Very high resolution interpolated climate surfaces for global land areas

International Journal of ClimatologyVolume 25, Issue 15 p. 1965-1978 Research Article Very high resolution interpolated climate surfaces for global land areas Robert J. Hijmans, Corresponding Author Robert J. Hijmans rhijmans@berkeley.edu Museum of Vertebrate Zoology, University of California, 3101 Valley Life Sciences Building, Berkeley, CA, USAMuseum of Vertebrate Zoology, University of California, 3101 Valley Life Sciences Building, Berkeley, CA, USASearch for more papers by this authorSusan E. Cameron, Susan E. Cameron Museum of Vertebrate Zoology, University of California, 3101 Valley Life Sciences Building, Berkeley, CA, USA Department of Environmental Science and Policy, University of California, Davis, CA, USA; and Rainforest Cooperative Research Centre, University of Queensland, AustraliaSearch for more papers by this authorJuan L. Parra, Juan L. Parra Museum of Vertebrate Zoology, University of California, 3101 Valley Life Sciences Building, Berkeley, CA, USASearch for more papers by this authorPeter G. Jones, Peter G. Jones International Center for Tropical Agriculture, Cali, ColombiaSearch for more papers by this authorAndy Jarvis, Andy Jarvis International Center for Tropical Agriculture, Cali, Colombia International Plant Genetic Resources Institute, Cali, ColombiaSearch for more papers by this author Robert J. Hijmans, Corresponding Author Robert J. Hijmans rhijmans@berkeley.edu Museum of Vertebrate Zoology, University of California, 3101 Valley Life Sciences Building, Berkeley, CA, USAMuseum of Vertebrate Zoology, University of California, 3101 Valley Life Sciences Building, Berkeley, CA, USASearch for more papers by this authorSusan E. Cameron, Susan E. Cameron Museum of Vertebrate Zoology, University of California, 3101 Valley Life Sciences Building, Berkeley, CA, USA Department of Environmental Science and Policy, University of California, Davis, CA, USA; and Rainforest Cooperative Research Centre, University of Queensland, AustraliaSearch for more papers by this authorJuan L. Parra, Juan L. Parra Museum of Vertebrate Zoology, University of California, 3101 Valley Life Sciences Building, Berkeley, CA, USASearch for more papers by this authorPeter G. Jones, Peter G. Jones International Center for Tropical Agriculture, Cali, ColombiaSearch for more papers by this authorAndy Jarvis, Andy Jarvis International Center for Tropical Agriculture, Cali, Colombia International Plant Genetic Resources Institute, Cali, ColombiaSearch for more papers by this author First published: 30 November 2005 https://doi.org/10.1002/joc.1276Citations: 13,460AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950–2000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty arising from the input data and the interpolation by mapping weather station density, elevation bias in the weather stations, and elevation variation within grid cells and through data partitioning and cross validation. Elevation bias tended to be negative (stations lower than expected) at high latitudes but positive in the tropics. Uncertainty is highest in mountainous and in poorly sampled areas. Data partitioning showed high uncertainty of the surfaces on isolated islands, e.g. in the Pacific. Aggregating the elevation and climate data to 10 arc min resolution showed an enormous variation within grid cells, illustrating the value of high-resolution surfaces. A comparison with an existing data set at 10 arc min resolution showed overall agreement, but with significant variation in some regions. A comparison with two high-resolution data sets for the United States also identified areas with large local differences, particularly in mountainous areas. Compared to previous global climatologies, ours has the following advantages: the data are at a higher spatial resolution (400 times greater or more); more weather station records were used; improved elevation data were used; and more information about spatial patterns of uncertainty in the data is available. Owing to the overall low density of available climate stations, our surfaces do not capture of all variation that may occur at a resolution of 1 km, particularly of precipitation in mountainous areas. In future work, such variation might be captured through knowledge-based methods and inclusion of additional co-variates, particularly layers obtained through remote sensing. Copyright © 2005 Royal Meteorological Society. Citing Literature Volume25, Issue15December 2005Pages 1965-1978 RelatedInformation