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