Articles | Volume 5, issue 1
https://doi.org/10.5194/ascmo-5-87-2019
https://doi.org/10.5194/ascmo-5-87-2019
18 Jun 2019
 | 18 Jun 2019

Skewed logistic distribution for statistical temperature post-processing in mountainous areas

Manuel Gebetsberger, Reto Stauffer, Georg J. Mayr, and Achim Zeileis

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Latest update: 24 Feb 2024
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Short summary
This article presents a method for improving probabilistic air temperature forecasts, particularly at Alpine sites. Using a nonsymmetric forecast distribution, the probabilistic forecast quality can be improved with respect to the common symmetric Gaussian distribution used. Furthermore, a long-term training approach of 3 years is presented to ensure the stability of the regression coefficients. The research was based on a PhD project on building an automated forecast system for northern Italy.