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Extreme precipitation intensities have increased in all regions of the Contiguous United States (CONUS)¹ and are expected to further increase with warming at scaling rates of about 7% per degree Celsius (ref. 2), suggesting a significant increase of flash flood hazards due to climate change. However, the scaling rates between extreme precipitation and temperature are strongly dependent on the region, temperature³, and moisture availability⁴, which inhibits simple extrapolation of the scaling rate from past climate data into the future⁵. Here we study observed and simulated changes in local precipitation extremes over the CONUS by analysing a very high resolution (4 km horizontal grid spacing) current and high-end climate scenario that realistically simulates hourly precipitation extremes. We show that extreme precipitation is increasing with temperature in moist, energy-limited, environments and decreases abruptly in dry, moisture-limited, environments. This novel framework explains the large variability in the observed and modelled scaling rates and helps with understanding the significant frequency and intensity increases in future hourly extreme precipitation events and their interaction with larger scales.