Projected increases in intensity and frequency of rainfall extremes through a regional climate modeling approach

Abstract Global warming is changing the hydrological cycle in multiple ways such as increased cloudiness, latent heat fluxes, and intense precipitation events. How extreme rainfall events will be influenced by the changing climate is becoming one of the most important problems for hydrological risk analysis and engineering design. In this study, a regional climate modeling approach based on the Providing REgional Climates for Impacts Studies modeling system is proposed for investigating the potential impacts of climate change induced by increased greenhouse gases on the intensity and frequency of extreme rainfall events in the context of Ontario, Canada. An ensemble of high‐resolution climate projections is first developed under both current and future forcing conditions. Validation of the ensemble simulations is then conducted through comparing the simulated rainfall annual extremes for 1960–1990 to the observed ones. Following that, the rainfall projections for future periods are used to develop projected intensity‐duration‐frequency curves and their plausible changes in 2030s, 2050s, and 2080s for the City of Toronto. The results suggest that intensities of rainfall extreme events versus various durations with different return periods are all likely to increase over time: [5, 17]% in 2030s, [11, 22]% in 2050s, and [25, 50]% in 2080s. Such a consistent increase would lead to an overall uplift in the exceedance values of rainfall intensity of extreme events, implying that intense rainfall events are likely to occur more frequently in the future. In addition, more significant changes in the rainfall intensity are projected for extreme events with longer return periods at all given durations. Key Points Projected IDF curves are developed using a regional climate modeling approach Intensities of rainfall extremes are projected to increase over time Intense rainfall events are likely to occur more frequently