Articles | Volume 16, issue 4
https://doi.org/10.5194/os-16-907-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-16-907-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Jul 2020
Research article |
| 30 Jul 2020
| 30 Jul 2020
Scale-dependent analysis of in situ observations in the mesoscale to submesoscale range around New Caledonia
Climate Change Research Centre, University of New South Wales, Sydney, NWS 2052, Australia
Frédéric Marin
LEGOS/IRD, Toulouse, France
Lionel Gourdeau
LEGOS/IRD, Toulouse, France
Sophie Cravatte
LEGOS/IRD, Toulouse, France
Rosemary Morrow
CNRS/LEGOS, Toulouse, France
Mei-Ling Dabat
CNRS/LEGOS, Toulouse, France
Related authors
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
Short summary
Short summary
The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Sophie Cravatte, Guillaume Serazin, Thierry Penduff, and Christophe Menkes
Ocean Sci., 17, 487–507, https://doi.org/10.5194/os-17-487-2021, https://doi.org/10.5194/os-17-487-2021, 2021
Short summary
Short summary
The various currents in the southwestern Pacific Ocean contribute to the redistribution of waters from the subtropical gyre equatorward and poleward. The drivers of their interannual variability are not completely understood but are usually thought to be related to well-known climate modes of variability. Here, we suggest that oceanic chaotic variability alone, which is by definition unpredictable, explains the majority of this interannual variability south of 20° S.
Laurent Bessières, Stéphanie Leroux, Jean-Michel Brankart, Jean-Marc Molines, Marie-Pierre Moine, Pierre-Antoine Bouttier, Thierry Penduff, Laurent Terray, Bernard Barnier, and Guillaume Sérazin
Geosci. Model Dev., 10, 1091–1106, https://doi.org/10.5194/gmd-10-1091-2017, https://doi.org/10.5194/gmd-10-1091-2017, 2017
Short summary
Short summary
A new, probabilistic version of an ocean modelling system has been implemented in order to simulate the chaotic and the atmospherically forced contributions to the ocean variability. For that purpose, a large ensemble of global hindcasts has been performed. Results illustrate the importance of the oceanic chaos on climate-related oceanic indices, and the relevance of such probabilistic ocean modelling approaches to anticipating the behaviour of the next generation of coupled climate models.
Gerald Dibarboure, Cécile Anadon, Frédéric Briol, Emeline Cadier, Robin Chevrier, Antoine Delepoulle, Yannice Faugère, Alice Laloue, Rosemary Morrow, Nicolas Picot, Pierre Prandi, Marie-Isabelle Pujol, Matthias Raynal, Anaelle Tréboutte, and Clément Ubelmann
Ocean Sci., 21, 283–323, https://doi.org/10.5194/os-21-283-2025, https://doi.org/10.5194/os-21-283-2025, 2025
Short summary
Short summary
The Surface Water and Ocean Topography (SWOT) mission delivers unprecedented swath-altimetry products. In this paper, we describe how we extended the Level-3 algorithms to handle SWOT’s unique swath-altimeter data. We also illustrate and discuss the benefits, relevance, and limitations of Level-3 swath-altimeter products for various research domains.
Arne Bendinger, Sophie Cravatte, Lionel Gourdeau, Clément Vic, and Florent Lyard
EGUsphere, https://doi.org/10.5194/egusphere-2025-95, https://doi.org/10.5194/egusphere-2025-95, 2025
Short summary
Short summary
Temporal variability of the semidiurnal internal tide around New Caledonia is investigated using regional modeling. An important contribution to temporal variability not linked to the astronomically-forced spring-neap cycle is due to the presence of mesoscale eddies, both at the generation sites and in propagation direction. The incoherent tide has a widespread signature in sea surface height (SSH) challenging the SSH observability of mesoscale to submesoscale dynamics.
Romain Le Gendre, David Varillon, Sylvie Fiat, Régis Hocdé, Antoine De Ramon N'Yeurt, Jérôme Aucan, Sophie Cravatte, Maxime Duphil, Alexandre Ganachaud, Baptiste Gaudron, Elodie Kestenare, Vetea Liao, Bernard Pelletier, Alexandre Peltier, Anne-Lou Schaefer, Thomas Trophime, Simon Van Wynsberge, Yves Dandonneau, Michel Allenbach, and Christophe Menkes
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-394, https://doi.org/10.5194/essd-2024-394, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Due to ocean warming, coral reef ecosystems are strongly impacted with dystrophic events and corals experiencing increasing frequencies of bleaching events. In-situ observation remains the best alternative for accurate characterization of trends and extremes in these shallow environments. This paper presents the coastal temperature dataset of the ReefTEMPS monitoring network which spreads over multiple Pacific Island Countries and Territories (PICTS) in the Western and Central South Pacific.
Arne Bendinger, Sophie Cravatte, Lionel Gourdeau, Luc Rainville, Clément Vic, Guillaume Sérazin, Fabien Durand, Frédéric Marin, and Jean-Luc Fuda
Ocean Sci., 20, 945–964, https://doi.org/10.5194/os-20-945-2024, https://doi.org/10.5194/os-20-945-2024, 2024
Short summary
Short summary
A unique dataset of glider observations reveals tidal beams south of New Caledonia – an internal-tide-generation hot spot in the southwestern tropical Pacific. Observations are in good agreement with numerical modeling output, highlighting the glider's capability to infer internal tides while assessing the model's realism of internal-tide dynamics. Discrepancies are in large part linked to eddy–internal-tide interactions. A methodology is proposed to deduce the internal-tide surface signature.
Elisa Carli, Rosemary Morrow, Oscar Vergara, Robin Chevrier, and Lionel Renault
Ocean Sci., 19, 1413–1435, https://doi.org/10.5194/os-19-1413-2023, https://doi.org/10.5194/os-19-1413-2023, 2023
Short summary
Short summary
Oceanic eddies are the structures carrying most of the energy in our oceans. They are key to climate regulation and nutrient transport. We prepare for the Surface Water and Ocean Topography mission, studying eddy dynamics in the region south of Africa, where the Indian and Atlantic oceans meet, using models and simulated satellite data. SWOT will provide insights into the structures smaller than what is currently observable, which appear to greatly contribute to eddy kinetic energy and strain.
Arne Bendinger, Sophie Cravatte, Lionel Gourdeau, Laurent Brodeau, Aurélie Albert, Michel Tchilibou, Florent Lyard, and Clément Vic
Ocean Sci., 19, 1315–1338, https://doi.org/10.5194/os-19-1315-2023, https://doi.org/10.5194/os-19-1315-2023, 2023
Short summary
Short summary
New Caledonia is a hot spot of internal-tide generation due to complex bathymetry. Regional modeling quantifies the coherent internal tide and shows that most energy is converted in shallow waters and on very steep slopes. The region is a challenge for observability of balanced dynamics due to strong internal-tide sea surface height (SSH) signatures at similar wavelengths. Correcting the SSH for the coherent internal tide may increase the observability of balanced motion to < 100 km.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
Short summary
Short summary
The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Oscar Vergara, Rosemary Morrow, Marie-Isabelle Pujol, Gérald Dibarboure, and Clément Ubelmann
Ocean Sci., 19, 363–379, https://doi.org/10.5194/os-19-363-2023, https://doi.org/10.5194/os-19-363-2023, 2023
Short summary
Short summary
Recent advances allow us to observe the ocean from space with increasingly higher detail, challenging our knowledge of the ocean's surface height signature. We use a statistical approach to determine the spatial scale at which the sea surface height signal is no longer dominated by geostrophic turbulence but in turn becomes dominated by wave-type motions. This information helps us to better use the data provided by ocean-observing satellites and to gain knowledge on climate-driving processes.
Maxime Ballarotta, Clément Ubelmann, Pierre Veillard, Pierre Prandi, Hélène Etienne, Sandrine Mulet, Yannice Faugère, Gérald Dibarboure, Rosemary Morrow, and Nicolas Picot
Earth Syst. Sci. Data, 15, 295–315, https://doi.org/10.5194/essd-15-295-2023, https://doi.org/10.5194/essd-15-295-2023, 2023
Short summary
Short summary
We present a new gridded sea surface height and current dataset produced by combining observations from nadir altimeters and drifting buoys. This product is based on a multiscale and multivariate mapping approach that offers the possibility to improve the physical content of gridded products by combining the data from various platforms and resolving a broader spectrum of ocean surface dynamic than in the current operational mapping system. A quality assessment of this new product is presented.
Michel Tchilibou, Ariane Koch-Larrouy, Simon Barbot, Florent Lyard, Yves Morel, Julien Jouanno, and Rosemary Morrow
Ocean Sci., 18, 1591–1618, https://doi.org/10.5194/os-18-1591-2022, https://doi.org/10.5194/os-18-1591-2022, 2022
Short summary
Short summary
This high-resolution model-based study investigates the variability in the generation, propagation, and sea height signature (SSH) of the internal tide off the Amazon shelf during two contrasted seasons. ITs propagate further north during the season characterized by weak currents and mesoscale eddies and a shallow and strong pycnocline. IT imprints on SSH dominate those of the geostrophic motion for horizontal scales below 200 km; moreover, the SSH is mainly incoherent below 70 km.
