J14.3 Physics-Based Assimilative Atmospheric Modeling for Satellite Drag Specification and Forecasts

Tuesday, 12 January 2016: 2:00 PM
Room 352 ( New Orleans Ernest N. Morial Convention Center)
Geoff Crowley, Atmospheric & Space Technology Research Associates, Boulder, CO; and M. Pilinski, J. Wolfe, T. Fuller-Rowell, T. Matsuo, M. Fedrizzi, S. C. Solomon, L. Qian, J. P. Thayer, and M. Codrescu

Much as aircraft are affected by the prevailing winds and weather conditions in which they fly, satellites are affected by the variability in 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 LEO 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 specifying orbital drag conditions. The system outputs include neutral density, winds, temperature, composition, and the satellite drag derived from these parameters. This modeling tool is called the Atmospheric Density Assimilation Model or ADAM. ADAM is based on three state-of-the-art coupled models of the thermosphere-ionosphere running in real-time and uses assimilative techniques to produce a thermospheric nowcast. ADAM will also produce 72 hour predictions of the global thermosphere-ionosphere system using the nowcast as the initial condition and using near real-time and predicted space weather data and indices as the inputs. We expect the model drag nowcast and predictions to exceed the performance of current atmospheric models thus lowering the in-track orbit errors associated with Low Earth Orbit predictions. Furthermore, our model will provide measures of satellite drag uncertainty which are currently not available with present techniques.

In this presentation, we will review the requirements for this system, present 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. Finally, we will present some preliminary modeling results and how they relate to expected orbital errors.

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