Projecting U.S. coastal storm surge risks and impacts with deep learning

Rice, Julian R.; Balaguru, Karthik; Ticona Rollano, Fadia; Wilson, John E.; Daniel, William B.; Judi, David R.; Sun, Ning; Leung, L. Ruby

doi:10.1088/1748-9326/adfd74

Projecting U.S. coastal storm surge risks and impacts with deep learning

Journal Article · Tue Sep 02 00:00:00 EDT 2025 · Environmental Research Letters

DOI:https://doi.org/10.1088/1748-9326/adfd74· OSTI ID:2588591

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Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Storm surge is one of the deadliest hazards posed by tropical cyclones (TCs), yet assessing its current and future risk is difficult due to the phenomenon’s rarity and physical complexity. Recent advances in artificial intelligence applications to natural hazard modeling suggest a new avenue for addressing this problem. We develop a deep learning storm surge model to efficiently estimate coastal surge risk in the United States from 900 000 synthetic TC events, accounting for projected changes in TC behavior and sea levels. The derived historical 100 year surge (the event with a 1% yearly exceedance probability) agrees well with historical observations and other modeling techniques. When coupled with an inundation model, we find that heightened TC intensities and sea levels by the end of the century result in a 50% increase in population at risk. Key findings include markedly heightened risk in Florida, and critical thresholds identified in Georgia and South Carolina.

View Accepted Manuscript (DOE)

Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC02-05CH11231; AC05-76RL01830

OSTI ID:: 2588591

Report Number(s):: PNNL-SA--209420

Journal Information:: Environmental Research Letters, Journal Name: Environmental Research Letters Journal Issue: 10 Vol. 20; ISSN 1748-9326

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: United States

Language:: English

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