Observational Uncertainty for Global Drought‐Pluvial Volatility

Author:

Li Yichan1,Cheng Linyin1ORCID,Miao Chiyuan2ORCID,Liu Zhiyong34ORCID

Affiliation:

1. Department of Geosciences University of Arkansas Fayetteville AR USA

2. State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical Science Beijing Normal University Beijing China

3. Center for Water Resources and Environment School of Civil Engineering Sun Yat‐sen University Guangzhou China

4. Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Zhuhai China

Abstract

AbstractDroughts and pluvials have occurred in most regions in the past. However, what calls growing attention is the additive effects of these two opposite extreme events occurring in spatial‐temporal proximity to one another, sometimes beyond either of the hazards individually. This study examines the likelihood of global drought‐pluvial volatility which involves both meteorological drought‐to‐pluvial (DTP) and pluvial‐to‐meteorological drought transitions; meanwhile, identifies discrepancies and agreements among the widely used observations for such events, an aspect that remains currently overlooked. Globally, we find that the observation‐based data sets including Global Precipitation Climatology Center (GPCC), Climate Research Unit (CRU) and ERA5 reach a good agreement in estimating the event transition rates, with an average 15.46% (15.49%) of all meteorological droughts (pluvials) being succeeded by pluvials (meteorological droughts) in the following season. At the regional scale, our results reveal that the spatial variability and frequency associated with meteorological DTP transitions are slightly larger than that with pluvial‐to‐ meteorological drought transitions, but the observational uncertainty is more pronounced in the latter case as a result of greater uncertainty in the univariate drought depiction and enhanced regional divergence among the observed data. In general, GPCC and CRU exhibit higher consistency, albeit with less agreement under pluvial‐to‐ meteorological drought transitions, while ERA5 yields underestimations and reduced spatial variability considering both transition scenarios. The study highlights a need of using multiple independent observation‐based data sets for compound/multivariate extreme analysis, particularly in the context of climate‐related decision‐making, water resources planning, and future model validation studies.

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

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