4.7 Article

Intraseasonal-to-semiannual variability of sea-surface height in the astern, equatorial Indian Ocean and southern Bay of Bengal

期刊

JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
卷 122, 期 5, 页码 4051-4067

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1002/2016JC012662

关键词

Bay of Bengal; intraseasonal; semiannual; sea surface height; reduced-gravity model; LCS model

资金

  1. Natural Science Foundation of China [41522601, 41525019, 41521005]
  2. Strategic Priority Research Program of the Chinese Academy of Sciences [XDA11010103]
  3. State Oceanic Administration of China [GASI-IPOVAI-02]
  4. Open Project Program of State Key Laboratory of Tropical Oceanography [LTOZZ1501]
  5. Pear River S&T Nova Program of Guangzhou [201506010036]

向作者/读者索取更多资源

Intraseasonal-to-semiannual variability of sea-surface height (SSH) in the eastern, equatorial Indian Ocean (EEIO) and southern Bay of Bengal (BoB) is investigated using altimetric data, and solutions to 11/2 layer (first baroclinic mode) and linear, continuously stratified (LCS; multibaroclinic-mode) models. The amplitude and dominant periods of SSH variability differ regionally. Large-amplitude variability is found along the west coast of Sumatra, in a zonal band across the BoB centered along 5 degrees N, east of Sri Lanka, and in the northwestern BoB, respectively. Along the Sumatran west coast, SSH variability peaks at 30-60, 90, and 180 days. Along 5 degrees N and east of Sri Lanka, the 30-60 day variability is dominant. Sensitivity experiments using a nonlinear version of the 11/2 layer model forced by realistic winds reproduce the observed patterns of intraseasonal variability in the southern BoB. At 30-60 days, the solutions show that eddies (nonlinear Rossby waves) propagating from the east, rather than local wind forcing, account for most of the variance east of Sri Lanka; furthermore, they demonstrate that the variance is significantly enhanced by the nonlinear transfer of 90-120 day energy into the intraseasonal band of 30-60 days. The LCS solutions show that the first two baroclinic modes explain most of the SSH variance at 90-180 days. The second baroclinic mode dominates the SSH variance at 180 days, a consequence of basin resonance and strong wind forcing.

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