Evidence map›Paper›PMID 40783401›Full record

ArticleScientific data2025

US-CoastEX: Observation-based probabilistic reanalysis of storm surge and sea level extremes for the United States.

Joao Morim, D J Rasmussen, Thomas Wahl, Francisco M Calafat, Robert E Kopp, Michael Oppenheimer, Soenke Dangendorf

Abstract read
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Joao MorimDepartment of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, Florida, USA. jmorimnascimento@ucf.edu.
D J RasmussenPrinceton School of Public and International Affairs, Princeton University, Princeton, NJ, USA.
Thomas WahlDepartment of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, Florida, USA.ORCID http://orcid.org/0000-0003-3643-5463
Francisco M CalafatMarine Physics and Ocean Climate, National Oceanography Centre, Liverpool, UK.ORCID http://orcid.org/0000-0002-7474-135X
Robert E KoppDepartment of Earth and Planetary Sciences and Rutgers Climate & Energy Institute, Rutgers University, New Brunswick, NJ, USA.
Michael OppenheimerDepartment of Geosciences and Princeton School of Public and International Affairs and High Meadows Environmental Institute, Princeton University, Princeton, NJ, USA.
Soenke DangendorfTulane University, School of Science & Engineering, USA, Department of River-Coastal Science and Engineering, New Orleans, LA, USA.ORCID http://orcid.org/0000-0002-3679-5234

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reliable estimates of storm surge and sea level extremes with proper uncertainty quantification are key for cost-effective risk/adaptation planning. However, observational estimates are often unavailable or uncertain along most coastlines owing to data scarcity. Here, we provide a fully observational-driven probabilistic dataset (US-CoastEX) of storm surge and sea level extremes for the U.S. coast (1950-2020). Non-stationary extreme storm surge distributions are generated for gauged and ungauged sites by applying Bayesian methods to the U.S. tide gauge network, complemented with additional storm data unavailable in commonly used tide gauge data. The distributions are combined with tidal peak data to estimate return periods and levels of extreme sea levels and their uncertainty. Ou results show that traditional site-by-site estimates based on existing model data, as well as regionally-aggregated analysis of standard tide gauge data, have underestimated 100-year extreme sea levels by 50% (on average) along much of the U.S. coast, especially in regions exposed to extreme storms. The data supports coastal managers to make decisions, especially in vulnerable areas where in-situ sea-level monitoring is limited.

Identifiers

PMID40783401
PMCPMC12335592

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.