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CHELSA_2011-2040

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Field Value
Description Climatic data projections for analysis and modeling.
Folder /datasets/Covariates/CHELSA_2011-2040
Discipline Covariates / Climate Sciences / Geography
DOI 10.1038/sdata.2017.122
Link Access Data
Public true
Publication Date 2020-09-05
Downloaded 2024-11-25
Time Resolution 2011-2040
Spatial Resolution 1km
Data Type GIS Geotiff file
Dataset Size 85G
Number of Files 286
Usage 
$ module avail
$ module load datasets
$ module load Covariates/CHELSA_2011-2040/2020-09-05
Usage Policy Link https://creativecommons.org/licenses/by/4.0/
Usage Policy This dataset is distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, sharing, adaptation, distribution, and reproduction in any medium or format, provided appropriate credit is given to the original authors and the source. Users must include a link to the license and clearly indicate if any changes were made. Images or other third-party materials included in the dataset are covered by the same license unless otherwise specified in the accompanying documentation. If certain materials are not included under this license and your intended use is not permitted by statutory regulation or exceeds the permitted use, permission must be obtained directly from the copyright holder. The metadata files associated with this dataset are made available under the Creative Commons Public Domain Dedication (CC0 1.0), allowing their free and unrestricted reuse.
Citation Karger, D., Conrad, O., Böhner, J. et al. Climatologies at high resolution for the earth’s land surface areas. Sci Data 4, 170122 (2017). https://doi.org/10.1038/sdata.2017.122
BibTeX
📜 View BibTeX citation
@article{Karger2017,
  author       = {Karger, Dirk Nikolaus and Conrad, Olaf and Böhner, Jürgen and Kawohl, Tobias and Kreft, Holger and Soria-Auza, Rodrigo Wilber and Zimmermann, Niklaus E. and Linder, H. Peter and Kessler, Michael},
  title        = {Climatologies at high resolution for the earth’s land surface areas},
  journal      = {Scientific Data},
  year         = {2017},
  volume       = {4},
  number       = {1},
  pages        = {170122},
  doi          = {10.1038/sdata.2017.122},
  url          = {https://doi.org/10.1038/sdata.2017.122},
  issn         = {2052-4463},
  abstract     = {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.}
}