High temporal and spatial resolution of bioclimatic variables on central chile for different climate change scenarios and global circulation models

The original data set corresponds to the bioclimatic variables developed by Nix (1986) and used by Higmans (2005) to global data sets for Central Chile at a resolution of 500 meters.<br>The data was generated using daily data of mean minimum and maximum temperatures and precipitation was collected between 1980 and 2017. Temperature data from 103 and precipitation from 321 weather stations, respectively. Data quality control was performed to correct anomaly data, such as repeated values, unrealistic data within the time series. In addition, processing was applied for missing data in the time series that consisted of identifying the station with the least number of missing data, then applying multiple linear regression using the observed data related to the nearest stations. The atmospheric variables of Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) reanalysis that are available for the entire period were included in the regression variables. This process was done iteratively to all required weather stations to complete missing data.<br>Statistical downscaling was performed using regressions that included geographic position and topography and subsequently a correction for bias using data assimilation. This method was applied to a set of CMIP5 GCMs that perform well in Central Chile. 14 GCMs were selected that by including their different assemblies make a total of 33 common data sets for the RCP26 and RCP85 scenarios.<br>To each of these data sets, the annual bioclimatic variables were calculated from 1980 to 2070. The data set was added at a resolution of 2 kilometers per repository capacity limit, but the original data is available upon request from [e-mail] <br>