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Spatio-Temporal Precipitation Climatology over Complex Terrain Using a Censored Additive Regression Model

Author

Listed:
  • Reto Stauffer
  • Jakob W. Messner
  • Georg J. Mayr
  • Nikolaus Umlauf
  • Achim Zeileis

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.

Suggested Citation

  • Reto Stauffer & Jakob W. Messner & Georg J. Mayr & Nikolaus Umlauf & Achim Zeileis, 2016. "Spatio-Temporal Precipitation Climatology over Complex Terrain Using a Censored Additive Regression Model," Working Papers 2016-07, Faculty of Economics and Statistics, Universität Innsbruck.
    • Handle: RePEc:inn:wpaper:2016-07
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    References listed on IDEAS

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    1. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
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    Cited by:

    1. Reto Stauffer & Jakob W. Messner & Georg J. Mayr & Nikolaus Umlauf & Achim Zeileis, 2016. "Ensemble Post-Processing of Daily Precipitation Sums over Complex Terrain Using Censored High-Resolution Standardized Anomalies," Working Papers 2016-21, Faculty of Economics and Statistics, Universität Innsbruck.
    2. Thomas Kneib & Nadja Klein & Stefan Lang & Nikolaus Umlauf, 2019. "Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 1-39, March.

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    More about this item

    Keywords

    climatology; precipitation; complex terrain; GAMLSS; censoring; daily resolution;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General

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