PC, the mean CRPS of isotonic distributional regression fitted post hoc to deterministic model output, offers a loss-function-independent way to compare AI and physics-based weather forecasts.
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Probabilistic measures afford fair comparisons of AIWP and NWP model output
PC, the mean CRPS of isotonic distributional regression fitted post hoc to deterministic model output, offers a loss-function-independent way to compare AI and physics-based weather forecasts.