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

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          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.

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          A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain

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            An Overview of the Global Historical Climatology Network Temperature Database

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              Statistical downscaling of general circulation model output: A comparison of methods

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                Author and article information

                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group
                2052-4463
                05 September 2017
                2017
                : 4
                : 170122
                Affiliations
                [1 ]Department of Systematic and Evolutionary Botany, University of Zurich , Zollikerstrasse 107, Zurich 8008, Switzerland
                [2 ]Swiss Federal Research Institute WSL , Zürcherstr 111, Birmensdorf 8903, Switzerland
                [3 ]Institute of Geography, University of Hamburg , Bundesstrasse 55, Hamburg 20146, Germany
                [4 ]Biodiversity, Macroecology & Conservation Biogeography Group, University of Göttingen , Göttingen 37077, Germany
                [5 ]Asociación Armonía , Av. Lomas de Arena # 400, Zona Palmasola, Santa Cruz de la Sierra 10260, Bolivia
                Author notes
                []

                M.K. initiated the project. D.N.K., O.K., and T.K. developed the algorithms in close communication with J.B. R.W.S. compiled the GHCN data and removed the errors. M.K., H.K., P.L., and N.Z. provided the funding for the project. D.N.K. wrote the first draft of the manuscript and all authors contributed significantly to the revisions.

                Author information
                http://orcid.org/0000-0003-4471-8236
                Article
                sdata2017122
                10.1038/sdata.2017.122
                5584396
                28872642
                58bedfa2-9f73-4f85-b64d-7069e3f979fd
                Copyright © 2017, The Author(s)

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.

                History
                : 11 October 2016
                : 21 July 2017
                Categories
                Data Descriptor

                atmospheric science,hydrology,biogeography
                atmospheric science, hydrology, biogeography

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