Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2016WR020086 |
Droughts in Amazonia: Spatiotemporal Variability, Teleconnections, and Seasonal Predictions | |
Lima, Carlos H. R.1; AghaKouchak, Amir2 | |
2017-12-01 | |
发表期刊 | WATER RESOURCES RESEARCH
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ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2017 |
卷号 | 53期号:12 |
文章类型 | Article |
语种 | 英语 |
国家 | Brazil; USA |
英文摘要 | Most Amazonia drought studies have focused on rainfall deficits and their impact on river discharges, while the analysis of other important driver variables, such as temperature and soil moisture, has attracted less attention. Here we try to better understand the spatiotemporal dynamics of Amazonia droughts and associated climate teleconnections as characterized by the Palmer Drought Severity Index (PDSI), which integrates information from rainfall deficit, temperature anomalies, and soil moisture capacity. The results reveal that Amazonia droughts are most related to one dominant pattern across the entire region, followed by two seesaw kind of patterns: north-south and east-west. The main two modes are correlated with sea surface temperature (SST) anomalies in the tropical Pacific and Atlantic oceans. The teleconnections associated with global SST are then used to build a seasonal forecast model for PDSI over Amazonia based on predictors obtained from a sparse canonical correlation analysis approach. A unique feature of the presented drought prediction method is using only a few number of predictors to avoid excessive noise in the predictor space. Cross-validated results show correlations between observed and predicted spatial average PDSI up to 0.60 and 0.45 for lead times of 5 and 9 months, respectively. To the best of our knowledge, this is the first study in the region that, based on cross-validation results, leads to appreciable forecast skills for lead times beyond 4 months. This is a step forward in better understanding the dynamics of Amazonia droughts and improving risk assessment and management, through improved drought forecasting. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000423299000045 |
WOS关键词 | INTERANNUAL VARIABILITY ; SEVERITY INDEX ; CLIMATE-CHANGE ; SOIL-MOISTURE ; UNITED-STATES ; MULTIVARIATE ; FOREST ; ENSO ; DEFORESTATION ; PATTERNS |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
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/19999 |
专题 | 资源环境科学 |
作者单位 | 1.Univ Brasilia, Dept Civil & Environm Engn, Brasilia, DF, Brazil; 2.Univ Calif Irvine, Dept Civil & Environm Engn, Irvine, CA USA |
推荐引用方式 GB/T 7714 | Lima, Carlos H. R.,AghaKouchak, Amir. Droughts in Amazonia: Spatiotemporal Variability, Teleconnections, and Seasonal Predictions[J]. WATER RESOURCES RESEARCH,2017,53(12). |
APA | Lima, Carlos H. R.,&AghaKouchak, Amir.(2017).Droughts in Amazonia: Spatiotemporal Variability, Teleconnections, and Seasonal Predictions.WATER RESOURCES RESEARCH,53(12). |
MLA | Lima, Carlos H. R.,et al."Droughts in Amazonia: Spatiotemporal Variability, Teleconnections, and Seasonal Predictions".WATER RESOURCES RESEARCH 53.12(2017). |
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