Evidence map›Paper›PMID 32999892›Full record

ArticleEarth's future2020

Global Socioeconomic Risk of Precipitation Extremes Under Climate Change.

Yujie Liu, Jie Chen, Tao Pan, Yanhua Liu, Yuhu Zhang, Quansheng Ge, Philippe Ciais, Josep Penuelas

Abstract read
In one paragraph

Article in Earth's future, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Design Rainfall Change of Rainwater Source Control Facility to Meet Future Scenarios in Beijing.International journal of environmental research and public health · 2023
    Article
  6. Article
  7. 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.

Yujie LiuKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences (CAS) Beijing China.ORCID https://orcid.org/0000-0002-0751-6857
Jie ChenKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences (CAS) Beijing China.ORCID https://orcid.org/0000-0001-7403-9942
Tao PanKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences (CAS) Beijing China.
Yanhua LiuKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences (CAS) Beijing China.
Yuhu ZhangCapital Normal University Beijing China.
Quansheng GeKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences (CAS) Beijing China.
Philippe CiaisLaboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE CEA CNRS UVSQ Gif-sur-Yvette France.
Josep PenuelasCSIC, Global Ecology CREAF-CSIC-UAB Barcelona Catalonia Spain.ORCID https://orcid.org/0000-0002-7215-0150

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precipitation extremes are among the most serious consequences of climate change around the world. The observed and projected frequency and intensity of extreme precipitation in some regions will greatly influence the social economy. The frequency of extreme precipitation and the population and economic exposure were quantified for a base period (1986-2005) and future periods (2016-2035 and 2046-2065) based on bias corrected projections of daily precipitation from five global climatic models forced with three representative concentration pathways (RCPs) and projections of population and gross domestic product (GDP) in the shared socioeconomic pathways (SSPs). The RCP8.5-SSP3 scenario produces the highest global population exposure for 2046-2065, with nearly 30% of the global population (2.97 × 10

Indexed as

climate changeprecipitation extremesRCP scenariossocioeconomic riskSSP scenarios

Identifiers

PMID32999892
PMCPMC7507788

What OpenQuestion holds

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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.