Nowcasting and Forecasting the Ionosphere-Thermosphere System During Extreme Events

Abstract:

The ionosphere-thermosphere (I-T) system rarely reaches a quiescent state, making prediction a persistent, day-to-day effort. In addition to advance knowledge of upstream space weather activity, accurate modeling and data assimilation capabilities are required to establish the initial conditions of any global-scale I-T forecast. Using Iterative Re-Initialization, Driver Estimation and Assimilation (IRIDEA), a recently developed approach for estimating real-time corrections to external drivers (e.g., solar wind and EUV irradiance variability) and their coupling functions within a physics-based modeling framework, we present a case study of I-T response during the extreme Halloween events of Oct/Nov, 2003. In the context of this event we will highlight modeling challenges; implementation within the Space Weather Technology, Research and Education Center’s (SWx TREC) accelerated R2O-O2R testbed; and expectations for improving I-T forecasting capabilities.