Validating WSA-ADAPT Solar Wind Predictions Using Baseline Models

Abstract:

As we move towards crewed missions to the moon and beyond, accurate forecasting of space weather grows increasingly important. The Wang-Sheeley-Arge (WSA) model predicts solar wind speed and IMF polarity at any point in the inner heliosphere, which can then be compared against in-situ satellite data. Using Air Force Data Assimilative Photospheric flux Transport (ADAPT) input maps, we can create multiple WSA-ADAPT predictions for forecasting purposes. Until now, only relative scoring has been calculated between the various realizations using the WSA Prediction Metric (WSA-PM). Here we detail the results of adding in baseline models, such as persistence, to further validate WSA predictions and get a quantitative measure of WSA performance, as well as investigate the performance of the mean ensemble prediction.