Abstract
We introduce a verification score for probabilistic forecasts of contours – the Spatial Probability Score (SPS). Defined as the spatial integral of local (Half) Brier Scores, the SPS can be considered the spatial analogue of the Continuous Ranked Probability Score (CRPS). Applying the SPS to idealized ensemble forecasts of the Arctic sea‐ice edge in a global coupled climate model, we demonstrate that the metric responds in a meaningful way to ensemble size, spread, and bias. When applied to individual forecasts or ensemble means (or quantiles), the SPS is reduced to the ‘volume’ of mismatch, which in the case of the ice edge corresponds to the Integrated Ice Edge Error (IIEE). By comparing initialized forecasts with climatological and persistence forecasts, we confirm earlier findings on the potential predictability of the Arctic sea‐ice edge from a probabilistic viewpoint. We conclude that the SPS is a promising probabilistic verification metric, for contour forecasts in general and for ice‐edge forecasts in particular.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Quarterly Journal of the Royal Meteorological Society
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.