Evaluating the WSA Model’s Predictive Performance

Charles Nickolos Arge1, Carl J Henney2, Kathleen Shurkin3, Michael S Kirk1 and Samantha Wallace4, (1)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (2)Air Force Research Laboratory Kirtland AFB, Kirtland AFB, NM, United States, (3)Air Force Research Laboratory, Albuquerque, NM, United States, (4)University of New Mexico, Physics and Astronomy, Albuquerque, NM, United States
Abstract:
The Wang-Sheeley-Arge (WSA) model is a combined empirical and physics-based model of the corona and solar wind. It was originally developed by Yi-Ming Wang and Neil Sheeley nearly 30 years ago. It has been significantly modified and improved since its inception and has been subjected to several validation studies, especially in the last decade. It was operationalized at the National Weather Service’s National Centers for Environmental Prediction in 2011. When evaluating the predictive performance of a model such as WSA, one must carefully consider what aspect of the model that is to be validated, as it is capable of predicting a variety of key parameters. For instance, WSA can predict the areas, shapes, and locations of coronal holes; the total open magnetic emerging from the Sun; the arrival, duration, and structure of high speed streams; and solar wind speed and interplanetary magnetic field polarity at any point in the inner heliosphere. Evaluation of the model’s ability to predict these various parameters often require a different approach/methodology for each of them. In this talk, the various methods (both past and present) used to evaluate WSA’s predictive performance are presented and discussed.
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