4.6 Article

High resolution climate data for Austria in the period 2008-2040 from a statistical climate change model

期刊

INTERNATIONAL JOURNAL OF CLIMATOLOGY
卷 33, 期 2, 页码 430-443

出版社

WILEY
DOI: 10.1002/joc.3434

关键词

regional climate change data; statistical climate change model; linear regression; bootstrapping; Austria

资金

  1. Austrian Federal Ministry for Science and Research
  2. Federal Ministry of Agriculture, Forestry, Environment and Water Management [100394]
  3. EC
  4. cc-TAME project

向作者/读者索取更多资源

Climate change data for Austria have been produced for the period from 2008 to 2040, with a temporal/spatial resolution of 1 d and 1 km2. The climate change data are based on historical daily weather station data from 1975 to 2007, and linear regression modelling with repeated bootstrapping. The spatial resolution is based on 60 climate clusters which represent homogenous climates with respect to mean annual precipitation sums and mean annual temperatures from the period 1961 to 1990. For each climate cluster, a regression model fit has been performed and extrapolated for the period 20082040. The integral parts of our regression model are: (1) the extrapolation of the observed linear temperature trend from 1975 to 2007, by using an average national trend of approximately 0.05 degrees C per year derived from a homogenized dataset, and (2) the repeated bootstrapping of historical temperature residuals, and of the observations for some other weather parameters, such as solar radiation, precipitation, relative humidity and wind speed. Thus, we ensure consistent physical, spatial and temporal correlations. Precipitation scenarios have been developed to account for any possible wider range of precipitation patterns. These scenarios include increased/decreased annual precipitation sums, as well as unchanged annual precipitation sums, but with different seasonal distributions. These climate change data are available at: http://www.landnutzung.at/Klima_Daten.html Copyright (C) 2012 Royal Meteorological Society

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