Calibrating Probabilistic Solar-Wind Forecasts Driven by the Wang-Sheeley-Arge Model.

By spatially perturbing coronal model output within a coupled coronal-heliospheric model we can generate probabilistic predictions of solar-wind speed. We apply these spatial perturbations to the Wang-Sheeley-Arge (WSA) model output to generate large sets of input conditions for the Heliospheric Upwind eXtrapolation with time dependence (HUXt) solar-wind model. The resulting ensemble forecasts at 1 AU contain useful information about likely outcomes and the method allows uncertainty to be better characterized. We tune the scales of perturbations to calibrate the probabilistic predictions. We use the rank histogram and reliability component of the Brier score to demonstrate how increasing levels of perturbation/variability generally improves the reliability of the WSA-HUXt ensemble distribution; the ability of the ensemble to capture the true likelihood of events based on observational frequencies. We use the resolution component of the Brier score to highlight how too large a perturbation harms the statistical resolution of the forecast; the ability of the model to meaningfully distinguish between events beyond a statistical observational baseline (like climatology). This adds a useful constraint on the maximum size of perturbation we should be applying. Additionally, we use continuous ranked probability score to demonstrate how a calibrated ensemble can improve a prediction system, reducing forecast error across all lead times. Finally we demonstrate that the calibrated ensemble provides value for an end-user through a Cost/Loss analysis. In refining this calibration procedure we provide optimal values of the perturbation parameters for use in the operational WSA-HUXt forecast.

Recommended citation: Edward-Inatimi, N.O., Owens, M.J., Barnard, L., Turner, H., Marsh, M., Gonzi, S., and Lang, M. (2026). Calibrating Probabilistic Solar-Wind Forecasts Driven by the Wang-Sheeley-Arge Model. Space Weather, 24. DOI: https://doi.org/10.1029/2025SW004675
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