The diapycnal mixing in the upper Pacific estimated from GTSPP observations

DENG Zeng'an; WEI Guanghao; YU Ting; WEI Hongyu; KANG Linchong; HAN Luyao

doi:10.1007/s13131-016-0795-z

Article Contents

Article Navigation > Acta Oceanologica Sinica > 2016 > 35(1): 46-52

DENG Zeng'an, WEI Guanghao, YU Ting, WEI Hongyu, KANG Linchong, HAN Luyao. The diapycnal mixing in the upper Pacific estimated from GTSPP observations[J]. Acta Oceanologica Sinica, 2016, 35(1): 46-52. doi: 10.1007/s13131-016-0795-z

Citation:

DENG Zeng'an, WEI Guanghao, YU Ting, WEI Hongyu, KANG Linchong, HAN Luyao. The diapycnal mixing in the upper Pacific estimated from GTSPP observations[J]. Acta Oceanologica Sinica, 2016, 35(1): 46-52. doi: 10.1007/s13131-016-0795-z

Citation:

PDF( 4413 KB)

The diapycnal mixing in the upper Pacific estimated from GTSPP observations

doi: 10.1007/s13131-016-0795-z

1.
School of Marine Science and Technology, Tianjin University, Tianjin 300172, China;National Marine Data and Information Service, Tianjin 300171, China
2.
National Marine Data and Information Service, Tianjin 300171, China

Received Date: 2014-10-22
Rev Recd Date: 2015-03-09

Abstract

Abstract

Diapycnal mixing (DM) in the upper 600 m of the Pacific Ocean was estimated based on the huge amount of the observations from Global Temperature-Salinity Profile Programme (GTSPP), using the strain version of the finescale parameterization. It is found that DM in each season exhibits similar distribution pattern, but differs in details. The intensification of DM is related to bottom roughness, surface near-inertial energy, and proximity to the equator. The intensified DM caused by rough topography shows in the profiles near the Mendocino fracture zone in the northeast Pacific, and the heightened DM caused by wind-generated near-inertial energy appears in the westerly region of the Southern Ocean. As compared to previous estimates, the DM estimate in this work has better spatial coverage and finer resolution, and more importantly it contains the seasonal variability. Furthermore, the resulting DM dataset is gridded, rendering it suitable for modeling applications.
- diapycnal mixing,
- GTSPP,
- fine-scale parameterization,
- Pacific

FullText(HTML)

References(17)

References

Alford M H, Cronin M F, Klymak J M. 2012. Annual cycle and depth penetration of wind-generated near-inertial internal waves at Ocean Station Papa in the northeast Pacific. J Phys Oceanogr, 42(6): 889-909

Chaigneau A, Pizarro O, Rojas W. 2008. Global climatology of nearinertial current characteristics from Lagrangian observations. Geophysical Research Letters, 35(13), doi: 10.1029/2008GL034060

Deng Zen'gan, Yu Ting. 2014a. Application of Argo-derived background diapycnal mixing in HYCOM. Journal of Marine Systems, 137: 1-12

Deng Zeng'an, Yu Ting, Shi Suixiang, et al. 2014b. The global distribution of diapycnal mixing and mixing coefficient tensor in the upper 2000m ocean from Argo observations. Marine Geodesy, 37(3): 337-353

Gregg M C, Kunze E. 1991. Shear and strain in Santa Monica basin. J Geophys Res, 96(C9): 16709-16719

Gregg M C, Sanford T B, Winkel D P. 2003. Reduced mixing from the breaking of internal waves in equatorial waters. Nature, 422(6931): 513-515

Harrison M J, Hallberg R W. 2008. Pacific subtropical cell response to reduced equatorial dissipation. J Phys Oceanogr, 38(9): 1894-1912

Jochum M. 2009. Impact of latitudinal variations in vertical diffusivity on climate simulations. J Geophys Res, 114(C1), doi: 10.1029/2008JC005030

Kunze E, Firing E, Hummon J M, et al. 2006. Global abyssal mixing inferred from lowered ADCP shear and CTD strain profiles. J Phys Oceanogr, 36(8): 1553-1576

Ledwell J R, Watson A J, Law C S. 1998. Mixing of a tracer in the pycnocline. J Geophys Res, 103(C10): 21499-21529

Polzin K L, Firing E. 1997. Estimates of diapycnal mixing using LADCP and CTD data from I8S. International WOCE Newsletter, No. 29, WOCE International Project Office, Southampton, United Kingdom, 39-42

Polzin K L, Garabato A C N, Huussen T N, et al. 2014. Finescale parameterizations of turbulent dissipation. J Geophys Res, 119(2): 1383-1419

Sun C, Thresher A, Keeley R, et al. 2010. The data management system for the Global Temperature and Salinity Profile Programme. In: Hall J, Harrison D E, Stammer D, eds. Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (Vol. 2). Venice, Italy: ESA Publication WPP-306

Tian Jiwei, Yang Qingxuan, Zhao Wei. 2009. Enhanced diapycnal mixing in the South China Sea. J Phys Oceanogr, 39(12): 3191-3203

Waterman S, Garabato A C N, Polzin K L. 2013. Internal waves and turbulence in the Antarctic Circumpolar Current. J Phys Oceanogr, 43(2): 259-282

Whalen C B, Talley L D, MacKinnon J A. 2012. Spatial and temporal variability of global ocean mixing inferred from Argo profiles. Geophysical Research Letters, 39(18), doi: 10.1029/2012GL053196

Wu Lixin, Zhao Jing, Steve R, et al. 2011. Seasonal and spatial variations of Southern Ocean diapycnal mixing from Argo profiling floats. Nature Geoscience, 4(6): 363-366

Relative Articles

Supplements(0)

Cited By

Proportional views