Climate change induced trends in long-term aridity—via changes to atmospheric water demand for have the potential to impact surface water availability across the globe by altering efficiency by which precipitation is converted to runoff. Quantification of aridity requires estimates of evaporative demand, often using vapor pressure deficit, potential evapotranspiration, and/or reference evapotranspiration, but no comprehensive estimate of these climate variables exists to date from the Coupled Model Intercomparison Project 6 (CMIP6). Here we present global monthly estimates of the Penman-Monteith short grass reference evapotranspiration, its advective and radiation components, Priestley-Taylor potential evapotranspiration, and vapor pressure deficit from 16 CMIP6 general circulation models (GCM) for the historical period and four future emission scenarios ranging from low to high projected emissions. The purpose of this dataset is to offer structured and well-documented estimates of historical and future projected evaporative demand derived from the state-of-the-science CMIP6 climate models for use in hydrologic and ecological analyses. We produce a single file for all monthly values of each variable for individual GCM/emission scenario combination gridded at the given GCMs native resolution. Produced alongside all of the files are descriptions of each of the variables and generated python scripts that contain the functions used to estimate vapor pressure deficit, potential evapotranspiration, and reference evapotranspiration.