Assessing the Calibration of High-Dimensional Ensemble Forecasts Using Rank Histograms

  title={Assessing the Calibration of High-Dimensional Ensemble Forecasts Using Rank Histograms},
  author={Thordis Linda Thorarinsdottir and Michael Scheuerer and Christoph Heinz},
  journal={Journal of Computational and Graphical Statistics},
  pages={105 - 122}
Any decision-making process that relies on a probabilistic forecast of future events necessarily requires a calibrated forecast. This article proposes new methods for empirically assessing forecast calibration in a multivariate setting where the probabilistic forecast is given by an ensemble of equally probable forecast scenarios. Multivariate properties are mapped to a single dimension through a prerank function and the calibration is subsequently assessed visually through a histogram of the… 

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  • Claudio Heinrich
  • Computer Science, Environmental Science
    Quarterly Journal of the Royal Meteorological Society
  • 2020
The goal of the method is to select a number of bins such that the intuitive decision whether a histogram is uniform or not is as close as possible to a formal statistical test.



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