Global dataset of downscaled future projections developed by applying a statistical method for climate model downscaling and bias correction. We applied the delta method, which comprises the sum of interpolated anomalies of each GCM to the WorldClim 1-km spatial resolution dataset. The GCMs were the 35 Coupled Model Intercomparison Project Phase 5 (CMIP5) models, for four representative concentrations pathways (RCPs). For each of these, we used the 30-year future periods named as 2030s, 2050s, 2070s and 2080s with three climate variables (mean monthly maximum and minimum temperatures and monthly rainfall). From these, we also derive a set of bioclimatic indices. The primary downscaling resolution is 30 arc-s (~1 km at the Equator) but we aggregate the data to other three resolutions using nearest neighbor interpolation, including: 2.5 arc-m (~5 km), 5 arc-m (~10 km), and 10 arc-m (20 km).
The dataset name structure for this dataset group: "CMIP5 Downscaled - Global Data Files at <res> resolution"
where <res> is the resolution.
The file name structure for these datasets: "cmip5dc_global_<res>_<rcp>_<YYYY>s_asc.zip" where <res> is the resolution=30",2.5',5',10';
<rcp> is one of four Representative Concentration Pathways; and <YYYY> is the time step.
Navarro Racines, Carlos Eduardo; Tarapues Montenegro, Jaime Eduardo; Thornton, Philip; Jarvis, Andy; Ramirez Villegas, Julian (2019). CCAFS-CMIP5 Delta Method Downscaling for monthly averages and bioclimatic indices of four RCPs. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/CCAFS-CMIP5_downscaling