Seasonal Variability of the Pacific South Equatorial Current during the Argo Era
Lina Yang, Raghu Murtugudde, Shaojun Zheng, Peng Liang, Wei Tan, Lei Wang, Baoxin Feng, Tianyu Zhang
Ministry of Natural Resources State Key Laboratory of Remote Sensing Science Guangdong Ocean University Earth System Science Interdisciplinary Center
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
The tropical Pacific currents from January 2004 to December 2018 are computed based on the gridded Argo temperatures and salinities using the P-vector method on an f plane and the geostrophic approximation on a β plane. Three branches of the South Equatorial Current (SEC) are identified, i.e., SEC(N) (2°S–5°N), SEC(M) (7°–3°S), and SEC(S) (20°–8°S), with the maximum zonal velocity of −55 cm s−1 and total volume transport of −49.8 Sv (1 Sv ≡ 106 m3 s−1) occurring in the central-east Pacific. The seasonal variability of each branch shows a distinct and different westward propagation of zonal current anomalies, which are well mirrored by the SLA differences between 2°S and 5°N, between 3°S and 6°S, and between 8°S and 15°S, respectively. Most of the seasonal variations are successfully simulated by a simple analytical Rossby wave model, highlighting the significance of the first-mode baroclinic, linear Rossby waves, particularly those driven by the wind stress curl in the central-east Pacific. However, the linear theory fails to explain the SEC(M) variations in certain months in the central-east Pacific, where the first baroclinic mode contributes only around 50% of the explained variance to the equatorial surface currents. A nonlinear model involving higher baroclinic modes is suggested for a further diagnosis. Considering the crucial role played by the tropical Pacific in the natural climate variability via the El Niño–Southern Ocean dynamics and the ocean response to anthropogenic forcing via the ocean heat uptake in the eastern tropical Pacific, advancing the process understanding of the SEC from observations is critical.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
物理Oceanographic and Atmospheric Processes
Climate variability and models · Marine and coastal ecosystems
参考文献 50
此处列出前 3 条
引用本文 6
按被引量排序,此处列出前 3 条