Evidence map›Paper›PMID 41501076›Full record

ArticleNature communications2026

Global increase in rain rate of tropical cyclones prior to landfall.

Quanjia Zhong, Jianping Gan, Shifei Tu, Ralf Toumi, Johnny C L Chan

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
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

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

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

5 authors.

Quanjia ZhongCenter for Ocean Research in Hong Kong and Macau (CORE) and Department of Ocean Science, Hong Kong University of Science and Technology, Hong Kong, China.ORCID http://orcid.org/0000-0002-6774-3146
Jianping GanCenter for Ocean Research in Hong Kong and Macau (CORE) and Department of Ocean Science, Hong Kong University of Science and Technology, Hong Kong, China. magan@ust.hk.ORCID http://orcid.org/0000-0001-9827-7929
Shifei TuSouth China Sea Institute of Marine Meteorology/Western Guangdong Key Laboratory of Marine Meteorological Disaster Theory and Application, College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang, China.ORCID http://orcid.org/0000-0003-3720-6259
Ralf ToumiDepartment of Physics, Imperial College London, London, UK.ORCID http://orcid.org/0000-0002-5203-1883
Johnny C L ChanAsia-Pacific Typhoon Collaborative Research Center, Shanghai, China. Johnny.Chan@cityu.edu.hk.ORCID http://orcid.org/0000-0001-8390-7422

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most studies on tropical cyclone (TC) rain rate focus on long-term variability, yet the short-term (days or shorter) variations across the TC lifecycle, with a particular focus on the period before landfall, are most critical because they strongly influence flood risk. Using satellite data, we show that, globally, the mean rain rate of TCs increases by over 20% from 60 hours before landfall to the time of landfall. This increase occurs across hemispheres, ocean basins, intensity categories, and latitudes, although the magnitude varies. As a TC approaches the coast, land-sea thermal contrasts raise low-level humidity over land, while frictional differences enhance convergence, upward motion, and instability on the offshore side of the circulation. These conditions collectively promote increased convection and precipitation of TCs as they near landfall. Our findings critically strengthen the current understanding of TC precipitation dynamics and support more effective flood management.

Identifiers

PMID41501076
PMCPMC12779963

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.