Collaborative Research: CAS - Climate: Improving Nonstationary Intensity-Duration-Frequency Analysis of Extreme Precipitation by Advancing Knowledge on the Generating Mechanisms

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2221803 (Mascaro) and 2221808 (Kunkel). This project will address fundamental questions at the intersection of climate dynamics and civil engineering aimed at improving the design of infrastructure systems under climate change. Current procedures to design infrastructure against extreme precipitation and associated flooding rely on intensity-duration-frequency (IDF) curves. These curves are generated through statistical analyses of historical rain gage records under the assumptions of stationarity ("the future is the same as the past") and existence of a homogeneous statistical population ("the statistical variability of precipitation caused by multiple generating mechanisms is explained by a single distribution"). These assumptions have been recently challenged by theoretical arguments and climate simulations, which suggest that extreme precipitation (EP) statistics are expected to change in a future warmer climate. The main goal of this project is to advance knowledge on changes in the generating mechanisms of sub-daily and daily EP and use this new knowledge to develop a novel physics-driven statistical framework to inform the development of improved nonstationary IDF curves. Two research hypotheses will be investigated: (1) The occurrence and/or thermodynamic and dynamic components of the generating mechanisms of EP are changing in time, leading to changes in IDF design values; and (2) improved nonstationary IDF curves can be developed through statistical models that incorporate information on changes in the generating mechanisms of EP simulated by climate models. The research hypotheses will be tested using hourly and daily rainfall records, atmospheric re-analyses, and climate simulations in multiple regions of the U.S. spanning a wide range of dominant mechanisms of EP, including fronts, extratropical cyclones, tropical cyclones, mesoscale convective systems, air mass convection, and North American monsoon. New knowledge on the physical mechanisms leading to the non-stationarity of EP statistics at sub-daily and daily durations in the U.S. will be acquired by applying deep learning techniques. Novel methods for detection, physical validation, and uncertainty quantification of regional trends in EP and in occurrence and characteristics of the generating mechanisms will be designed by combining statistical tests and historical climate simulations from the Coupled Model Intercomparison Project Phase 6. This knowledge will inform a nonstationary statistical model for IDF analysis of EP that accounts for mixed populations. Regionalization techniques will be designed to reduce uncertainty in parameter estimation and incorporate regional changes in the physical mechanisms affecting EP. A Bayesian framework will be adopted to account for uncertainty. The added value of the nonstationary statistical model compared to current stationary approaches will be assessed through cross-validation bootstrapping experiments. The statistical model will be then applied with changes in EP mechanisms simulated by selected general circulation models under different future scenarios and used to compute new design metrics accounting for nonstationary extreme regimes. The methodological advancements are intended to address critical limitations of current stationary IDF design methods. Most importantly, there are multiple generating mechanisms for EP whose frequency and intensity may change in different ways in response to anthropogenically-forced climate change. The research will develop a framework for the objective incorporation of this knowledge into IDF curves, providing more robust estimates of future changes. This project is targeted to have multiple broader impacts. It seeks to improve infrastructure design and management against EP under climate change, which would (i) reduce storm-related damages ($261.1 billion from 2001 to 2020 in the U.S.), thus benefitting society; and (ii) increase the resilience of critical infrastructure, thus improving national security. The project will develop an outreach program that involves practitioner education through ongoing collaborations of the investigators with engineering and construction firms, public agencies, and the American Society of Civil Engineers. Additionally, the project will develop new aspects of curricula at the investigators’ institutions in the areas of engineering, hydrology, and atmospheric sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.