EconPapers    
Economics at your fingertips  
 

Tricks for improving non-homogeneous regression for probabilistic precipitation forecasts: Perfect predictions, heavy tails, and link functions

Manuel Gebetsberger (), Jakob W. Messner (), Georg J. Mayr () and Achim Zeileis ()

Working Papers from Faculty of Economics and Statistics, University of Innsbruck

Abstract: Raw ensemble forecasts display large errors in predicting precipitation amounts and its forecast uncertainty, especially in mountainous regions where local effects are often not captured. Therefore, statistical post-processing is typically applied to obtain automatically corrected weather forecasts where precipitation represents one of the most challenging quantities. This study applies the non-homogenous regression framework as a start-of-the-art ensemble post-processing technique to predict a full forecast distribution and improves its forecast performance with three statistical tricks. First of all, a novel split-type approach effectively accounts for perfect ensemble predictions that can occur. Additionally, the statistical model assumes a censored logistic distribution to deal with the heavy tails of precipitation amounts. Finally, the optimization of regression coefficients for the scale parameter is investigated with suitable link-functions. These three refinements are tested for stations in the European Alps for lead-times from +24h to +48h and accumulation periods of 24 and 6 hours. Results highlight an improvement due to a combination of the three statistical tricks against the default post-processing method which does not account for perfect ensemble predictions. Probabilistic forecasts for precipitation amounts as well as the probability of precipitation events could be improved, especially for 6 hour sums.

Keywords: non-homogeneous regression; censored logistic distribution; log-link; probabilistic precipitation forecasts; operational forecasting (search for similar items in EconPapers)
JEL-codes: C53 C61 Q50 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-for
Date: 2016-10
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
https://eeecon.uibk.ac.at/wopec2/repec/inn/wpaper/2016-28.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:inn:wpaper:2016-28

Access Statistics for this paper

More papers in Working Papers from Faculty of Economics and Statistics, University of Innsbruck Contact information at EDIRC.
Series data maintained by Janette Walde ().

 
Page updated 2017-02-24
Handle: RePEc:inn:wpaper:2016-28