Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2018WR023892 |
Multivariate Nonstationary Oscillation Simulation of Climate Indices With Empirical Mode Decomposition | |
Lee, Taesam1; Ouarda, Taha B. M. J.2 | |
2019-06-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2019 |
卷号 | 55期号:6页码:5033-5052 |
文章类型 | Article |
语种 | 英语 |
国家 | South Korea; Canada |
英文摘要 | The objective of the current study is to build a stochastic model to simulate climate indices that are teleconnected with the hydrologic regimes of large-scale water resources systems such as the Great Lakes system. Climate indices generally contain nonstationary oscillations (NSOs). We adopted a stochastic simulation model based on Empirical Mode Decomposition (EMD). The procedure for the model is to decompose the observed series and then to simulate the decomposed components with the NSO resampling (NSOR) technique. Because the model has only been previously applied to single variables, a multivariate version of NSOR (M-NSOR) is developed to consider the links between the climate indices and to reproduce the NSO process. The proposed M-NSOR model is tested in a simulation study on the Rossler system. The simulation results indicate that the M-NSOR model reproduces the significant oscillatory behaviors of the system and the marginal statistical characteristics. Subsequently, the M-NSOR model is applied to three climate indices (i.e., Arctic Oscillation, El Nino-Southern Oscillation, and Pacific Decadal Oscillation) for the annual and winter data sets. The results of the proposed model are compared to those of the Contemporaneous Shifting Mean and Contemporaneous Autoregressive Moving Average model. The results indicate that the proposed M-NSOR model is superior to the Contemporaneous Shifting Mean and Contemporaneous Autoregressive Moving Average model for reproducing the NSO process, while the other basic statistics are comparatively well preserved in both cases. The current study concludes that the proposed M-NSOR model can be a good alternative to simulate NSO processes and their teleconnections with climate indices. |
英文关键词 | Atlantic Oscillation climate indices ENSO multivariate simulation nonstationary oscillation Pacific Decadal Oscillation |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000477616900030 |
WOS关键词 | NINO-SOUTHERN-OSCILLATION ; TIME-SERIES ; TELECONNECTION PATTERNS ; GEOPOTENTIAL HEIGHT ; ARCTIC OSCILLATION ; VARIABILITY ; ENSO ; PRECIPITATION ; TEMPERATURE ; PACIFIC |
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/183984 |
专题 | 资源环境科学 |
作者单位 | 1.Gyeongsang Natl Univ, Dept Civil Engn, ERI, Jinju, South Korea; 2.INRS ETE, Natl Inst Sci Res, Stat Hydroclimatol, Quebec City, PQ, Canada |
推荐引用方式 GB/T 7714 | Lee, Taesam,Ouarda, Taha B. M. J.. Multivariate Nonstationary Oscillation Simulation of Climate Indices With Empirical Mode Decomposition[J]. WATER RESOURCES RESEARCH,2019,55(6):5033-5052. |
APA | Lee, Taesam,&Ouarda, Taha B. M. J..(2019).Multivariate Nonstationary Oscillation Simulation of Climate Indices With Empirical Mode Decomposition.WATER RESOURCES RESEARCH,55(6),5033-5052. |
MLA | Lee, Taesam,et al."Multivariate Nonstationary Oscillation Simulation of Climate Indices With Empirical Mode Decomposition".WATER RESOURCES RESEARCH 55.6(2019):5033-5052. |
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