Characteristics of flash droughts and their association with compound meteorological extremes in China: Observations and model simulations

中国 闪光灯(摄影) 气候学 环境科学 暴发洪水 气候变化 地理 气象学 地质学 海洋学 物理 大洪水 光学 考古
作者
Yuqing Zhang,Qinglong You,Changchun Chen,Huaijun Wang,Safi Ullah,Liucheng Shen
出处
期刊:Science of The Total Environment [Elsevier BV]
卷期号:916: 170133-170133 被引量:14
标识
DOI:10.1016/j.scitotenv.2024.170133
摘要

Flash droughts have gained considerable public attention due to the imminent threats they pose to food security, ecological safety, and human health. Currently, there has been little research exploring the projected changes in flash droughts and their association with compound meteorological extremes (CMEs). In this study, we applied the pentad-mean water deficit index to investigate the characteristics of flash droughts and their association with CMEs based on observational data and downscaled model simulations. Our analysis reveals an increasing trend in flash drought frequency in China based on historical observations and model simulations. Specifically, the proportion of flash drought frequency with a one-pentad onset time showed a consistent upward trend, with the southern parts of China experiencing a high average proportion during the historical period. Furthermore, the onset dates of the first (last) flash droughts during year are projected to shift earlier (later) in a warmer world. Flash droughts become significantly more frequent in the future, with a growth rate approximately 1.3 times higher in the high emission scenario than in the medium emission scenario. The frequency of flash droughts with a one-pentad onset time also exhibits a significant upward trend, indicating that flash droughts will occur more rapidly in the future. CMEs in southern regions of China were found to be more likely to trigger flash droughts in the historical period. The probability of CMEs triggering flash droughts is expected to increase with the magnitude of warming, particularly in the far-future under the high emissions scenario.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
慧慧queen完成签到,获得积分10
1秒前
Xiao悔完成签到,获得积分10
1秒前
啦啦啦完成签到 ,获得积分10
3秒前
xss发布了新的文献求助10
3秒前
4秒前
肆意无雪发布了新的文献求助10
5秒前
所所应助那只鹿采纳,获得10
5秒前
huihui发布了新的文献求助10
6秒前
淡然夏瑶完成签到 ,获得积分10
7秒前
7秒前
7秒前
10秒前
10秒前
科研通AI2S应助黄黄采纳,获得10
10秒前
艾欧勾勾完成签到 ,获得积分10
10秒前
10秒前
甜蜜傲芙发布了新的文献求助10
11秒前
11秒前
Herbert完成签到,获得积分10
11秒前
化身孤岛的鲸完成签到 ,获得积分10
11秒前
小蘑菇应助肆意无雪采纳,获得10
12秒前
12秒前
lyq发布了新的文献求助10
12秒前
12秒前
ax发布了新的文献求助10
13秒前
AAA完成签到,获得积分10
13秒前
13秒前
一个巨型懒懒完成签到,获得积分10
13秒前
宁静完成签到,获得积分10
13秒前
13秒前
13秒前
14秒前
huihui完成签到,获得积分10
14秒前
14秒前
15秒前
搞怪的老九应助ZZzz采纳,获得10
16秒前
16秒前
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Rosenblum, Global Change Biology 800
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7774009
求助须知:如何正确求助?哪些是违规求助? 9316002
关于积分的说明 20348763
捐赠科研通 7359731
什么是DOI,文献DOI怎么找? 3317334
关于科研通互助平台的介绍 2465859
邀请新用户注册赠送积分活动 2332575