FYI, in addition to the FutureClim, here is another downscaled GCM data collection (up to 30 arc-second, a.k.a., 1 km), being developed by Julian Ramirez (firstname.lastname@example.org) and Andy Jarvis (email@example.com) at CIAT.
Downscaled GCM Data Portal
From the website:
The datasets contained in this website are part of the International Centre for Tropical Agriculture (CIAT) climate change downscaled data, developed in the Decision and Policy Analysis (DAPA) program. The data have been originally downloaded from the IPCC data portal and re-processed using an spline interpolation algorithm of the anomalies and the current distribution of climates from the WorldClim database developed by Hijmans et al. (2005). All GCMs presented here come from the fourth and third IPCC Assessment Reports, but in further updates of the webpage, only models from the 4AR will be kept.
We assume that the geographies of changes in climates don’t vary too much at regional scales and that the relationships between the different variables will remain basically the same in the future. The surfaces provided here are thus generated using an empirical downscaling approach instead of re-modeling the climate patterns using an RCM (Regional Climate Model).
The downscaling process we follow is mainly the following: (1) calculation of anomalies (if they’re not provided directly by IPCC) by simply subtracting each variable’s future values with the baseline (both provided by IPCC), (2) interpolation of anomalies to a 30 arc-seconds resolution (approx. 1km) and (3) addition of the interpolated anomalies to the current distribution of climates in WorldClim, for temperature we make an absolute sum, but for precipitation (as there are differences between the GCM baseline and our WorldClim baseline), we use the relative difference.
All the datasets are available to direct-download from the site: