Estimating tidally driven mixing in the deep ocean

By Louis St. Laurent, H. Simmons, S. Jayne. 2002

371 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Oceanography

View Paper: https://www.semanticscholar.org/paper/1a1bb9d890de43d4fd0c1a84e7949664fcd017ec

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Global and Planetary Change

1. Oliver B. Fringer
2. Dujuan Kang
3. S. Jayne
4. Robert Hallberg
5. Sonya Legg
6. S. Griffies
7. Alistair Adcroft
8. J. MacKinnon

In Oceanography

1. Robert Hallberg
2. Dujuan Kang
3. Oliver B. Fringer
4. S. Griffies
5. S. Jayne
6. Sonya Legg
7. Alistair Adcroft
8. I. Held

Citations in the corpus

• The Flexible Global Ocean‐Atmosphere‐Land System Model Grid‐Point Version 3 (FGOALS‐g3): Description and Evaluation (2020, methodology): “The Laurent et al. (2002) tidal mixing model (Yu et al., 2017) is introduced into LICOM3.”
• The GFDL Global Ocean and Sea Ice Model OM4.0: Model Description and Simulation Features (2019, background): “Mixing generated by breaking internal gravity waves generated by tidal forcing (i.e., internal tides), is parameterized using St Laurent et al. (2002) for the local dissipation at the internal tide generation sites.”
• Energetics of Barotropic and Baroclinic Tides in the Monterey Bay Area (2012, methodology): “The estimate of St. Laurent et al. is obtained from equation (52) as CStL = 37.02 MW for 1000 vertical modes.”
• Spatial and temporal variability of global ocean mixing inferred from Argo profiles (2012, positive): “Most previous in situ observations and model-derived global maps of the tidal energy dissipation rate [St. Laurent et al., 2002], have highlighted mixing near rough topography in the abyssal ocean, the correlation presented here in the upper ocean is particularly striking.”
• The Impact of Abyssal Mixing Parameterizations in an Ocean General Circulation Model (2009, methodology): “Saenko and Merryfield (2005) also utilized the St. Laurent et al. (2002) parameterization in a study similar to Simmons et al. (2004).”
• Model-predicted distribution of wind-induced internal wave energy in the world's oceans (2008, neutral): “…tide energy down to dissipation scales was examined [Hibiya et al., 1996, 1998, 2002; MacKinnon and Winters, 2005; Furuichi et al., 2005] to clarify the global distribution of tide-induced diapycnal diffusivity [St. Laurent et al., 2002; Hibiya and Nagasawa, 2004; Hibiya et al., 2006, 2007].”