Evidence map›Paper›PMID 42642429›Full record

ArticleNature communications2026

Navigating optimal solar-wind trade-offs under climate change.

Jingyun Li, Dan Tong, Dongsheng Zheng, Yuanyuan Lin, Yuan Xu, Qiang Zhang

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

6 authors.

Jingyun LiDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China.
Dan TongDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China. dantong@tsinghua.edu.cn.ORCID http://orcid.org/0000-0003-3787-0707
Dongsheng ZhengDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0001-9712-5456
Yuanyuan LinDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China.
Yuan XuNational Climate Centre, China Meteorological Administration, Beijing, China.ORCID http://orcid.org/0000-0002-3539-4068
Qiang ZhangDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0002-8376-131X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The optimal solar-wind ratio (SWR) plays a critical role in shaping the cost and reliability of renewable electricity systems, yet its adaptability under climate change remains poorly understood. Here, we develop a climate-driven SWR optimization framework that couples multi-model climate projections with an integrated investment and dispatch model to quantify how future climate variability reshapes cost-optimal solar-wind configurations. We find that optimal SWRs exhibit pronounced latitudinal differences and show modest changes under climate change. Deployment pathways inherited from the historical preference scenario may diverge from optimal SWRs, leading to increases in system costs and capacity requirements. In many regions, these SWR mismatches amplify electricity supply costs far more than the cost impacts associated with climate-induced changes in renewable resources alone. Cost escalation is driven mainly by SWR mismatch rather than solely by climate-induced resource changes. These findings highlight the importance of climate-responsive and region-specific SWR optimization as a key element of resilient and economically efficient power system planning.

Identifiers

PMID42642429
PMCPMC13507135

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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.