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Gebetsberger Mayr Stauffer-2017.pdf
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🔗 Source: zeileis.org
📊 Size: 376 KB
📄 Pages: 6 pages
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Weather forecasts based on numerical weather prediction models can be corrected by statistical post-processing methods, which often assume a Gaussian distribution for surface air temperature. However, this assumption can lead to strongly skewed residuals, especially in areas with complex topography. Two approaches are proposed to overcome this issue: using a skewed response distribution, such as the generalized logistic distribution, and extending the classical Gaussian distributional regression model by including all available information from the weather prediction model with a boosting variable selection method. The results show that both approaches can improve predictions, especially for an Alpine station, in terms of overall performance and calibration.

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Weather forecasts based on numerical weather prediction models can be corrected by statistical post-processing methods, which often assume a Gaussian...

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  • File Format: PDF
  • File Size: 376 KB
  • Pages: 6
  • Language: EN
  • Total Downloads: 48
  • Last Updated: 19 hours ago

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