Cori Pegliasco, Antoine Delepoulle, Evan Mason, Rosemary Morrow, Yannice Faugère, and Gérald Dibarboure
Earth Syst. Sci. Data, 14, 1087–1107, https://doi.org/10.5194/essd-14-1087-2022, https://doi.org/10.5194/essd-14-1087-2022, 2022
Short summary
Short summary
The new global Mesoscale Eddy Trajectory Atlases (META3.1exp) provide eddy identification and trajectories from altimetry maps. These atlases comprise an improvement to and continuation of the historical META2.0 product. Changes in the detection parameters and tracking were tested by comparing the eddies from the different datasets. In particular, the eddy contours available in META3.1exp are an asset for multi-disciplinary studies.
Sophie Cravatte, Guillaume Serazin, Thierry Penduff, and Christophe Menkes
Ocean Sci., 17, 487–507, https://doi.org/10.5194/os-17-487-2021, https://doi.org/10.5194/os-17-487-2021, 2021
Short summary
Short summary
The various currents in the southwestern Pacific Ocean contribute to the redistribution of waters from the subtropical gyre equatorward and poleward. The drivers of their interannual variability are not completely understood but are usually thought to be related to well-known climate modes of variability. Here, we suggest that oceanic chaotic variability alone, which is by definition unpredictable, explains the majority of this interannual variability south of 20° S.
Michel Tchilibou, Lionel Gourdeau, Florent Lyard, Rosemary Morrow, Ariane Koch Larrouy, Damien Allain, and Bughsin Djath
Ocean Sci., 16, 615–635, https://doi.org/10.5194/os-16-615-2020, https://doi.org/10.5194/os-16-615-2020, 2020
Short summary
Short summary
This paper focuses on internal tides in the marginal Solomon Sea where LLWBCs transit. The objective is to characterize such internal tides and to give some insights into their impacts on water mass transformation in this area of interest for the global circulation. Results are discussed for two contrasted ENSO conditions with different mesoscale activity and stratification. Such study is motivated by the next altimetric SWOT mission that will be able to observe such phenomena.
Michel Tchilibou, Lionel Gourdeau, Rosemary Morrow, Guillaume Serazin, Bughsin Djath, and Florent Lyard
Ocean Sci., 14, 1283–1301, https://doi.org/10.5194/os-14-1283-2018, https://doi.org/10.5194/os-14-1283-2018, 2018
Short summary
Short summary
This paper is motivated by the next SWOT altimetric mission dedicated to the observation of mesoscale and submesoscale oceanic features. It focuses on tropical areas with a strong discrepancy in the spectral signature between altimetry and models. The paper reviews the spectral signature of tropical turbulence which presents a rich variety of phenomena depending on the latitudinal dependence of the Coriolis force. Internal tides observed by altimetry explain the discrepancy with the model.
Fabrice Ardhuin, Yevgueny Aksenov, Alvise Benetazzo, Laurent Bertino, Peter Brandt, Eric Caubet, Bertrand Chapron, Fabrice Collard, Sophie Cravatte, Jean-Marc Delouis, Frederic Dias, Gérald Dibarboure, Lucile Gaultier, Johnny Johannessen, Anton Korosov, Georgy Manucharyan, Dimitris Menemenlis, Melisa Menendez, Goulven Monnier, Alexis Mouche, Frédéric Nouguier, George Nurser, Pierre Rampal, Ad Reniers, Ernesto Rodriguez, Justin Stopa, Céline Tison, Clément Ubelmann, Erik van Sebille, and Jiping Xie
Ocean Sci., 14, 337–354, https://doi.org/10.5194/os-14-337-2018, https://doi.org/10.5194/os-14-337-2018, 2018
Short summary
Short summary
The Sea surface KInematics Multiscale (SKIM) monitoring mission is a proposal for a future satellite that is designed to measure ocean currents and waves. Using a Doppler radar, the accurate measurement of currents requires the removal of the mean velocity due to ocean wave motions. This paper describes the main processing steps needed to produce currents and wave data from the radar measurements. With this technique, SKIM can provide unprecedented coverage and resolution, over the global ocean.
