Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1007/s00382-019-04749-6 |
Metrics for understanding large-scale controls of multivariate temperature and precipitation variability | |
O&1; 39;Brien, John P.2; 39;Brien, Travis A.3 | |
2019-10-01 | |
发表期刊 | CLIMATE DYNAMICS
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ISSN | 0930-7575 |
EISSN | 1432-0894 |
出版年 | 2019 |
卷号 | 53页码:3805-3823 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Two or more spatio- temporally co-located meteorological/climatological extremes (co-occurring extremes) place far greater stress on human and ecological systems than any single extreme could. This was observed during the California drought of 2011-2015 where multiple years of negative precipitation anomalies occurred simultaneously with positive temperature anomalies resulting in California's worst drought on observational record. The large-scale drivers which modulate the occurrence of extremes in two or more variables remains largely unexplored. Using California wintertime (November-April) temperature and precipitation as a case study, we apply a novel, nonparametric conditional probability distribution method that allows for evaluation of complex, multivariate, and nonlinear relationships that exist among temperature, precipitation, and various indicators of large-scale climate variability and change. We find that multivariate variability and statistics of temperature and precipitation exhibit strong spatial variation across scales that are often treated as being homogeneous. Further, we demonstrate that the multivariate statistics of temperature and precipitation are highly non-stationary and therefore require more robust and sophisticated statistical techniques for accurate characterization. Of all the indicators of the large-scale climate conditions we studied, the dipole index explains the greatest fraction of multivariate variability in the co-occurrence of California wintertime extremes in temperature and precipitation. |
英文关键词 | ENSO El Nino La Nina PDO AMO Global change Climate variability Teleconnections California Joint extremes Precipitation extremes Non-stationarity |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000489753900006 |
WOS关键词 | NORTH AMERICAN REGION ; CALIFORNIA DROUGHT ; ARCTIC AMPLIFICATION ; UNITED-STATES ; PACIFIC ; ENSO ; TELECONNECTIONS ; WINTER ; OSCILLATION ; EXTREMES |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/187195 |
专题 | 气候变化 |
作者单位 | 1.Univ Calif Santa Cruz, Dept Earth & Planetary Sci, 1156 High St, Santa Cruz, CA 95064 USA; 2.Lawrence Berkeley Natl Lab, Climate & Ecosyst Sci Div, 1 Cyclotron Rd,MS74R-316C, Berkeley, CA 94720 USA; 3.Utah State Univ, Dept Plants Soils & Climate, 4820 Old Main Hill, Logan, UT 84322 USA |
推荐引用方式 GB/T 7714 | O&,39;Brien, John P.,39;Brien, Travis A.. Metrics for understanding large-scale controls of multivariate temperature and precipitation variability[J]. CLIMATE DYNAMICS,2019,53:3805-3823. |
APA | O&,39;Brien, John P.,&39;Brien, Travis A..(2019).Metrics for understanding large-scale controls of multivariate temperature and precipitation variability.CLIMATE DYNAMICS,53,3805-3823. |
MLA | O&,et al."Metrics for understanding large-scale controls of multivariate temperature and precipitation variability".CLIMATE DYNAMICS 53(2019):3805-3823. |
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