Statistics – Applications
Scientific paper
Dec 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011agufmsa31b1984k&link_type=abstract
American Geophysical Union, Fall Meeting 2011, abstract #SA31B-1984
Statistics
Applications
[3369] Atmospheric Processes / Thermospheric Dynamics
Scientific paper
Our society relies heavily on its space infrastructure for a vast number of applications. However, NASA predicts that between now and 2030 orbital collisions will become increasingly frequent and could reach a run-away environment - the so-called Kessler Syndrome. Preventing this scenario requires, in addition to an object removal technique, an improved new orbital dynamics framework with improved drag predictions based on thermospheric densities and wind velocities. In particular for LEO (Low Earth Orbit) objects, satellite drag due to atmospheric friction is the major non-conservative force that can lead to significant errors. To achieve the goal of improved orbital drag specification, the IMPACT project (Integrated Modeling of Perturbations in Atmospheres for Conjunction Tracking) will employ a comprehensive physics-based model of the thermosphere GITM. The GITM model (Global Ionosphere-Thermosphere Model), developed at the University of Michigan, is solving the full hydrodynamic equation without assuming hydrostatic equilibrium and also includes heating and cooling processes that are causing the density variations and thermospheric wind velocities in the upper atmosphere. The model is coupled to solar and magnetospheric drivers and is, therefore, ideally suited for orbital drag calculations that include relative wind velocities. We will present a study of thermospheric wind velocities as predicted with GITM and compared to observations. We will use the results for orbital drag calculations and determine the sensitivity of the errors in orbital predictions as a function of thermospheric density and wind velocities and how they can alter the orbit of LEO objects and lead to significant errors in orbital predictions. This work is a major new investment at Los Alamos National Laboratory funded by the Laboratory Directed Research and Development (LDRD) program and we gratefully acknowledge the support of the U.S. Department of Energy for this work.
Godinez Humberto C.
Impact Team
Koller Josef
Ridley Aaron J.
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