Laurent Bessières, Stéphanie Leroux, Jean-Michel Brankart, Jean-Marc Molines, Marie-Pierre Moine, Pierre-Antoine Bouttier, Thierry Penduff, Laurent Terray, Bernard Barnier, and Guillaume Sérazin
Geosci. Model Dev., 10, 1091–1106, https://doi.org/10.5194/gmd-10-1091-2017, https://doi.org/10.5194/gmd-10-1091-2017, 2017
Short summary
Short summary
A new, probabilistic version of an ocean modelling system has been implemented in order to simulate the chaotic and the atmospherically forced contributions to the ocean variability. For that purpose, a large ensemble of global hindcasts has been performed. Results illustrate the importance of the oceanic chaos on climate-related oceanic indices, and the relevance of such probabilistic ocean modelling approaches to anticipating the behaviour of the next generation of coupled climate models.
Rosemary Morrow, Alice Carret, Florence Birol, Fernando Nino, Guillaume Valladeau, Francois Boy, Celine Bachelier, and Bruno Zakardjian
Ocean Sci., 13, 13–29, https://doi.org/10.5194/os-13-13-2017, https://doi.org/10.5194/os-13-13-2017, 2017
Short summary
Short summary
Spectral analyses of along-track altimetric data are used to estimate noise levels and observable ocean scales in the NW Mediterranean Sea. In winter, all altimetric missions can observe wavelengths down to 40–50 km (individual feature diameters of 20–25 km). In summer, SARAL can detect scales down to 35 km, whereas Jason-2 and CryoSat-2 with higher noise can only observe scales less than 50–55 km. Along-track altimeter data are also compared with collocated glider and coastal HF radar data.
S. T. Gille, M. M. Carranza, R. Cambra, and R. Morrow
Biogeosciences, 11, 6389–6400, https://doi.org/10.5194/bg-11-6389-2014, https://doi.org/10.5194/bg-11-6389-2014, 2014
Short summary
Short summary
The Kerguelen Plateau supports a strong spring chlorophyll bloom, in contrast with most of the Southern Ocean. Throughout the Southern Ocean, including in the Kerguelen area, wind can determine oceanic vertical velocities that may bring nutrients to the surface and contribute to the development of blooms. The Kerguelen Island itself generates a wind shadow that locally enhances upwelling velocities to the north of the main axis of the winds, and chlorophyll is high in this upwelling region.
Cited articles
Alory, G., Delcroix, T., Téchiné, P., Diverrès, D., Varillon, D., Cravatte, S., Gouriou, Y., Grelet, J., Jacquin, S., Kestenare, E., Maes, C., Morrow, R., Perrier, J., Reverdin, G., and Roubaud, F.: The French contribution to the voluntary observing ships network of sea surface salinity, Deep-Sea Res. Pt I, 105, 1–18, https://doi.org/10.1016/j.dsr.2015.08.005, 2015. a, b
Babiano, A., Basdevant, C., and Sadourny, R.: Structure Functions and Dispersion Laws in Two-Dimensional Turbulence, J. Atmos. Sci., 42, 941–949, https://doi.org/10.1175/1520-0469(1985)042<0941:SFADLI>2.0.CO;2, 1985. a, b, c, d
Balwada, D., Lacasce, J., and Speer, K. G.: Scale Dependent Distribution of Kinetic Energy from Surface Drifters in the Gulf of Mexico: Scale Dep. Dist. of KE from Surface Drifters in the GOM, Geophys. Res. Lett., 43, 10856–10863, https://doi.org/10.1002/2016GL069405, 2016. a, b, c
Batchelor, G. K.: Small-scale variation of convected quantities like temperature in turbulent fluid Part 1. General discussion and the case of small conductivity, J. Fluid Mech., 5, 113–133, https://doi.org/10.1017/S002211205900009X, 1959. a
Bennett, A. F.: Relative Dispersion: Local and Nonlocal Dynamics, J. Atmos. Sci., 41, 1881–1886, https://doi.org/10.1175/1520-0469(1984)041<1881:RDLAND>2.0.CO;2, 1984. a
