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  • Bias-corrected and downscaled future climate meterological forcing data for Africa, for the period 1948-2099. This dataset is derived from the Global Meteorological Forcing Dataset for Land Surface Modeling, produced by the Princeton University [Department of Civil and Environmental Engineering]. The source data is a 150-yr (1948-2099) dataset of meteorological forcings for driving land surface models and other land modeling schemes. It is derived by bias correcting and downscaling WCRP CMIP3 climate model data for the 20th century and 21st century future climate projections. The dataset is bias-corrected and downscaled using the newly developed equidistant quantile matching method (Li et al., 2010) which better represents changes in the full distribution (not just the mean change). In addition to precipitation and temperature, radiation, humidity, pressure and windspeed are also downscaled. The downsclaing is based on the observational based global forcing dataset of Sheffield et al. (2006) also available from this website. The dataset is currently available at 1.0 degree, 3-hourly resolution globally for 1948-2008. Experimental versions include a 1901-2008 version, real-time updates, higher resolution versions at 0.25deg and 0.5deg and future climate projections based on bias-corrected climate model output. The data are currently available for one climate model (NCAR-PCM1) for the 20th century historical forcing (20C3M; 1948-2000) and one future climate scenario (SRES A2; 2001-2099). This work was supported by NSF Project 0629471 "Collaborative research: Understanding change in the climate and hydrology of the Arctic land region: Synthesizing the results of the ARCSS Fresh Water Initiative Projects". Variables description Tair: 2 m air temperature (K) PSurf: 2 m surface pressure (Pa) Qair: specific humidity (kg/kg) Wind: 10m wind speed (m/s) Precip: precipitation (mm) LWdown: Downwards long-wave radiation flux (W/m-2) LWnet: Net short-wave radiation flux (W/m-2) SWdown: Downwards short-wave radiation flux (average) (W/m-2) This data set has been produced for driving land surface models and other land modeling schemes, in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 1 (WP1).