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Projections of climate change are available at coarse scales (70-400 km). But agricultural and species models typically require finer scale climate data to model climate change impacts. Here, we present a global database of future climates developed by applying the delta method -a method for climate model bias correction. We performed a technical evaluation of the bias-correction method using a 'perfect sibling' framework and show that it reduces climate model bias by 50-70%. The data include monthly maximum and minimum temperatures and monthly total precipitation, and a set of bioclimatic indices, and can be used for assessing impacts of climate change on agriculture and biodiversity. The data are publicly available in the World Data Center for Climate (WDCC; cera-www. dkrz.de), as well as in the CCAFS-Climate data portal (http://ccafs-climate.org). The database has been used up to date in more than 350 studies of ecosystem and agricultural impact assessment. 1 international center for tropical Agriculture (ciAt), cali, colombia. 2 cGiAR Research Program on climate change, Agriculture and food Security (ccAfS), c/o ciAt, cali, colombia. 3 international Livestock Research institute (iLRi), nairobi, Kenya. 4 School of earth and environment, University of Leeds, Leeds, UK. *email: j.r.villegas@cgiar.org DATA DeSCrIPTor oPeN Scientific Data | (2020) 7:7 | https://doi.

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Coffee is grown in more than 60 tropical countries on over 11 million ha by an estimated 25 million farmers, most of whom are smallholders. Several regional studies demonstrate the climate sensitivity of coffee (Coffea arabica) and the likely impact of climate change on coffee suitability, yield, increased pest and disease pressure and farmers' livelihoods. The objectives of this paper are (i) to quantify the impact of progressive climate change to grow coffee and to produce high quality coffee in Nicaragua and (ii) to develop an adaptation framework across time and space to guide adaptation planning. We used coffee location and cup quality data from Nicaragua in combination with the Maxent and CaNaSTA crop suitability models, the WorldClim historical data and the CMIP3 global circulation models to predict the likely impact of climate change on coffee suitability and quality. We distinguished four different impact scenarios: Very high (coffee disappears), high (large negative changes), medium (little negative changes) and increase (positive changes) in climate suitability. During the Nicaraguan coffee roundtable, most promising adaptation strategies were identified, which we then used to develop a two-dimensional adaptation framework for coffee in time and space. Our analysis indicates that incremental adaptation may occur over