A meteorological example of how forecasts have improved since 1981, in this case for the 500 hPa geopotential height. Henley and Pope encourage a similar approach for space weather, using common metrics such as the “anomaly correlation” shown here on the y axis (expressed as a percentage). This metric correlates deviations of forecasts and observations from climatological values. The blue, red, green, and yellow bands indicate forecasts for 3, 5, 7, and 10 days ahead, and their width indicates the difference between the metrics for northern (top of band) and southern hemispheres (bottom). Credit: Henley and Pope, 2017, Figure 2
Source: Space Weather

Tools previously developed to assess and improve the value of terrestrial weather forecasts are now being used to advance space weather forecasting. Henley and Pope [2017] discuss these tools, including both techniques to quantify forecast uncertainties and methods to customize forecasts so that they can be well-integrated with how each user manages their specific risks. In particular, they highlight the technique of cost-loss analysis, which provides a way to assess the benefits of different user actions to mitigate risks in response to a forecast of that risk. This is a very readable introduction to the technique and discusses its application in a recent paper by Owens and Riley [2017]. It also discusses the potential for wider application to space weather of metrics developed by the global weather forecasting community, and the importance of those metrics being common standards used by all forecast centers.

Citation: Henley, E. M., & Pope, E. C. D. [2017]. Cost-loss analysis of ensemble solar wind forecasting: Space weather use of terrestrial weather tools. Space Weather, 15. https://doi.org/10.1002/2017SW001758

—Michael Hapgood, Editor, Space Weather

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