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1 results

  • 16 - Forecast Verification and Post-processing

  • William W. Hsieh, University of British Columbia, Vancouver
  • Book:
    Introduction to Environmental Data Science
    Published online:
    23 March 2023
    Print publication:
    23 March 2023, pp 518-548

  • Summary

    Forecast verification evaluates the quality of the forecasts made by a model, using a variety of forecast scores developed for binary classes, multiple classes, continuous variables and probabilistic forecasts. Skill scores estimate a model’s skill relative to a reference model or benchmark. Problems such as spurious skills and extrapolation with new data are discussed. Model bias in the output predicted by numerical models is alleviated by post-processing methods, while output from numerical models with low spatial resolution is enhanced by downscaling methods, especially in climate change studies.