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

Reto Stauffer*, Georg J. Mayr, Jakob W. Messner, Nikolaus Umlauf, Achim Zeileis

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

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
Volume37
Issue number7
Pages (from-to)3264-3275
ISSN0899-8418
DOIs
Publication statusPublished - 15 Jun 2017
Externally publishedYes

Keywords

  • censoring
  • climatology
  • complex terrain
  • daily resolution
  • GAMLSS
  • precipitation

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