Specification of the Ionosphere-Thermosphere Environment using Ensemble Kalman Filter with Orthogonal Transformations
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Tuesday, 6 January 2015: 5:30 PM
227A-C (Phoenix Convention Center - West and North Buildings)
The Ionosphere-Thermosphere environment undergoes constant and sometimes dramatic changes due to solar and geomagnetic activity. Furthermore, given that this environment has a significant effect on space infrastructure, such as satellites, it is important to understand the potential changes caused by space weather events. This work presents a case study of a number of time periods using assimilation methods with the Global Ionosphere-Thermosphere Model (GITM). The main objective is to analyze the changes in the global upper atmospheric environment caused by extreme space weather events, and analyze the effect on satellite drag and collision uncertainty. In particular, an ensemble Kalman filter (EnKF) assimilation method is applied to GITM and used to incorporate observations from the CHAllenging Minisatellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE) missions. To reduce the introduction of noise into the assimilation results, we use orthogonal transformations in the EnKF to capture the dominant correlations within the model variables. In particular, we use principal component analysis technique to extract the dominant directions of variability and form a basis for an orthogonal transformation. The assimilation is performed in the space spanned by the orthogonal basis and used to adjust the model variables and parameters.
The experiments show that key solar parameters, which act as proxy for solar activity, exert a significant influence in the evolution of the total atmospheric density. To validate the assimilation results, a forecast error is computed using an independent observation set. Additional ionosphere-thermosphere models are also compared against assimilated GITM results to test the accuracy of the assimilation technique. Finally, a series of orbital propagation experiments are performed using configurations consistent with a number of satellites. The results show that the assimilated GITM contains the smallest forecast error for total density, compared to other ionosphere-thermosphere models, and provides a total density that is more accurate for orbital propagation of satellites.
The work is part of the Integrated Modeling of Perturbations in Atmospheres for Conjunction Tracking (IMPACT) project in Los Alamos National Laboratory.