Ensemble Assimilation Using Three First-Principles Thermospheric Models as a Tool for 72-hour Density and Satellite Drag Forecasts

Wednesday, 17 December 2014
Don Hunton1, Marcin Pilinski1, Geoffrey Crowley1, Irfan Azeem1, Timothy J Fuller-Rowell2, Tomoko Matsuo3, Mariangel Fedrizzi4, Stanley C Solomon5, Liying Qian6, Jeffrey P Thayer7 and Mihail Codrescu8, (1)Atmospheric and Space Technology Research Associates LLC, Boulder, CO, United States, (2)Univ of Colorado-CIRES, Boulder, CO, United States, (3)University of Colorado, Boulder, CO, United States, (4)NOAA/SWPC-Univ. Colorado/CIRES, Boulder, CO, United States, (5)National Center for Atmospheric Research, Boulder, CO, United States, (6)NCAR High Altitude Observatory, Boulder, CO, United States, (7)University of Colorado at Boulder, Boulder, CO, United States, (8)SWPC/NOAA, Boulder, CO, United States
Much as aircraft are affected by the prevailing winds and weather conditions in which they fly, satellites are affected by variability in the density and motion of the near earth space environment. Drastic changes in the neutral density of the thermosphere, caused by geomagnetic storms or other phenomena, result in perturbations of satellite motions through drag on the satellite surfaces. This can lead to difficulties in locating important satellites, temporarily losing track of satellites, and errors when predicting collisions in space. As the population of satellites in Earth orbit grows, higher space-weather prediction accuracy is required for critical missions, such as accurate catalog maintenance, collision avoidance for manned and unmanned space flight, reentry prediction, satellite lifetime prediction, defining on-board fuel requirements, and satellite attitude dynamics.

We describe ongoing work to build a comprehensive nowcast and forecast system for neutral density, winds, temperature, composition, and satellite drag. This modeling tool will be called the Atmospheric Density Assimilation Model (ADAM). It will be based on three state-of-the-art coupled models of the thermosphere-ionosphere running in real-time, using assimilative techniques to produce a thermospheric nowcast. It will also produce, in realtime, 72-hour predictions of the global thermosphere-ionosphere system using the nowcast as the initial condition.

We will review the requirements for the ADAM system, the underlying full-physics models, the plethora of input options available to drive the models, a feasibility study showing the performance of first-principles models as it pertains to satellite-drag operational needs, and review challenges in designing an assimilative space-weather prediction model. The performance of the ensemble assimilative model is expected to exceed the performance of current empirical and assimilative density models.