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 (j.r.villegas@cgiar.org) and Andy Jarvis (a.jarvis@cgiar.org) at CIAT.

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Downscaled GCM Data Portal

http://gisweb.ciat.cgiar.org/GCMPage

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:
http://gisweb.ciat.cgiar.org/GCMPage/download.html

FYI: Spatially-downscaled climate projection datasets by Peter Jones (Waen Associates/CIAT), Philip Thornton (ILRI), and Jens Heinke (PIK) are now available to download at http://futureclim.info. The datasets currently include 5 arc-minute (a.k.a., 10 km) resolution, global coverage of three core variables (i.e., monthly rainfall, tmin, and tmax) and two derived variables (solar radiation and rainy days) for biophysical modeling applications, for four GCM’s (CNRM-CM3, CSIRO-Mk3.0, ECHam5, and MIROC 3.2), three emission scenarios (A1B, A2, B1) for two time slices (2030 and 2050).

By the way, please be aware that the consequences of misusing or misinterpreting climate projection data can be potentially very… harmful. If you have any question, please contact the authors. Even if you don’t have any question, we strongly encourage you to consult with the authors on the correct use and interpretation of the data and results in your research.

Happy Easter!
Jawoo (on behalf of HarvestChoice/IFPRI/CSI)

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Characteristically Generated Monthly Climate Data using Downscaled Climate Model Data from the IPCC's Fourth Assessment

Peter G Jones (p.jones@cgiar.org) | Waen Associates, Wales
Philip K Thornton (p.thornton@cgiar.org) | International Livestock Research Institute (ILRI)
Jens Heinke (heinke@pik-potsdam.de) | Potsdam Institute for Climate Impact Research (PIK)

Summary

This dataset was generated by a generalized downscaling (5 arc-minute) and data generation method that takes the outputs of a General Circulation Model and allows the stochastic generation of daily weather data that are to some extent characteristic of future climatologies. Such data can then be used to drive any impacts model that requires daily (or otherwise aggregated) weather data. A subset of the climate models and scenario runs carried out for 2007's Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) for two time slices (2030 and 2050) was used in this process.

Disclaimers

These downscaled climate data are NOT predictions of what the future climate will be like in any place. They are projections of possible future climate, and should be treated with considerable caution. There is a great deal of variability between different climate models, between different greenhouse gas emission scenarios, and between different downscaling methods. It is not possible to infer anything meaningful from one climate model and one scenario: that is merely one replicate from the future (essentially unknown) probability distribution of future climates at any one place. Users should note that these data represent possible future climatologies in different places; the data say nothing about how climate variability may change in the future, and cannot be used to infer anything meaningful about this. If you are AT ALL unsure as to how these data can be used and how they cannot be used, please contact one of the authors.

Download

Data: http://FutureClim.info
Readme: https://hc.box.net/shared/xc38lnbznn
Report: https://hc.box.net/shared/f2gk053td8