气候变化领域集成服务门户(CCPortal): Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

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DOI	10.5194/hess-22-287-2018
	Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables
	Mortensen E.; Wu S.; Notaro M.; Vavrus S.; Montgomery R.; De Piérola J.; Sánchez C.; Block P.
发表日期	2018
ISSN	1027-5606
起始页码	287
结束页码	303
卷号	22 期号:1
英文摘要	Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semiarid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Meteorological droughts in this region are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region's hydrologic cycle. An extensive season-ahead precipitation prediction model is developed to help bolster the existing capacity of stakeholders to plan for and mitigate deleterious impacts of drought. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to 11 potential predictors to produce an ensemble forecast of regional January-March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. The information provided by the developed model and ancillary modeling efforts, such as extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet-dry days per rainy season, may further assist regional stakeholders and policymakers in preparing for drought. © 2018 Author(s).
语种	英语
scopus关键词	Arid regions; Atmospheric pressure; Forecasting; Nickel; Oceanography; Principal component analysis; Surface waters; Ensemble forecasts; Meteorological drought; Precipitation predictions; Principal component regression; Ranked probability skill scores; Sea surface temperature (SST); Southern oscillation index; Spatiotemporal variability; Drought; air-sea interaction; climate change; drought; El Nino; El Nino-Southern Oscillation; ensemble forecasting; hydrological cycle; index method; precipitation (climatology); prediction; regression analysis; sea surface salinity; sea surface temperature; semiarid region; spatiotemporal analysis; stakeholder; Peru
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/160150
作者单位	Mortensen, E., Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, 53706, United States; Wu, S., Nelson Institute Center for Climatic Research, University of Wisconsin-Madison, Madison, 53706, United States; Notaro, M., Nelson Institute Center for Climatic Research, University of Wisconsin-Madison, Madison, 53706, United States; Vavrus, S., Nelson Institute Center for Climatic Research, University of Wisconsin-Madison, Madison, 53706, United States; Montgomery, R., Montgomery Assoc. Resource Solutions LLC, Cottage Grove, 53527, United States; De Piérola, J., Southern Peru Copper Corporation, Santiago-de Surco-Lima, 33, Peru; Sánchez, C., Southern Peru Copper Corporation, Santiago-de Surco-Lima, 33, Peru; Block, P., Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, 53706, United States
推荐引用方式 GB/T 7714	Mortensen E.,Wu S.,Notaro M.,et al. Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables[J],2018,22(1).
APA	Mortensen E..,Wu S..,Notaro M..,Vavrus S..,Montgomery R..,...&Block P..(2018).Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables.Hydrology and Earth System Sciences,22(1).
MLA	Mortensen E.,et al."Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables".Hydrology and Earth System Sciences 22.1(2018).