Evidence map›Paper›PMID 40595670›Full record

ArticleNature communications2025

Asymmetric shifts in precipitation due to urbanization across global cities.

Jinghua Xiong, Yuting Yang, Long Yang, Dawen Yang

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Jinghua XiongState Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing, China.
Yuting YangState Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing, China. Yuting_Yang@tsinghua.edu.cn.ORCID http://orcid.org/0000-0002-4573-1929
Long YangSchool of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu Province, China.ORCID http://orcid.org/0000-0002-1872-0175
Dawen YangState Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing, China. yangdw@tsinghua.edu.cn.ORCID http://orcid.org/0000-0002-2383-1881

Funding

Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 2023YFC3006702Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 2023YFC3206603
6 · The paper itself

Abstract

Urbanization alters precipitation patterns by modifying thermal, dynamic, and chemical processes in the atmosphere. However, its effect on precipitation regimes, particularly at the sub-daily scale, is poorly understood. In this work, we use a high-resolution, spatially continuous satellite precipitation dataset to examine urbanization-induced shifts across precipitation intensities over global cities. We show that urbanization generally causes asymmetric shifts, increasing lower-intensity events and decreasing higher-intensity ones, with distinct patterns in tropical monsoon regions. These shifts, primarily driven by changes in event frequency, lead to reduced precipitation variability in urban areas, particularly in temperate cities and those exhibiting higher urbanization levels. Sub-daily analysis reveals that lower-intensity precipitation most notably increases in the early morning, while higher-intensity events decrease in the late afternoon, dampening diurnal precipitation variability. These findings offer important observational evidence of how urbanization alters precipitation regimes and highlight the need for adaptive urban water management strategies.

Identifiers

PMID40595670
PMCPMC12214829

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.