This study is focused on improving the poorly understood seasonal dependence of northern high-latitude F region thermospheric winds under active geomagnetic conditions. The gaps in our understanding of the dynamic high-latitude thermosphere are largely due to the sparseness of thermospheric wind measurements. With current observational facilities, it is infeasible to construct a synoptic picture of thermospheric winds, but enough data with wide spatial and temporal coverage have accumulated to construct a meaningful statistical analysis. We use long-term data from eight ground-based and two space-based instruments to derive climatological wind patterns as a function of magnetic local time, magnetic latitude, and season. These diverse data sets possess different geometries and different spatial and solar activity coverage. The major challenge is to combine these disparate data sets into a coherent picture while overcoming the sampling limitations and biases among them. In our previous study (focused on quiet time winds), we found bias in the Gravity Field and Steady State Ocean Circulation Explorer (GOCE) cross-track winds. Here we empirically quantify the GOCE bias and use it as a correction profile for removing apparent bias before empirical wind formulation. The assimilated wind patterns exhibit all major characteristics of high-latitude neutral circulation. The latitudinal extent of duskside circulation expands almost 10^∘ from winter to summer. The dawnside circulation subsides from winter to summer. Disturbance winds derived from geomagnetic active and quiet winds show strong seasonal and latitudinal variability. Comparisons between wind patterns derived here and Disturbance Wind Model (DWM07) (which have no seasonal dependence) suggest that DWM07 is skewed toward summertime conditions.

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This paper investigates the large-scale seasonal dependence of geomagnetically quiet time, northern high-latitude F region thermospheric winds by combining extensive observations from eight ground-based (optical remote sensing) and three space-based (optical remote sensing and in situ) instruments. To provide a comprehensive picture of the wind morphology, data are assimilated into a seasonal empirical vector wind model as a function of season, latitude, and local time in magnetic coordinates. The model accurately represents the behavior of the constituent data sets. There is good general agreement among the various data sets, but there are some major offsets between GOCE and the other data sets, especially on the duskside. The assimilated wind patterns exhibit a strong and large duskside anticyclonic circulation cell, sharp latitudinal gradients in the duskside auroral zone, strong antisunward winds in the polar cap, and a weaker tendency toward a dawnside cyclonic circulation cell. The high-latitude wind system shows a progressive intensification of wind patterns from winter to equinox to summer. The latitudinal extent of the duskside circulation cell does not depend strongly on season. Zonal winds show a mainly diurnal variation (two extrema) around polar and middle latitudes and semidiurnal variation (four extrema) at auroral latitudes; meridional winds are primarily diurnal at all high latitudes. The strength of zonal winds channeling through the auroral zone on the duskside is strongest in the summer season. The vorticity of the wind pattern increases from winter to summer, whereas divergence is maximum in equinox. In all three seasons, divergence is weaker than vorticity.

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The accuracy of global atmospheric models used to predict the middle/lower thermosphere characteristics is still an open topic. Uncertainties in the prediction of the gas properties in the thermosphere lead to inaccurate computations of the drag force on space objects (i.e. satellites or debris). Currently the lifetime of space objects and therefore the population of debris in low Earth orbit (LEO) cannot be quantified with a satisfactory degree of accuracy. In this paper, the Global Ionosphere Thermosphere Model (GITM) developed at the University of Michigan has been validated in order to provide detailed simulations of the thermosphere. First, a sensitivity analysis has been performed to investigate the effect of the boundary conditions on the final simulations results. Then, results of simulations have been compared with flight measurements from the CHallenging Minisatellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE) satellites and with existing semi-empirical atmospheric models (IRI and MSIS). The comparison shows a linear dependency of the neutral density values with respect to the solar activity. In particular, GITM shows an over-predicting or under-predicting behaviour under high or low solar activity respectively. The reasons for such behaviour can be attributed to a wrong implementation of the chemical processes or the gas transport properties in the model.@en