Climate change is impacting the distribution of precipitation around the world, as blocking patterns lead to record-breaking rainfalls that result in heavy damages and casualties. The increased frequency and severity of precipitation extremes has tremendous impacts on engineering design, risk insurance and agricultural yields. Climate models are often able to provide physically-justified rainfall simulation for the near-future, but it is often necessary to apply bias correction to these model output. The calibration may be unsuitable for the extremes and fail to capture salient feature of observed time series. Different types of precipitation (e.g., orographic or convective rainfall) may be impacted differently by climate change.

The three talks in this session consider extreme value methods to on better understand drivers of precipitation extremes, perform sensitivity analysis for combinations of risk estimates, and to assess the suitability and calibration of climate model outputs by comparing them to weather station measurements.