Evidence map›Paper›PMID 42020429›Full record

ArticleNature communications2026

Strengthening influence of atmospheric rivers on global snow depth dynamics.

Haili Li, Chang-Qing Ke, Xiaoyi Shen, Suhui Wu, Qinghui Zhu, Yu Cai, Yao Xiao, Deliang Chen, Xixi Lu, Zheng Duan and 2 more

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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Haili LiSchool of Geography and Ocean Science, Nanjing University, Nanjing, China.
Chang-Qing KeSchool of Geography and Ocean Science, Nanjing University, Nanjing, China. kecq@nju.edu.cn.ORCID http://orcid.org/0000-0003-0212-4069
Xiaoyi ShenSchool of Earth Sciences and Engineering, Hohai University, Nanjing, China.
Suhui WuSchool of Geography and Ocean Science, Nanjing University, Nanjing, China.
Qinghui ZhuNanjing Police University, Nanjing, China.
Yu CaiSchool of Geography and Ocean Science, Nanjing University, Nanjing, China.
Yao XiaoSchool of Geography and Ocean Science, Nanjing University, Nanjing, China.
Deliang ChenDepartment of Earth System Science, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0003-0288-5618
Xixi LuDepartment of Geography, National University of Singapore, Kent Ridge, Singapore.ORCID http://orcid.org/0000-0002-2528-4631
Zheng DuanDepartment of Earth and Environmental Sciences, Lund University, Lund, Sweden.ORCID http://orcid.org/0000-0002-4411-8196
Liyin HeNicholas School of the Environment, Duke University, Durham, NC, USA.ORCID http://orcid.org/0000-0003-4427-1438
Yuyue XuSchool of Geography and Ocean Science, Nanjing University, Nanjing, China.ORCID http://orcid.org/0000-0002-5000-4232

Funding

National Natural Science Foundation of China (National Science Foundation of China) 42306201Natural Science Foundation of Jiangsu Province (Jiangsu Provincial Natural Science Foundation) BK20230799
6 · The paper itself

Abstract

Atmospheric rivers (ARs), narrow zones of intense water vapor transport in the Earth's atmosphere, play a pivotal role in driving heavy precipitation and temperature anomalies. Snowpack dynamics, essential for global water availability, are sensitive to variations in precipitation and temperature. However, the global influence of ARs on snowpack dynamics remains unclear. Here, we assess how ARs affect snow depth worldwide and explore the underlying physical mechanisms. Our results reveal that ARs drive strong intra-seasonal snowpack variability-generally increasing snow depth in winter and spring and decreasing it in summer (with declines exceeding 15% in Temperate regions) and autumn. Active El Niño-Southern Oscillation can amplify this influence. On interannual timescales, more frequent ARs are associated with reduced snow depth in summer but increased snow depth in other seasons. Snowfall emerges as the primary factor explaining interannual snowpack changes related to ARs. This study provides a crucial advancement in understanding the complex climate-snowpack relationship and underscores the need to represent AR-snowpack interactions in Earth system models.

Identifiers

PMID42020429
PMCPMC13314956

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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.