Spatio-temporal precipitation climatology over complex terrain using a censored additive regression model

Publication: Research - peer-reviewJournal article – Annual report year: 2017

Without internal affiliation


  • Author: Stauffer, Reto

    University of Innsbruck

  • Author: Mayr, Georg J.

    University of Innsbruck

  • Author: Messner, Jakob W.

    University of Innsbruck

  • Author: Umlauf, Nikolaus

    University of Innsbruck

  • Author: Zeileis, Achim

    University of Innsbruck

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Flexible spatio-temporal models are widely used to create reliable and accurate estimates for precipitation climatologies. Most models are based on square root transformed monthly or annual means, where a normal distribution seems to be appropriate. This assumption becomes invalid on a daily time scale as the observations involve large fractions of zero observations and are limited to non-negative values. We develop a novel spatio-temporal model to estimate the full climatological distribution of precipitation on a daily time scale over complex terrain using a left-censored normal distribution. The results demonstrate that the new method is able to account for the non-normal distribution and the large fraction of zero observations. The new climatology provides the full climatological distribution on a very high spatial and temporal resolution, and is competitive with, or even outperforms existing methods, even for arbitrary locations.

Original languageEnglish
JournalInternational Journal of Climatology
Issue number7
Pages (from-to)3264-3275
StatePublished - 15 Jun 2017
Externally publishedYes
CitationsWeb of Science® Times Cited: 4


  • censoring, climatology, complex terrain, daily resolution, GAMLSS, precipitation
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ID: 134849233