| Spatio-temporal Variability in Sea Surface Temperatures for the Yellow Sea based on MODIS Dataset | |
Liu, Chunli1; Sun, Qiwei2,3; Xing, Qianguo4 ; Liang, Zhenlin1; Deng, Yue1; Zhu, Lixin1; Deng, Y (reprint author), Shandong Univ, Marine Coll, Weihai 264209, Peoples R China. [email protected]
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| 发表期刊 | OCEAN SCIENCE JOURNAL
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| ISSN | 1738-5261 |
| 2017-03-01 | |
| 卷号 | 52期号:1页码:1-10 |
| 关键词 | Yellow Sea Sea Surface Temperature Currents Empirical Orthogonal Function Analysis |
| DOI | 10.1007/s12601-017-0006-7 |
| 产权排序 | [Liu, Chunli; Liang, Zhenlin; Deng, Yue; Zhu, Lixin] Shandong Univ, Marine Coll, Weihai 264209, Peoples R China; [Sun, Qiwei] Chinese Acad Sci, South China Sea Inst Oceanol, State Key Lab Trop Oceanog, Guangzhou 510301, Guangdong, Peoples R China; [Sun, Qiwei] Univ Chinese Acad Sci, Beijing 100049, Peoples R China; [Xing, Qianguo] Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China |
| 作者部门 | 海岸带信息集成与综合管理实验室 |
| 英文摘要 | The spatio-temporal variabilities in sea surface temperature (SST) were analyzed using a time series of MODIS datasets for four separate regions in the Yellow Sea (YS) that were located along a north-south axis. The space variant temporal anomaly was further decomposed using an empirical orthogonal function (EOF) for estimating spatially distributed SST. The monthly SSTs showed similar temporal patterns in each region, which ranged from 2.4 degrees C to 28.4 degrees C in the study years 2011 to 2013, with seasonal cycles being stronger at the higher latitudes and weaker at the lower latitudes. Spatially, although there were no significant differences among the four regions (p<0.05) in any year, the geographical distribution of SST was characterized by an obvious gradient whereby SST decreased along the north-south axis. The monthly thermal difference among regions was largest in winter since the SST in the southeast was mainly affected by the Yellow Sea Warm Currents. The EOF1 mode accounted for 56% of the total spatial variance and exhibited a warming signal during the study period. The EOF2 mode accounted for 8% of the total variance and indicated the warm current features in the YS. The EOF3 mode accounted for 6% of the total variance and indicated the topographical features. The methodology used in this study demonstrated the spatio temporal variabilities in the YS. |
| 文章类型 | Article |
| 资助机构 | National Science Foundation of China(41206166) ; Science and Technology Development Plan Project of Weihai(2014DXGJ36) ; State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences(LTO1608) ; Natural Science Foundation of Shandong Province, China(ZR2010DQ019) |
| 收录类别 | SCI |
| 语种 | 英语 |
| 关键词[WOS] | COLD-WATER MASS ; ORTHOGONAL FUNCTION-ANALYSIS ; SANTA-BARBARA CHANNEL ; EAST CHINA SEA ; WARM CURRENT ; EVOLUTION ; PATTERNS |
| 研究领域[WOS] | Marine & Freshwater Biology ; Oceanography |
| WOS记录号 | WOS:000397134300001 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.yic.ac.cn/handle/133337/22036 |
| 专题 | 中国科学院海岸带环境过程与生态修复重点实验室_海岸带信息集成与战略规划研究中心 中国科学院海岸带环境过程与生态修复重点实验室 |
| 通讯作者 | Deng, Y (reprint author), Shandong Univ, Marine Coll, Weihai 264209, Peoples R China. [email protected] |
| 作者单位 | 1.Shandong Univ, Marine Coll, Weihai 264209, Peoples R China 2.Chinese Acad Sci, South China Sea Inst Oceanol, State Key Lab Trop Oceanog, Guangzhou 510301, Guangdong, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Chunli,Sun, Qiwei,Xing, Qianguo,et al. Spatio-temporal Variability in Sea Surface Temperatures for the Yellow Sea based on MODIS Dataset[J]. OCEAN SCIENCE JOURNAL,2017,52(1):1-10. |
| APA | Liu, Chunli.,Sun, Qiwei.,Xing, Qianguo.,Liang, Zhenlin.,Deng, Yue.,...&Deng, Y .(2017).Spatio-temporal Variability in Sea Surface Temperatures for the Yellow Sea based on MODIS Dataset.OCEAN SCIENCE JOURNAL,52(1),1-10. |
| MLA | Liu, Chunli,et al."Spatio-temporal Variability in Sea Surface Temperatures for the Yellow Sea based on MODIS Dataset".OCEAN SCIENCE JOURNAL 52.1(2017):1-10. |
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