Data assimilation for neutral thermospheric species during geomagnetic storms



[1] During a geomagnetic storm, Joule heating heats the neutral gas and drives horizontally divergent winds which force upwelling of the neutral atmosphere. The heavier molecular species N2 and O2, abundant in the lower thermosphere, are transported to high altitude where they increase the loss rate of the F region ionosphere. The “bulge” of enhanced molecular species, or depleted atomic oxygen, is long-lived, returning to equilibrium mainly through the slow process of molecular diffusion. Its longevity, of the order of a day, enables the global wind system to transport the composition disturbance over thousands of kilometers, driven by the combination of quiet and storm-time wind fields. In a stand-alone physical model the formation and subsequent movement of the composition features depend on accurate specification of the spatial and temporal distribution of the Joule heating from the magnetosphere and knowledge of the time-dependent wind fields to define the transport. Neither is sufficiently well known given current observational capability. An alternative approach is to combine the knowledge contained in a physical model with observations of the thermospheric composition. It has been demonstrated that FUV images can provide a reliable estimate of the magnitude and structure of oxygen-depleted regions on the sunlit side of Earth. A Kalman filter data assimilation method has been developed to combine FUV observations with a physical model in order to optimally define the global distribution of neutral thermosphere composition. This distribution is used as one of the important drivers in a model for Global Assimilation of Ionospheric Measurements (GAIM) in order to improve specification and forecast of the response of the ionosphere to geomagnetic storms.