Estimating how close a species is to its upper thermal limits (i.e., warming tolerance, a thermal sensitivity index) and how that proximity changes across space enables spatially explicit identification of species with increased extinction risk as temperatures increase. Yet, thermal sensitivity is often difficult to calculate because it is the result of many traits. We aimed to synthesize multiple traits into a single estimate of relative terrestrial thermal sensitivity for 13 anuran species in the southeastern United States. We employed models that incorporate traits and microclimate variation to (1) estimate species warming tolerance (the difference between species critical thermal maximum and modeled operative temperature, an estimate of body temperature) and (2) investigate how warming tolerance varied with latitude (whereby latitude represents different temperature regimes and external drivers of thermal sensitivity). We ran mechanistic niche models across a 12° latitudinal gradient and 10 years to estimate individual operative temperature. We calculated the minimum, 25th percentile (hottest quarter), and median daily minimum warming tolerance. Estimates of minimum warming tolerance spanned −5 to 10°C (Lithobates palustris and Gastrophryne carolinensis respectively) and differed among species. For most species, modeled operative temperatures exceeded species' critical thermal maximum during extreme warm temperatures (i.e., heat waves) in part of their range, and warming tolerance increased with latitude. During heat waves, five species had lower warming tolerance at higher latitudes, and three species' warming tolerance did not change with latitude. We identified species that are approaching their thermal limits in the Southeast and characterized spatial patterns of warming tolerance. Increased temperatures could increase anuran extinction risk, posing an additional challenge for threatened anuran species. Spatial patterns of warming tolerance were not consistent among species in our study, highlighting that patterns identified at higher taxonomic categories could be inconsistent at lower taxonomic categories.