Improving Data Drivers for Coronal and SolarWind Models (Postprint)

摘要

Global estimates of the solar photospheric magnetic field distribution are critical for space weather forecasting. These global maps are the essential data input for accurate modeling of the corona and solar wind, which is vital for gaining the basic understanding necessary to improve space weather forecasting models. We are now testing the global photospheric field maps generated by the Air Force Data Assimilative Photospheric flux Transport (ADAPT) model as input to the Wang-Sheeley- Arge (WSA) coronal and solar wind model. ADAPT incorporates data assimilation within a modified version of the Worden & Harvey photospheric magnetic flux transport model to provide an instantaneous snapshot of the global photospheric field distribution compared to that of traditional synoptic maps. In this paper we provide an overview of the WSA and ADAPT models, plus discuss preliminary results obtained from WSA when using a traditional versus an ADAPT photospheric field synoptic map as its input.