Similarity‐based semilocal estimation of post‐processing models

@article{Lerch2017SimilaritybasedSE,
  title={Similarity‐based semilocal estimation of post‐processing models},
  author={Sebastian Lerch and S{\'a}ndor Baran},
  journal={Journal of the Royal Statistical Society: Series C (Applied Statistics)},
  year={2017},
  volume={66}
}
  • S. Lerch, S. Baran
  • Published 11 September 2015
  • Environmental Science
  • Journal of the Royal Statistical Society: Series C (Applied Statistics)
Weather forecasts are typically given in the form of forecast ensembles obtained from multiple runs of numerical weather prediction models with varying initial conditions and physics parameterizations. Such ensemble predictions tend to be biased and underdispersive and thus require statistical post‐processing. In the ensemble model output statistics approach, a probabilistic forecast is given by a single parametric distribution with parameters depending on the ensemble members. The paper… 

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