High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth’s land surface areas) data of downscaled model output temperature and precipitation estimates of the ERA-Interim climatic reanalysis to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction. The resulting data consist of a monthly temperature and precipitation climatology for the years 1979–2013. We compare the data derived from the CHELSA algorithm with other standard gridded products and station data from the Global Historical Climate Network. We compare the performance of the new climatologies in species distribution modelling and show that we can increase the accuracy of species range predictions. We further show that CHELSA climatological data has a similar accuracy as other products for temperature, but that its predictions of precipitation patterns are better. Design Type(s) data integration objective • modeling and simulation objective Measurement Type(s) temperature of air • hydrological precipitation process Technology Type(s) data acquisition system Factor Type(s) Sample Characteristic(s) Earth • planetary atmosphere Design Type(s) data integration objective • modeling and simulation objective Measurement Type(s) temperature of air • hydrological precipitation process Technology Type(s) data acquisition system Factor Type(s) Sample Characteristic(s) Earth • planetary atmosphere Machine-accessible metadata file describing the reported data (ISA-Tab format)
Climatologies at high resolution for the earth’s land surface areas
D. Karger,O. Conrad,J. Böhner,Tobias Kawohl,H. Kreft,Rodrigo W. Soria-Auza,N. Zimmermann,Peter H Linder,M. Kessler
Published 2016 in Scientific Data
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- Publication year
2016
- Venue
Scientific Data
- Publication date
2016-07-01
- Fields of study
Medicine, Physics, Environmental Science
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Semantic Scholar, PubMed
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