CCAFS-CMIP5 Delta Method Downscaling for monthly averages and bioclimatic indices of four RCPs

Project: Delta method downscaled CMIP5 database - The datasets contained here are part of the International Centre for Tropical Agriculture (CIAT) and The CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). We apply a simple downscaling method (named delta method), based on the sum of interpolated anomalies from CMIP to high resolution monthly climate surfaces. The method produces high resolution climate change data that can be used for crop modeling, niche modeling, and more generally, for assessing impacts of climate change on agriculture at fine scales. For more detailed information visit the main page of CCAFS: https://ccafs.cgiar.org and CCAFS-Climate portal https://ccafs-climate.org Funding: This project was implemented as part of the CCAFS, which is carried out with support from CGIAR Fund Donors and through bilateral funding agreements. For details, please visit https://ccafs.cgiar.org/donors . Summary: We developed a global dataset of downscaled future projections developed by applying a statistical method for climate model downscaling and bias correction. To develop the dataset, 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 (mean of 2020-2049), 2050s (2040-2069), 2070s (2060-2089) and 2080s (2070-2099) with three climate variables (mean monthly maximum and minimum temperatures and monthly rainfall). From these, we also derive a set of bioclimatic indices.