Reconstructing Upper Ocean Vertical Velocity Field from Sea Surface Height in the Presence of Unbalanced Motion
Type | Article | ||||||||
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Date | 2020-01 | ||||||||
Language | English | ||||||||
Author(s) | Qiu Bo1, Chen Shuiming1, Klein Patrice2, 3, Torres Hector2, Wang Jinbo2, Fu Lee-Lueng2, Menemenlis Dimitris2 | ||||||||
Affiliation(s) | 1 : Department of Oceanography, University of Hawaii at Manoa, Honolulu, Hawaii, USA 2 : Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA 3 : Université de Brest, CNRS, IRD, Ifremer, LOPS, Plouzané, France |
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Source | Journal Of Physical Oceanography (0022-3670) (American Meteorological Society), 2020-01 , Vol. 50 , N. 1 , P. 55-79 | ||||||||
DOI | 10.1175/JPO-D-19-0172.1 | ||||||||
WOS© Times Cited | 37 | ||||||||
Keyword(s) | Eddies, Mesoscale processes, Ocean dynamics, Vertical motion, Altimetry | ||||||||
Abstract | Reconstructability of upper ocean vertical velocity (w) and vorticity (ζ) fields from high-resolution sea surface height (SSH) data is explored using the global 1/48° horizontal-resolution MITgcm output in the context of the forth-coming Surface Water and Ocean Topography (SWOT) mission. By decomposing w with an omega equation of the primitive-equation system and by taking into account the measurement design of the SWOT mission, this study seeks to reconstruct the subinertial, balanced w and ζ signals. By adopting the effective surface quasi-geostrophic (eSQG) framework and applying to the Kuroshio Extension region of the North Pacific, we find that the target and reconstructed fields have a spatial correlation of ~0.7 below the mixed layer for w and 0.7 ~ 0.9 throughout the 1000m upper ocean for ζ in the error-free scenario. By taking the SWOT sampling and measurement errors into account, the spatial correlation is found to decrease to 0.4 ~ 0.6 below the mixed layer for w and 0.6 ~ 0.7 for ζ, respectively. For both w and ζ reconstruction, the degradation due to the SWOT errors is more significant in the surface layer and for smaller-scale signals. The impact of errors lessens with the increasing depth and lengthening horizontal scales. |
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