dominant source of heat, ionization, and dissociation of the thermosphere, and to a large extent drives the global dynamics, and controls the neutral composition and density structure. Neutral composition is important for space weather applications because of its impact on ionospheric loss rates, and neutral density is critical for satellite drag prediction. Recent observations from the Global Ultraviolet Imager (GUVI) instrument on the TIMED satellite depict the global distribution of neutral species; in particularly, the ratio of the height-integrated atomic oxygen to molecular nitrogen. The global circulation controls the neutral species composition structure, which in turn is very dependent on the balance between solar heating at the lower latitudes, and magnetospheric forcing at high latitudes. The observed latitude structure of O/N 2 therefore imposes constraints on external sources of energy to the thermosphere–ionosphere system, and is valuable information for use in physical models. One of the uses of thermospheric general circulation models for space weather operations lies in their utility as state propagators in data assimilation techniques. The physical models can match empirical models in accuracy provided accurate drivers are available, but their true value comes when combined with data in an optimal way. Recent results show that using a physical model within a data assimilation system is only beneficial if accurate drivers of the model are available. The use of O/N 2 data to tune the model forcing is therefore particularly important in the context of the recent development of a Kalman filter data assimilation model for use within the Global Assimilation of Ionospheric Measurement (GAIM) program. The need for adequate drivers is just as relevant in the application to neutral density, for satellite orbit prediction and re-entry estimation. Both applications rely on accurate estimates of the solar EUV and magnetospheric drivers.

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