• extreme precipitation;
  • regional climate change;
  • exceedance probability

[1] Studies of extreme precipitation have documented changes at the continental scale during the twentieth century, but few studies have quantified changes at small to regional spatial scales during the same time. We analyze historic data from over 600 precipitation stations in the San Francisco Bay Area (SFBA), California, to assess whether there have been statistically significant changes in extreme precipitation between 1890 and 2010. An annual exceedance probability analysis of extreme precipitation events in the SFBA, coupled with a Markov chain Monte Carlo algorithm, reveals an increase in the occurrence of large events. The depth-duration-frequency characteristics of maximum annual precipitation events having durations of 1 h to 60 days indicate on average an increase in storm intensity in the last 120 years, with the intensity of the largest (least frequent) events increasing the most. Mean annual precipitation (MAP) also increased during the study period, but the relative increase in extreme event intensity exceeds that of MAP, indicating that a greater fraction of precipitation fell during large events. Analysis of data from subareas within the SFBA region indicates considerable heterogeneity in the observed nonstationarity; for example, the 5 day, 25 year event exceedance depth changed by +26%, +16%, and −1% in San Francisco, Santa Rosa, and San Jose, respectively. These results emphasize the importance of analyzing local data for accurate risk assessment, emergency planning, resource management, and climate model calibration.