Evidence map›Paper›PMID 39790104›Full record

ArticleNational science review2025

Unraveling climate change-induced compound low-solar-low-wind extremes in China.

Licheng Wang, Yawen Liu, Lei Zhao, Xi Lu, Liangdian Huang, Yana Jin, Steven J Davis, Amir Aghakouchak, Xin Huang, Tong Zhu and 1 more

Abstract read
In one paragraph

Article in National science review, 2025. 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

11 authors.

Licheng WangCollege of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
Yawen LiuSchool of Atmospheric Sciences, Nanjing University, Nanjing 210023, China.
Lei ZhaoDepartment of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Xi LuSchool of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China.ORCID https://orcid.org/0000-0002-5063-3776
Liangdian HuangCollege of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
Yana JinCollege of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
Steven J DavisDepartment of Earth System Science, University of California, Irvine, Irvine, CA 92697, USA.
Amir AghakouchakDepartment of Earth System Science, University of California, Irvine, Irvine, CA 92697, USA.
Xin HuangSchool of Atmospheric Sciences, Nanjing University, Nanjing 210023, China.
Tong ZhuCollege of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.ORCID https://orcid.org/0000-0002-2752-7924
Yue QinCollege of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

China's pursuit of carbon neutrality targets hinges on a profound shift towards low-carbon energy, primarily reliant on intermittent and variable, yet crucial, solar and wind power sources. In particular, low-solar-low-wind (LSLW) compound extremes present a critical yet largely ignored threat to the reliability of renewable electricity generation. While existing studies have largely evaluated the impacts of average climate-induced changes in renewable energy resources, comprehensive analyses of the compound extremes and, particularly, the underpinning dynamic mechanisms remain scarce. Here we show the dynamic evolution of compound LSLW extremes and their underlying mechanisms across China via coupling multi-model simulations with diagnostic analysis. Our results unveil a strong topographic dependence in the frequency of compound LSLW extremes, with a national average frequency of 16.4 (10th-90th percentile interval ranges from 5.3 to 32.6) days/yr, when renewable energy resources in eastern China are particularly compromised (∼80% lower than that under an average climate). We reveal a striking increase in the frequency of LSLW extremes, ranging from 12.4% under SSP126 to 60.2% under SSP370, primarily driven by both renewable energy resource declines and increasingly heavily-tailed distributions, resulting from weakened meridional temperature (pressure) gradient, increased frequency of extremely dense cloud cover and additional distinctive influence of increased aerosols under SSP370. Our study underscores the urgency of preparing for significantly heightened occurrences of LSLW events in a warmer future, emphasizing that such climate-induced compound LSLW extreme changes are not simply by chance, but rather projectable, thereby underscoring the need for proactive adaptation strategies. Such insights are crucial for countries navigating a similar transition towards renewable energy.

Indexed as

climate changecompound energy droughtsrenewable energysolar energywind energy

Identifiers

PMID39790104
PMCPMC11715666

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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.