气候变化领域集成服务门户(CCPortal): A global probabilistic dataset for monitoring meteorological droughts

CCPortal

DOI	10.1175/BAMS-D-19-0192.1
	A global probabilistic dataset for monitoring meteorological droughts
	Turco M.; Jerez S.; Donat M.G.; Toreti A.; Vicente-Serrano S.M.; Doblas-Reyes F.J.
发表日期	2020
ISSN	00030007
起始页码	E1628
结束页码	E1644
卷号	101 期号:10
英文摘要	Accurate and timely drought information is essential to move from postcrisis to preimpact drought-risk management. A number of drought datasets are already available. They cover the last three decades and provide data in near-real time (using different sources), but they are all “deterministic” (i.e., single realization), and input and output data partly differ between them. Here we first evaluate the quality of long-term and continuous climate data for timely meteorological drought monitoring considering the standardized precipitation index. Then, by applying an ensemble approach, mimicking weather/climate prediction studies, we develop Drought Probabilistic (DROP), a new global land gridded dataset, in which an ensemble of observation-based datasets is used to obtain the best near-real-time estimate together with its associated uncertainty. This approach makes the most of the available information and brings it to the end users. The high-quality and probabilistic information provided by DROP is useful for monitoring applications, and may help to develop global policy decisions on adaptation priorities in alleviating drought impacts, especially in countries where meteorological monitoring is still challenging. © 2020 American Meteorological Society. All rights reserved.
语种	英语
scopus关键词	Drops; Risk management; Uncertainty analysis; Ensemble approaches; Global policies; Input and outputs; Meteorological drought; Meteorological monitoring; Monitoring applications; Probabilistic information; Standardized precipitation index; Drought
来源期刊	Bulletin of the American Meteorological Society
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/177801
作者单位	Regional Atmospheric Modeling Group, Department of Physics, University of Murcia, Murcia, Spain; Earth Science Department, Barcelona Supercomputing Center, Barcelona, Spain; European Commission, Joint Research Centre, Ispra, Italy; Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas, Zaragoza, Spain; Earth Science Department, Barcelona Supercomputing Center, ICREA, Barcelona, Spain
推荐引用方式 GB/T 7714	Turco M.,Jerez S.,Donat M.G.,et al. A global probabilistic dataset for monitoring meteorological droughts[J],2020,101(10).
APA	Turco M.,Jerez S.,Donat M.G.,Toreti A.,Vicente-Serrano S.M.,&Doblas-Reyes F.J..(2020).A global probabilistic dataset for monitoring meteorological droughts.Bulletin of the American Meteorological Society,101(10).
MLA	Turco M.,et al."A global probabilistic dataset for monitoring meteorological droughts".Bulletin of the American Meteorological Society 101.10(2020).