A time series dataset of climate variables from 1951 to 2014 in karst region of southwestern China

Abstract

This study uses the local smooth thin plate spline function provided in the ANUSPLIN software version 4.3, combined with the Shuttle Radar Topography Mission (SRTM) digital elevation model, to spatially interpolate four monthly climatic variables (including temperature, precipitation, percentage of sunshine, and wet days with daily precipitation <0.1 mm). Three sets of gridded data in different formats with a resolution of 1km are finally obtained. Monthly climate raster data in Southwest China from 1951 to 2014. The data set contains files in three formats of four climate indicators: temperature, precipitation, percentage of sunshine, and number of wet days, totaling 54 years * December * 4 climate indicators * 3 format = 9216 file.{ASCII character set encoding text file(.asc), two-dimensional uniform grid(.grd),, label image file(.tif)}. The error statistics show that the error of the interpolation results is relatively low, especially the accuracy of the temperature interpolation is high. The gridded data of the four climate variables can truly reflect the spatial distribution of climates in the karst area. Further analyses show that from 1951 to 2014, the distribution of temperature and precipitation showed a decreasing trend from the southeast to the northwest. This dataset can provide data support for regional climate research in karst area of southwestern China, vegetation, rocky desertification and climate change, land use and land cover changes, and climate–driven terrestrial ecological model simulations.