Evidence map›Paper›PMID 38665268›Full record

ArticleNPJ climate and atmospheric science2023

Causes of accelerated High-Tide Flooding in the U.S. since 1950.

Qiang Sun, Sönke Dangendorf, Thomas Wahl, Philip R Thompson

Abstract read
In one paragraph

Article in NPJ climate and atmospheric science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Coastal flooding at predictable hours.Nature communications · 2026
    Article
  2. Article
  3. Funding rules that promote equity in climate adaptation outcomes.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  4. 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

4 authors.

Qiang SunDepartment of River-Coastal Science and Engineering, Tulane University, 627 Lindy Claiborne Boggs Center, 6823 St. Charles Avenue, New Orleans, LA 70118 USA.ORCID 0000-0001-6753-2384
Sönke DangendorfDepartment of River-Coastal Science and Engineering, Tulane University, 627 Lindy Claiborne Boggs Center, 6823 St. Charles Avenue, New Orleans, LA 70118 USA.ORCID 0000-0002-3679-5234
Thomas WahlDepartment of Civil, Environmental and Construction Engineering and National Center for Integrated Coastal Research, University of Central Florida, Orlando, FL USA.ORCID 0000-0003-3643-5463
Philip R ThompsonDepartment of Oceanography, University of Hawai'i, Honolulu, HI USA.ORCID 0000-0002-0875-4208

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The U.S. coastlines have experienced rapid increases in occurrences of High Tide Flooding (HTF) during recent decades. While it is generally accepted that relative mean sea level (RMSL) rise is the dominant cause for this, an attribution to individual components is still lacking. Here, we use local sea-level budgets to attribute past changes in HTF days to RMSL and its individual contributions. We find that while RMSL rise generally explains > 84% of long-term increases in HTF days locally, spatial patterns in HTF changes also depend on differences in flooding thresholds and water level characteristics. Vertical land motion dominates long-term increases in HTF, particularly in the northeast, while sterodynamic sea level (SDSL) is most important elsewhere and on shorter temporal scales. We also show that the recent SDSL acceleration in the Gulf of Mexico has led to an increase of 220% in the frequency of HTF events over the last decade.

Indexed as

Climate-change impactsEnvironmental impact

Identifiers

PMID38665268
PMCPMC11041669

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.