These data were compiled to assess potential changes in the climatic suitability for 66 species (dominant and associate plant species) and forecast climate exposure for 29 major plant communities within major plant communities in the southwestern United States. An objective of our study was that species within plant communities have unique climate suitability signatures and forecast changes in climatic suitability will not be uniform within the species respective communities or among species within the community. The climate suitability spatial models were developed under a modern baseline (1960-90) and future climate scenario (2041-2060) using Maxent and WorldClim temperature and precipitation variables. Plant species were chosen that are characteristic species of plant communities in the southwest as mapped by GAP/LANDFIRE National Terrestrial Ecosystems v1 (USGS-Core Science Analytics, Synthesis, and Library – Gap Analysis Project, 2011). Monthly average minimum and maximum temperature and monthly total precipitation values were acquired from WorldClim v1.4 for current climate conditions and Community Climate System Model 4.0 (CCSM4, Gent et al. 2011) representative concentration pathway (rcp) models, 4.5 and 8.5, for the future climate scenario. The climate exposure spatial models are represented as a composite score of the climate exposure of characteristic plants for each community. Baseline climate exposure rasters represent a baseline climate change and were developed for current climate conditions (~1960-1990) from WordlClim v1.4 data. Climate exposure ratings are forecast for the period 2040-60 using the Community Climate System Model v4 (CCSM4) for Representative Concentration Pathways (RCP) 4.5 and 8.5. Climate exposure is indicated as a categorical score (1-5) that is a composite of climate suitability scores for characteristic plant species identified for each plant community and represents a range of climate exposure ratings from unfavorable to best climatic suitability. Plant communities are represented as mapped by the USGS – Core Science Analytics, Synthesis, and Library – Gap Analysis Project, 2011 (Gap Landcover).