WorldClim version 2 has average monthly climate data for minimum, mean, and maximum temperature and for precipitation for 1970-2000. You can download the variables (minimum temperature (°C), maximum temperature (°C), average temperature (°C), precipitation (mm), solar radiation (kJ m-2 day-1), wind speed (m s-1) and water vapor pressure (kPa)) for different spatial resolutions, from 30 seconds (~1 km2) to 10 minutes (~340 km2). Each download is a "zip" file containing 12 GeoTiff (.tif) files, one for each month of the year (January is 1; December is 12).

Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis.

This dataset contains two metrics for climate change exposure using downscaled climate projections with the SRES A2 emissions scenario (Tabor and Williams, 2007).The metrics represent dissimilarity measurements of the squared Euclidean distance between seasonal (June–August and December–February) temperature and precipitation variables in the 20th century climate and mid-21st century climate. (1) disappearing climate risk - measure of dissimilarity between a pixel’s late 20th century climate and its closest matching pixel in the global set of 21st-century climates (2) novel climate risk - measure of dissimilarity between a pixel’s future climate and its closest matching pixel in the global set of late 20th-century climates.

This dataset contains two metrics for climate change exposure using downscaled climate projections with the SRES A2 emissions scenario (Tabor and Williams, 2007).The metrics represent dissimilarity measurements of the squared Euclidean distance between seasonal (June–August and December–February) temperature and precipitation variables in the 20th century climate and mid-21st century climate. (1) disappearing climate risk - measure of dissimilarity between a pixel’s late 20th century climate and its closest matching pixel in the global set of 21st-century climates (2) novel climate risk - measure of dissimilarity between a pixel’s future climate and its closest matching pixel in the global set of late 20th-century climates.

Indicator based upon the Land-Use Harmonization 2 (LUH2) gridded global land use maps produced by advanced Earth System Models (ESM) which model the combined pressures of land use conversion and fossil fuel emissions on the carbon-climate system (Hurtt et al. in prep). The pressure data is derived from the History Database of the Global Environment (HYDE). Primary vegetation is defined as natural vegetation (either forest or non-forest) that has never been impacted by human activities (e.g. agriculture or wood harvesting) since the start of the time series (850). However, such areas may be indirectly impacted by humans, for instance, through hunting, pollution or the introduction of invasive alien species. They still represent modelled estimates, and the uncertainty associated with the land use present within each particular grid cell increases as we step back in time through the series.

Climate risk data are used to identify climate stability or scope for climate-adaptation focused interventions. The recent datasets from Tabor et al. 2018 which assess climate change exposure using downscaled climate projections with the SRES A2 emissions scenario was selected for ranking climate risk, combining two measures of radically changing climates. Tabor highlight (a) the threat status of the climate, assigning high values where the late 20th century climates will cease to exist anywhere in the world and therefore this climate space is very threatened as it may be disappearing from the world; and (b) the distance from current climates, with high values indicating areas with novel climates not currently experienced anywhere in the world, and where there is high uncertainty on future species communities. Climate risk values are grouped by deciles whereby landscapes with moderate climate risk are deemed most appropriate for selection, in that there are some adaptation challenges that the LWP intervention may be able to tackle.