Institutional Repository of Key Laboratory of Ocean Circulation and Wave Studies, Institute of Oceanology, Chinese Academy of Sciences
| Reconstruction of vertical thermal structure from several subsurface temperatures in the China Seas and adjacent waters | |
Hao Jiajia1,2,3; Chen Yongli1; Feng Junqiao1,2; Wang Fan1 ; [email protected]
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| 2009-06-01 | |
| 发表期刊 | CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY
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| 卷号 | 27期号:2页码:218-228 |
| 文章类型 | Article |
| 摘要 | Empirical Orthogonal Function (EOF) analysis is used in this study to generate main eigenvector fields of historical temperature for the China Seas (here referring to Chinese marine territories) and adjacent waters from 1930 to 2002 (510 143 profiles). A good temperature profile is reconstructed based on several subsurface in situ temperature observations and the thermocline was estimated using the model. The results show that: 1) For the study area, the former four principal components can explain 95% of the overall variance, and the vertical distribution of temperature is most stable using the in situ temperature observations near the surface. 2) The model verifications based on the observed CTD data from the East China Sea (ECS), South China Sea (SCS) and the areas around Taiwan Island show that the reconstructed profiles have high correlation with the observed ones with the confidence level > 95%, especially to describe the characteristics of the thermocline well. The average errors between the reconstructed and observed profiles in these three areas are 0.69A degrees C, 0.52A degrees C and 1.18A degrees C respectively. It also shows the model RMS error is less than or close to the climatological error. The statistical model can be used to well estimate the temperature profile vertical structure. 3) Comparing the thermocline characteristics between the reconstructed and observed profiles, the results in the ECS show that the average absolute errors are 1.5m, 1.4 m and 0.17A degrees C/m, and the average relative errors are 24.7%, 8.9% and 22.6% for the upper, lower thermocline boundaries and the gradient, respectively. Although the relative errors are obvious, the absolute error is small. In the SCS, the average absolute errors are 4.1 m, 27.7 m and 0.007A degrees C/m, and the average relative errors are 16.1%, 16.8% and 9.5% for the upper, lower thermocline boundaries and the gradient, respectively. The average relative errors are all < 20%. Although the average absolute error of the lower thermocline boundary is considerable, but contrast to the spatial scale of average depth of the lower thermocline boundary (165 m), the average relative error is small (16.8%). Therefore the model can be used to well estimate the thermocline.; Empirical Orthogonal Function (EOF) analysis is used in this study to generate main eigenvector fields of historical temperature for the China Seas (here referring to Chinese marine territories) and adjacent waters from 1930 to 2002 (510 143 profiles). A good temperature profile is reconstructed based on several subsurface in situ temperature observations and the thermocline was estimated using the model. The results show that: 1) For the study area, the former four principal components can explain 95% of the overall variance, and the vertical distribution of temperature is most stable using the in situ temperature observations near the surface. 2) The model verifications based on the observed CTD data from the East China Sea (ECS), South China Sea (SCS) and the areas around Taiwan Island show that the reconstructed profiles have high correlation with the observed ones with the confidence level > 95%, especially to describe the characteristics of the thermocline well. The average errors between the reconstructed and observed profiles in these three areas are 0.69A degrees C, 0.52A degrees C and 1.18A degrees C respectively. It also shows the model RMS error is less than or close to the climatological error. The statistical model can be used to well estimate the temperature profile vertical structure. 3) Comparing the thermocline characteristics between the reconstructed and observed profiles, the results in the ECS show that the average absolute errors are 1.5m, 1.4 m and 0.17A degrees C/m, and the average relative errors are 24.7%, 8.9% and 22.6% for the upper, lower thermocline boundaries and the gradient, respectively. Although the relative errors are obvious, the absolute error is small. In the SCS, the average absolute errors are 4.1 m, 27.7 m and 0.007A degrees C/m, and the average relative errors are 16.1%, 16.8% and 9.5% for the upper, lower thermocline boundaries and the gradient, respectively. The average relative errors are all < 20%. Although the average absolute error of the lower thermocline boundary is considerable, but contrast to the spatial scale of average depth of the lower thermocline boundary (165 m), the average relative error is small (16.8%). Therefore the model can be used to well estimate the thermocline. |
| 关键词 | Thermocline Eof Reconstruction Of Vertical Thermal Structure China Seas |
| DOI | 10.1007/s00343-009-9201-4 |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000267970300005 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.qdio.ac.cn/handle/337002/119 |
| 专题 | 海洋环流与波动重点实验室 |
| 通讯作者 | [email protected] |
| 作者单位 | 1.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Wave Studies, Qingdao 266071, Peoples R China 2.Chinese Acad Sci, Grad Sch, Beijing 100039, Peoples R China 3.CAS, Yantai Inst Costal Zone Res Sustainable Dev, Yantai 264003, Peoples R China |
| 第一作者单位 | 中国科学院海洋研究所 |
| 推荐引用方式 GB/T 7714 | Hao Jiajia,Chen Yongli,Feng Junqiao,et al. Reconstruction of vertical thermal structure from several subsurface temperatures in the China Seas and adjacent waters[J]. CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY,2009,27(2):218-228. |
| APA | Hao Jiajia,Chen Yongli,Feng Junqiao,Wang Fan,[email protected].(2009).Reconstruction of vertical thermal structure from several subsurface temperatures in the China Seas and adjacent waters.CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY,27(2),218-228. |
| MLA | Hao Jiajia,et al."Reconstruction of vertical thermal structure from several subsurface temperatures in the China Seas and adjacent waters".CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY 27.2(2009):218-228. |
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