Evaluation and Projection of Changes in Daily Maximum Wind Speed over China Based on CMIP6

Author:

Zha Jinlin12,Shen Cheng3,Wu Jian1,Zhao Deming2,Fan Wenxuan1,Jiang Huiping45,Zhao Tianbao1

Affiliation:

1. a Key Laboratory of Atmospheric Environment and Processes in the Boundary Layer over the Low-Latitude Plateau Region, Department of Atmospheric Science, Yunnan University, Kunming, China

2. b CAS Key Laboratory of Regional Climate and Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

3. c University of Gothenburg, Department of Earth Sciences–Regional Climate Group, Gothenburg, Sweden

4. d International Research Center of Big Data for Sustainable Development Goals (CBAS), Beijing, China

5. e CAS Key Laboratory of Digital Earth Science, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing, China

Abstract

Abstract Future changes in spatiotemporal features of the mean wind speed over China have been extensively reported, but future changes in the maximum wind speed, such as the daily maximum wind speed (DMWS), were rarely estimated. In this study, the performance of Coupled Model Intercomparison Project phase 6 (CMIP6) models in simulating the DMWS changes across China is evaluated, based on which the projection on DMWS is carried out under different shared socioeconomic pathways (SSPs). The observed DMWS shows a significant reduction during all four seasons, with the strongest decrease in spring and the weakest decrease in autumn. The DMWS increases from January to April and decreases from April to August. The spatiotemporal characteristics of the DMWS are captured by the multimodel ensemble of CMIP6; however, the reduction of DMWS in CMIP6 is weaker than those in observations. The performance of CMIP6 in simulating the future DMWS changes over China shows regional and seasonal discrepancies. The projected DMWS exhibits a reduction for all SSPs from 2021 to 2100, and the decreasing trend is increased accompanied by the strength in the forcing scenario. The lower-emission scenario likely avoids the long-term weakening of the DMWS. The effects of strength in forcing scenarios on the trends of DMWS are more significant than the DMWS climate state. The seasonal cycle of the projected DMWS under the different SSPs is consistent with the historical DMWS; however, the strength in the forcing scenario could induce enhanced variability in the month-to-month DMWS difference. Significance Statement Estimation and projection of daily maximum wind speed (DMWS) are crucial for many socioeconomic and environmental issues, as DMWS can induce damage to buildings and infrastructure and affect the air quality and frequency of dust storms, among many other aspects. Nevertheless, future changes in the DMWS have rarely been investigated in China. This paper suggests that the lower forcing scenario could effectively avoid the long-term reduction in DMWS. The seasonal cycle of the future DMWS is consistent with the historical DMWS; however, the stronger forcing scenario induces the strengthening of the month-to-month wind speed difference variability. This study provides a scientific basis for decision-makers to formulate policies to deal with climate change.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Swedish Formas

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference98 articles.

1. On the projected decline in droughts over South Asia in CMIP6 multimodel ensemble;Aadhar, S.,2020

2. Sensitivity of precipitation forecast skill scores to bilinear interpolation and a simple nearest-neighbor average on high-resolution verification grids;Accadia, C.,2003

3. Recent homogeneity analysis and long-term spatiotemporal rainfall trends in Nigeria;Akinsanola, A. A.,2017

4. Projected changes in seasonal precipitation extremes over the United States in CMIP6 simulations;Akinsanola, A. A.,2020

5. Projected changes in wind speed and wind energy potential over West Africa in CMIP6 models;Akinsanola, A. A.,2021

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3