We examine the relationship between hourly extreme precipitation and daily mean temperature across the Contiguous United States (CONUS) during the period 1950–2009. Logarithmically-transformed hourly extreme precipitation generally increases approximately linearly with the daily mean temperature. At most (about 80%) of the stations, regression slopes between hourly extreme precipitation and daily mean temperature are higher than 7%, the approximate Clausius-Clapyron rate. Stations located in the western coastal region exhibit the lowest regression slopes, with median regression slopes less than 7%, while stations in the northern tier of the CONUS showed higher regression slopes, with median regression slope of 16%. More stations (75%) exhibit regression slopes higher than 7% in summer than in winter (65%). Stations in the southern U.S. have higher regression slopes in winter than in summer, whereas stations in the northern U.S. have higher slopes in summer. It seems physically implausible that the intensity of extreme rainfall events could be as sensitive to local temperature as reflected by the regression slopes. Hence, these large values at least partially may be a consequence of factors relating to temperature gradients as opposed to temperature in its own right.