Development of Ionospheric Data Assimilation Model using GNSS Observations

This study attempts to construct the ionosphere data assimilation model for both quiet and storm time ionosphere. The model assimilates radio occultation and ground-based GNSS observations of global ionosphere using an Ensemble Kalman Filter (EnKF) software of Data Assimilation Research Testbed (DART) together with the theoretical thermosphere-ionosphere-electrodynamic general circulation model (TIEGCM), developed by National Center for Atmospheric Research (NCAR). Using DART-TIEGCM, we investigate the effects of rapid assimilation-forecast cycling for the 26 September 2011 geomagnetic storm period. Effects of various assimilation-forecast cycles, 60-, 30-, and 10-minutes, on the ionospheric forecast are examined by using the global root-mean-square error (RMSE) of observation-minus-forecast (OmF) TEC residuals during the entire storm period. Examinations show that the 10-minutes assimilation cycle could greatly improve the quality of model forecast under the storm conditions. Additionally, examinations of storm-time forecast quality for different high latitude forcing given by Heelis and Weimer empirical models are also performed.