2018
DOI: 10.1002/2017gl076269
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An Argo‐Derived Background Diffusivity Parameterization for Improved Ocean Simulations in the Tropical Pacific

Abstract: Model biases are substantial in ocean and coupled ocean‐atmosphere simulations in the tropical Pacific Ocean, including a too cold tongue and too diffuse thermocline. These biases can be partly attributed to vertical mixing parameterizations in which the background diffusivity depiction has great uncertainties. Here based on the fine‐scale parameterization, the Argo data are used to derive the spatially varying background diffusivity, with a magnitude of O(10−6 m2 s−1) in the most area of tropical Pacific. Thi… Show more

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Cited by 31 publications
(9 citation statements)
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“…Recent research by Holmes et al (in preparation) has highlighted the global significance of air-sea fluxes and turbulent mixing in this region for modulating ocean heat uptake. However, the parameterization of this vertical mixing in climate models remains a difficult task, and improvements are required in order to reduce model biases (e.g., Sasaki et al 2013;Zhu and Zhang 2018).…”
Section: Enso Modellingmentioning
confidence: 99%
“…Recent research by Holmes et al (in preparation) has highlighted the global significance of air-sea fluxes and turbulent mixing in this region for modulating ocean heat uptake. However, the parameterization of this vertical mixing in climate models remains a difficult task, and improvements are required in order to reduce model biases (e.g., Sasaki et al 2013;Zhu and Zhang 2018).…”
Section: Enso Modellingmentioning
confidence: 99%
“…Since no shear data was available in our field observations, we adopted a fixed value R ω = 7. Actually, on the basis of the historical LADCP and CTD data, Kunze et al (2006) found that the average R ω in the Pacific equals to 7 ± 1 above 2000 m depth, which has been widely assumed in the previous similar studies in the Pacific Ocean (e.g., Li and Xu 2014;Zhu and Zhang 2018).…”
Section: Finescale Parameterizationmentioning
confidence: 74%
“…Because of the successive arrival of SEs, diapycnal mixing in the subthermocline has significant intreaseasonal variations. Diapycnal mixing has a strong impact on the transformation of interhemispheric water masses in the WBR and hence on the tropical overturning circulation (Fine et al, 1994;Furue and Endoh, 2005;Zhu and Zhang, 2018). The SEs play an important role on the variation of diapycnal mixing in the subthermocline layer.…”
Section: Summary and Discussionmentioning
confidence: 99%
“…The diapycnal mixing effects must be parameterized in the ocean climate models. Better understanding of the diapycnal mixing processes is necessary to improve model's parameterizations (Zhu and Zhang, 2018). Since diapycnal mixing remains grossly under-sampled in vast region of the global ocean, the spatial distribution and intensity of diapycnal mixing is an important issue in physical oceanography (Liang et al, 2018).…”
Section: Introductionmentioning
confidence: 99%
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