Quantification of Long-Range Dependence in Hydroclimatic Time Series: A Method-Comparison Study
文献类型：期刊论文
| 作者 | Niu, Jingyi; Xie, Ping; Sang, Yan-Fang; Zhang, Liping; Wu, Linqian6; Sivakumar, Ellie5; Huo, Jingqun; Chen, Deliang4 |
| 刊名 | JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY
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| 出版日期 | 2023-12-01 |
| 卷号 | 62期号:12页码:1921-1942 |
| 关键词 | Regression analysis Statistical techniques Time series Stochastic models Climate variability |
| DOI | 10.1175/JAMC-D-23-0129.1 |
| 产权排序 | 2 |
| 文献子类 | Article |
| 英文摘要 | Accurate evaluation of the long-range dependence in hydroclimatic time series is important for understanding its inherent characteristics. However, the reliability of its evaluation may be questioned, since different methods may yield various outcomes. In this study, we evaluate the performances of seven widely used methods for estimating longrange estimation, periodogram estimation, wavelet estimation (WLE), and discrete second derivative estimation (DSDE). We examine the influences of six major factors: data length, mean value, three nonstationary components (trend, jump, and periodicity), and one stationary component (short-range dependence). Results from the Monte Carlo experiments show that WLE and DSDE have greater credibility than the other five methods. They also reveal that data length, as well as stationary and nonstationary components, have notable influences on the evaluation of long-range dependence. Following it, we use the WLE and DSDE methods to evaluate the long-range dependence of precipitation during 1961-2015 on the Tibetan Plateau. The results indicate that the precipitation variability mirrors the long-range dependence of the Indian summer monsoon but with obvious spatial difference. This result is consistent with the observations made by previous studies, further confirming the superiority of the WLE and DSDE methods. The outcomes from this study have important implications for modeling and prediction of hydroclimatic time series. |
| WOS关键词 | DISCRETE WAVELET SPECTRUM ; PRECIPITATION ; MULTIFRACTALITY ; PREDICTABILITY ; TRENDS ; MEMORY |
| WOS研究方向 | Meteorology & Atmospheric Sciences |
| 出版者 | AMER METEOROLOGICAL SOC |
| WOS记录号 | WOS:001129101200001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/200978]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 作者单位 | 1.Wuhan Univ, State Key Lab Water Resources Engn & Management, Wuhan, Peoples R China 2.Inst Geog Sci & Nat Resources Res, Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China 3.Univ Gothenburg, Dept Earth Sci, Reg Climate Grp, Gothenburg, Sweden 4.Indian Inst Technol, Dept Civil Engn, Mumbai, India 5.Minist Ecol & Environm, Yellow River Basin Ecol Environm Supervis Adm, Yellow River Ecol Environm Sci Res Inst, Zhengzhou, Peoples R China 6.Univ Chinese Acad Sci, Beijing, Peoples R China 7.Minist Emergency Management China, Key Lab Cpd & Chained Nat Hazards Dynam, Beijing, Peoples R China 8.Yarlung Zangbo Grand Canyon Water Cycle Monitoring, Linzhi, Peoples R China |
| 推荐引用方式 GB/T 7714 | Niu, Jingyi,Xie, Ping,Sang, Yan-Fang,et al. Quantification of Long-Range Dependence in Hydroclimatic Time Series: A Method-Comparison Study[J]. JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY,2023,62(12):1921-1942. |
| APA | Niu, Jingyi.,Xie, Ping.,Sang, Yan-Fang.,Zhang, Liping.,Wu, Linqian.,...&Chen, Deliang.(2023).Quantification of Long-Range Dependence in Hydroclimatic Time Series: A Method-Comparison Study.JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY,62(12),1921-1942. |
| MLA | Niu, Jingyi,et al."Quantification of Long-Range Dependence in Hydroclimatic Time Series: A Method-Comparison Study".JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY 62.12(2023):1921-1942. |
入库方式： OAI收割
来源：地理科学与资源研究所
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