Adjustment of Intensity-Duration-Frequency Curves Under Changing Climate

The impact of climate change on extreme rainfall events presents a critical challenge for urban planning, agriculture, and water resource management. This study aims to redefine Depth-Duration-Frequency (DDF) curves under changing climate conditions, focusing on the Veneto region in Northern Italy. Utilizing data from 29 rain gauge stations, we observed significant variability in rainfall patterns, which raises questions about the applicability of traditional, stationary DDF curves for future infrastructure planning. To improve the predictive capability of DDF curves, we employed Convection-Permitting Models (CPMs) and compared their outputs with observational data. While initial comparisons revealed biases in the CPMs, bias-correction techniques significantly improved the model's alignment with observational data. Our results indicate that there is a projected increase in 1-hour rainfall across a range of return periods by the year 2100. Specifically, increases ranged from 29% to 66% for various return periods after bias-correction. The study reveals that traditional methods based on the Clausius-Clapeyron relation may not be sufficient for capturing the nuances of extreme rainfall events, highlighting the importance of CPMs in future climate projections. The findings underscore the need for region-specific climate adaptation strategies and pave the way for more robust, climate-resilient infrastructure planning. These insights are not just pertinent for Northern Italy but could be indicative of larger, global patterns, emphasizing on how we approach climate change mitigation and adaptation.