Seasonal and regional variations in extreme precipitation event frequency using CMIP5

Understanding how the frequency and intensity of extreme precipitation events are changing is important for regional risk assessments and adaptation planning. Here we use observational data and an ensemble of climate change model experiments (from the Coupled Model Intercomparison Project Phase 5 (CMIP5)) to examine past and potential future seasonal changes in extreme precipitation event frequency over the United States. Using the extreme precipitation index as a metric for extreme precipitation change, we find key differences between models and observations. In particular, the CMIP5 models tend to overestimate the number of spring events and underestimate the number of summer events. This seasonal shift in the models is amplified in projections. These results provide a basis for evaluating climate model skill in simulating observed seasonality and changes in regional extreme precipitation. Additionally, we highlight key sources of variability and uncertainty that can potentially inform regional impact analyses and adaptation planning.