Ionospheric data assimilation with thermosphere‐ionosphere‐electrodynamics general circulation model and GPS‐TEC during geomagnetic storm conditions

摘要: The main purpose of this paper is to investigate the effects rapid assimilation-forecast cycling on performance ionospheric data assimilation during geomagnetic storm conditions. An ensemble Kalman filter software developed by National Center for Atmospheric Research (NCAR), called Data Assimilation Testbed, applied assimilate ground-based GPS total electron content (TEC) observations into a theoretical numerical model thermosphere and ionosphere (NCAR thermosphere-ionosphere-electrodynamics general circulation model) 26 September 2011 period. Effects various cycle lengths: 60, 30, 10 min forecast are examined using global root-mean-squared observation-minus-forecast (OmF) TEC residuals. Substantial reduction in OmF suggests that system can greatly improve quality Furthermore, updating thermospheric state variables coupled thermosphere-ionosphere step an important factor improving trajectory forecasting. shorter (10 min paper) helps restrain unrealistic error growth due imbalance among resulting from inadequate update, which turn leads greater accuracy.