Climatologies at high resolution for the earth’s land surface areas

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.

Data Variable Codes:

  • Bio1 = Annual Mean Temperature
  • Bio2 = Mean Diurnal Range
  • Bio3 = Isothermality
  • Bio4 = Temperature Seasonality
  • Bio5 = Max Temperature of Warmest Month
  • Bio6 = Min Temperature of Coldest Month
  • Bio7 = Temperature Annual Range
  • Bio8 = Mean Temperature of Wettest Quarter
  • Bio9 = Mean Temperature of Driest Quarter
  • Bio10 = Mean Temperature of Warmest Quarter
  • Bio11 = Mean Temperature of Coldest Quarter
  • Bio12 = Annual Precipitation
  • Bio13 = Precipitation of Wettest Month
  • Bio14 = Precipitation of Driest Month
  • Bio15 = Precipitation Seasonality
  • Bio16 = Precipitation of Wettest Quarter
  • Bio17 = Precipitation of Driest Quarter
  • Bio18 = Precipitation of Warmest Quarter
  • Bio19 = Precipitation of Coldest Quarter

  Paper Citation:

Karger DN. et al. Climatologies at high resolution for the earth’s land surface areas, Scientific Data, 4, 170122 (2017) doi: 10.1038/sdata.2017.122.


Dirk Nikolaus Karger; Olaf Conrad; Jürgen Böhner; Tobias Kawohl; Holger Kreft; Rodrigo Wilber Soria-Auza; Niklaus E. Zimmermann; H. Peter Linder; Michael Kessler (2017). Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. doi:10.5061/dryad.kd1d4.

DataCite ISO 19139 GCMD DIF README.txt BibTex RIS

Data and Resources


Field Values
DOI 10.5061/dryad.kd1d4
  • Name: Dirk Nikolaus Karger  Affiliation: WSL  Email: dirk.kargerfoo(at)  DataCRediT: Collection, Validation, Curation, Publication, Supervision
  • Name: Olaf Conrad  Affiliation: University of Hamburg  Email: olaf.conradfoo(at)
  • Name: Jürgen Böhner  Affiliation: University of Hamburg  Email: juergen.boehnerfoo(at)
  • Name: Tobias Kawohl  Affiliation: University of Hamburg  Email: tobias.kawohlfoo(at)
  • Name: Holger Kreft  Affiliation: University of Goettingen  Email: hkreftfoo(at)
  • Name: Rodrigo Wilber Soria-Auza  Affiliation: Rodrigo Wilber Soria-Auza  Email: wilbersafoo(at)
  • Name: Niklaus E. Zimmermann  Affiliation: WSL  Email: niklaus.zimmermannfoo(at)
  • Name: H. Peter Linder  Affiliation: University of Zurich  Email: peter.linderfoo(at)
  • Name: Michael Kessler  Affiliation: University of Zurich  Email: michael.kesslerfoo(at)
Contact Person Name: Dirk Nikolaus Karger  Email: dirk.kargerfoo(at)  Affiliation: WSL
Publication Publisher: Dryad Digital Repository  Year: 2017
  • Type: Created  Date: 2017-07-21
Version 1.2
Type Dataset
General Type Dataset
Language English
Location global
License Other (Open)    [Open Data]
Last Updated December 9, 2018, 01:23 (CET)
Created July 3, 2018, 14:25 (CEST)

Custom Metadata

Custom Field Values
License CC BY0