Evidence map›Paper›PMID 41261146›Full record

ArticleScientific data2025

A multi-model based dataset of global atmospheric moisture source-sink relationships and atmospheric basins.

Yu Zhang, Deyu Zhong, Rongrong Cai, Mingxi Zhang, Yinglin Tian, Di Xie, Yuan Cao, Yuantao Mei

Abstract read
PubMed Full text at PMC Publisher
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.

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

8 authors.

Yu ZhangState Key Laboratory of Hydroscience and Engineering, Key Laboratory of Hydrosphere Sciences of the Ministry of Water Resources, Department of Hydraulic Engineering, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0001-7317-3752
Deyu ZhongState Key Laboratory of Hydroscience and Engineering, Key Laboratory of Hydrosphere Sciences of the Ministry of Water Resources, Department of Hydraulic Engineering, Tsinghua University, Beijing, China. zhongdy@tsinghua.edu.cn.
Rongrong CaiInternational Economic & Technical Cooperation and Exchange Center, Ministry of Water Resources, Beijing, China.
Mingxi ZhangState Key Laboratory of Hydroscience and Engineering, Key Laboratory of Hydrosphere Sciences of the Ministry of Water Resources, Department of Hydraulic Engineering, Tsinghua University, Beijing, China.
Yinglin TianState Key Laboratory of Hydroscience and Engineering, Key Laboratory of Hydrosphere Sciences of the Ministry of Water Resources, Department of Hydraulic Engineering, Tsinghua University, Beijing, China.
Di XieState Key Laboratory of Hydroscience and Engineering, Key Laboratory of Hydrosphere Sciences of the Ministry of Water Resources, Department of Hydraulic Engineering, Tsinghua University, Beijing, China.
Yuan CaoState Key Laboratory of Hydroscience and Engineering, Key Laboratory of Hydrosphere Sciences of the Ministry of Water Resources, Department of Hydraulic Engineering, Tsinghua University, Beijing, China.
Yuantao MeiState Key Laboratory of Hydroscience and Engineering, Key Laboratory of Hydrosphere Sciences of the Ministry of Water Resources, Department of Hydraulic Engineering, Tsinghua University, Beijing, China.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52209026
6 · The paper itself

Abstract

A comprehensive understanding of the atmospheric hydrological cycle is crucial for studying the transboundary impacts of climate and anthropogenic changes on global water resources. This study presents AMSSRAB, a global dataset of atmospheric moisture source-sink relationships (AMSSRs) between evaporation and precipitation locations, and the derived atmospheric basins (ABs) that regionalize the global atmospheric hydrological cycle. By integrating three atmospheric moisture tracking models (WAM2layers, UTrack, and WaterSip), AMSSRAB provides a multi-model ensemble representation of atmospheric moisture flows. The dataset provides seasonal atmospheric moisture source-sink relationships at 1° resolution over 40 years (1979-2018). The derived atmospheric basins identify quasi-independent moisture circulation systems characterized by high internal recycling. AMSSRAB demonstrates strong agreement with bias-corrected reconstruction data and previously published datasets while offering a regional perspective that complements existing evaporationshed-precipitationshed frameworks. This dataset enables researchers to investigate moisture source-sink relationships at multiple scales, analyze regional moisture recycling patterns, and examine atmospheric moisture responses to climate variability within the Earth's atmospheric water system.

Identifiers

PMID41261146
PMCPMC12630925

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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.