Challenge in Specifying and Forecasting Space Weather

Abstract:

Physics-based Data Assimilation (DA) has been shown to be a powerful technique for specifying and predicting space weather. However, it is also known that different data assimilation models simulating the same geophysical event can display different space weather features even if the same data are assimilated. In this study, we used our Multimodel Ensemble Prediction System (MEPS) of DA models to elucidate the similarities and differences in the individual DA model reconstructions of the mid-low latitude ionosphere when the same data are assimilated. Ensemble model averages were also obtained. For this ensemble modeling study, we selected the quiet/storm period of 16–17 March 2013 (equinox, solar medium). Five data assimilation models and one physics-based model were used to produce an ensemble mean output for TEC for latitudes less than 60˚ and all longitudes. The data assimilated included GPS TEC and COSMIC occultation data. Both a simple average and a weighted average of the models were used in the ensemble averaging in order to determine if there was an improvement of the ensemble averages over the individual models when compared to independent measurements.