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Abstract The impacts of climate change on extreme rainfall characteristics at fine spatiotemporal scales are governed by substantial uncertainty, primarily due to the systematic error components inherited from conventional numerical prediction systems, and/or the intrinsic assumptions of the selected modeling schemes. Here, we attempt to robustly evaluate the effects of future climate scenarios on intensity‐duration‐frequency (IDF) curves over the entire Contiguous United States, while accounting for the nonstationary nature of the rainfall process across adequately fine spatiotemporal resolutions. To do so, we apply a parametric approach to statistically downscaled climate model outputs that reflect the Representative Concentration Pathway 8.5, which are offered by the North American Coordinated Regional Downscaling Experiment. Compared to traditional IDF estimation techniques, the employed framework is based on multifractal (MF) scaling arguments and assumes that the statistical structure of rainfall at interannual scales can be approximated by sequential realizations of a stationary MF process with parameters that vary slowly across (not within) realizations. The obtained results show that return period estimates exhibit significant downward trends over most of the domain, which slowly dampen with time, as the effects of climate change are more pronounced at lower exceedance probability levels. Given the observed rate of changes in the frequency and intensity of extreme rainfall for the remainder of the century, we argue that future infrastructure design should be strategically tailored to account for a wide range of potential outcomes.
Emmanouil et al. (Sat,) studied this question.