Identifying non-stationarity in the dependence structures of meteorological factors within and across seasons and exploring possible causes
文献类型：期刊论文
| 作者 | Dong, Haixia6; Huang, Shengzhi6; Wang, Hao5; Huang, Qiang6; Leng, Guoyong4; Li, Ziyan6; Li, Lin3; Peng, Jian1,2 |
| 刊名 | STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
 |
| 出版日期 | 2023-07-03 |
| 页码 | 19 |
| 关键词 | Non-stationarity identification Loess plateau Precipitation Temperature Drivers Changing environment |
| ISSN号 | 1436-3240 |
| DOI | 10.1007/s00477-023-02496-z |
| 通讯作者 | Huang, Shengzhi(huangshengzhi7788@126.com) |
| 英文摘要 | Precipitation (P) and temperature (T) are key components of the hydrometeorological system, and their dependence structures exhibit significant dynamic changes, including non-stationary behavior, in response to environmental variations. These changes affect local hydrological processes and impact the predictability of the hydrometeorological system. However, the dynamics of dependence structures among meteorological factors during corresponding and adjacent seasons, as well as their underlying causes, have not been fully revealed. Therefore, this study comprehensively explored the dynamics of the precipitation-temperature dependence structure (PTDS) and temperature-temperature dependence structure (TTDS), and their possible causes. Firstly, non-stationary of PTDS was identified using a copula model. Then the main drivers of PTDS were determined by the random forest (RF) model and variable projection importance (VIP) criteria. These drivers include both conventional factors such as local meteorological factors (e.g., P, T, wind speed (WS), vapor pressure, relative humidity and sunshine duration (SD)) and teleconnection factors (e.g., Sunspots, the Arctic Oscillation, Pacific Decadal Oscillation (PDO), El Nino-Southern Oscillation (ENSO)). Additionally, the normalized difference vegetation index (NDVI) was used to investigate the response of dependence structure to vegetation dynamics. Finally, the ridge regression model was applied to construct driver models for the dynamics of dependence structures. The Loess Plateau was selected as the study area because of its high ecological sensitivity and typical human afforestation activities. The results show that: (1) non-stationarity in the PTDS occurred in different seasons and at various stations; (2) the primary drivers of PTDS and TTDS dynamics are predominantly local meteorological factors; (3) there is a strong correlation between SD and ENSO, and the impacts of PDO on local meteorological factors (WS and T) play a crucial role in driving the PTDS dynamics; and (4) NDVI is the main driver, primarily influencing T and ultimately affecting the dynamics of PTDS and TTDS. These findings suggest that there are significant ecological impacts through radiative or non-radiative feedback mechanisms under warming scenarios. Overall, this study provides new insights into the drivers and mechanisms behind the dynamics of dependence structures among meteorological elements. It contributes to a deeper understanding of the changing local hydrometeorological processes. |
| WOS关键词 | SOUTH CHINA ; PRECIPITATION ; TEMPERATURE ; WATER ; AFFORESTATION ; VARIABILITY ; RAINFALL ; IMPACT ; RIVER |
| 资助项目 | National Key Ramp;D Program of China[2022YFC3202303] ; Xinjian-g Uygur Autonomous Region Key Ramp;D Program[2022B03024-4] ; National Natural Science Foundation of China[52279026] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA28060100] |
| WOS研究方向 | Engineering ; Environmental Sciences & Ecology ; Mathematics ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:001021361100001 |
| 出版者 | SPRINGER |
| 资助机构 | National Key Ramp;D Program of China ; Xinjian-g Uygur Autonomous Region Key Ramp;D Program ; National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/195335]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Huang, Shengzhi |
| 作者单位 | 1.UFZ Helmholtz Ctr Environm Res, Dept Remote Sensing, Permoserstr 15, D-04318 Leipzig, Germany 2.Univ Leipzig, Remote Sensing Ctr Earth Syst Res, D-04103 Leipzig, Germany 3.Power China Guiyang Engn Corp Ltd, Guiyang 550081, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 5.China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China 6.Xian Univ Technol, State Key Lab Ecohydraul Northwest Arid Reg China, Xian 710048, Peoples R China |
| 推荐引用方式 GB/T 7714 | Dong, Haixia,Huang, Shengzhi,Wang, Hao,et al. Identifying non-stationarity in the dependence structures of meteorological factors within and across seasons and exploring possible causes[J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT,2023:19. |
| APA | Dong, Haixia.,Huang, Shengzhi.,Wang, Hao.,Huang, Qiang.,Leng, Guoyong.,...&Peng, Jian.(2023).Identifying non-stationarity in the dependence structures of meteorological factors within and across seasons and exploring possible causes.STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT,19. |
| MLA | Dong, Haixia,et al."Identifying non-stationarity in the dependence structures of meteorological factors within and across seasons and exploring possible causes".STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2023):19. |
入库方式： OAI收割
来源：地理科学与资源研究所
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