Evidence map›Paper›PMID 37954193›Full record

ArticleNational science review2023

How does Mei-yu precipitation respond to climate change?

Bo Sun, Rufan Xue, Wanling Li, Siyu Zhou, Huixin Li, Botao Zhou, Huijun Wang

Abstract read
In one paragraph

Article in National science review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Bo SunCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disasters, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Rufan XueCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disasters, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Wanling LiCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disasters, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Siyu ZhouCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disasters, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Huixin LiCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disasters, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Botao ZhouCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disasters, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China.ORCID https://orcid.org/0000-0002-5995-2378
Huijun WangCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disasters, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mei-yu is an important weather phenomenon in the middle-lower Yangtze River valley (YRV) region. This study investigates the changes in the characteristics of Mei-yu under global warming and the potential reasons based on observation and reanalysis data during 1961-2022. Notable increasing long-term trends are detected in the number of days without rainfall (NDWOR), the intensity of rainfall events, and the frequency and intensity of extreme precipitation events (EPEs) in the YRV region during the Mei-yu period (15 June-10 July) over past decades. The increasing trend in NDWOR is attributed to decreased relative humidity over land surface and a longer time for the air to be replenished with moisture after rainfall events in a warming climate. The increasing trends in the intensity of rainfall events and frequency/intensity of EPEs are attributed to the strengthened transient water vapor convergence and convection in the atmosphere under global warming. Furthermore, the response of Mei-yu to 2°C of global warming with respect to the pre-industrial climate is analysed using CMIP6 models. The results suggest that the NDWOR, intensity of rainfall events and frequency of EPEs will increase in the YRV region during the Mei-yu period under the 2°C warming scenario, which implies a more challenging climate risk management in the future. Overall, the intensity of rainfall events during the Mei-yu period has the most significant response to climate change in observations and projections. The model results have a relatively large uncertainty.

Indexed as

2°C warming scenariodays without rainfallextreme precipitation eventsMei-yuwater vapor

Identifiers

PMID37954193
PMCPMC10632799

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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.