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Observed trends, theory and modelling results all suggest increases in future extreme precipitation due to climate warming. The largest increases are expected in short-duration events with less than a day. Relatively few previous studies have focused specifically on the projection of sub-daily precipitation extremes. In this study, a statistical downscaling method based on circulation patterns (CPs) is developed to project site-specific extreme hourly precipitation over the United Kingdom. First, a CP-classification categorizes extreme hourly precipitation events based on the underlying atmospheric pressure conditions on each day. An analogue day method is then used to find for each future day the most similar day in the past by comparing the predictor values of daily precipitation and temperature simulated by regional climate models (RCMs) with observations conditioned on different CPs and seasons. Finally, the maximum hourly precipitation records on the most similar days are extracted and perturbed using precipitation duration-temperature relationships. The applied statistical downscaling method is a combination of the analogue and the regression-based method. It is found that the statistical downscaling method is able to reproduce observed extreme hourly precipitation. In terms of future changes under a warmer climate, it is shown that increases in extreme hourly precipitation can be as high as 112% but are highly variable depending on the rainfall stations, the future time periods, the emission scenarios, and the different RCM runs.