Boccaletti, G., Ferrari, R., and Fox-Kemper, B.: Mixed Layer Instabilities and Restratification, J. Phys. Oceanogr., 37, 2228–2250, https://doi.org/10.1175/JPO3101.1, 2007. a, b
Boyd, J. P.: The Energy Spectrum of Fronts: Time Evolution of Shocks in Burgers Equation, J. Atmos. Sci., 49, 128–139, https://doi.org/10.1175/1520-0469(1992)049<0128:TESOFT>2.0.CO;2, 1992. a
Callies, J., Ferrari, R., Klymak, J. M., and Gula, J.: Seasonality in submesoscale turbulence, Nat. Commun., 6, 6862, https://doi.org/10.1038/ncomms7862, 2015. a
Cao, H., Jing, Z., Fox‐Kemper, B., Yan, T., and Qi, Y.: Scale Transition From Geostrophic Motions to Internal Waves in the Northern South China Sea, J. Geophys. Res.-Oceans, 124, 9364–9383, https://doi.org/10.1029/2019JC015575, 2019. a
Charney, J. G.: Geostrophic Turbulence, J. Atmos. Sci., 28, 1087–1095, https://doi.org/10.1175/1520-0469(1971)028<1087:GT>2.0.CO;2, 1971. a, b
Chereskin, T. K., Rocha, C. B., Gille, S. T., Menemenlis, D., and Passaro, M.: Characterizing the Transition From Balanced to Unbalanced Motions in the Southern California Current, J. Geophys. Res.-Oceans, 124, 2088–2109, https://doi.org/10.1029/2018JC014583, 2019. a, b, c, d
Cho, J. Y. N. and Lindborg, E.: Horizontal velocity structure functions in the upper troposphere and lower stratosphere: 1. Observations, J. Geophys. Res.-Atmos., 106, 10223–10232, https://doi.org/10.1029/2000JD900814, 2001. a, b
Cole, S. T. and Rudnick, D. L.: The spatial distribution and annual cycle of upper ocean thermohaline structure, J. Geophys. Res., 117, C02027, https://doi.org/10.1029/2011JC007033, 2012. a
Cole, S. T., Rudnick, D. L., and Colosi, J. A.: Seasonal evolution of upper-ocean horizontal structure and the remnant mixed layer, J. Geophys. Res., 115, C04012, https://doi.org/10.1029/2009JC005654, 2010. a
Corrsin, S.: On the Spectrum of Isotropic Temperature Fluctuations in an Isotropic Turbulence, J. Appl. Phys., 22, 469–473, https://doi.org/10.1063/1.1699986, 1951. a
de Lavergne, C., Falahat, S., Madec, G., Roquet, F., Nycander, J., and Vic, C.: Toward global maps of internal tide energy sinks, Ocean Model., 137, 52–75, https://doi.org/10.1016/j.ocemod.2019.03.010, 2019. a, b
Delcroix, T.: Observed surface oceanic and atmospheric variability in the tropical Pacific at seasonal and ENSO timescales: A tentative overview, J. Geophys. Res., 103, 18611–18633, https://doi.org/10.1029/98JC00814, 1998. a
d'Ovidio, F., Pascual, A., Wang, J., Doglioli, A. M., Jing, Z., Moreau, S.,
Grégori, G., Swart, S., Speich, S., Cyr, F., Legresy, B., Chao, Y., Fu, L.,
and Morrow, R.: Frontiers in Fine-Scale in situ Studies: Opportunities During the SWOT Fast Sampling Phase, Frontiers in Marine Science, 6, https://doi.org/10.3389/fmars.2019.00168, 2019. a
Fu, L.-L. and Ubelmann, C.: On the Transition from Profile Altimeter to Swath Altimeter for Observing Global Ocean Surface Topography, J. Atmos. Ocean. Tech., 31, 560–568, https://doi.org/10.1175/JTECH-D-13-00109.1, 2013. a
Garrett, C. and Munk, W.: Space-Time scales of internal waves, Geophysical Fluid Dynamics, 3, 225–264, https://doi.org/10.1080/03091927208236082, 1972. a
Hénin, C., Guillerm, J.-M., and Chabert, L.: Circulation superficielle autour de la Nouvelle-Calédonie, Océanographie Tropicale, 19, 113–126, 1984. a
Hodges, B. A. and Rudnick, D. L.: Horizontal variability in chlorophyll fluorescence and potential temperature, Deep-Sea Res. Pt. I, 53, 1460–1482, https://doi.org/10.1016/j.dsr.2006.06.006, 2006. a
Hoskins, B. J. and Bretherton, F. P.: Atmospheric Frontogenesis Models: Mathematical Formulation and Solution, J. Atmos. Sci., 29, 11–37, https://doi.org/10.1175/1520-0469(1972)029<0011:AFMMFA>2.0.CO;2, 1972. a
Klein, P., Treguier, A.-M., and Hua, B. L.: Three-dimensional stirring of thermohaline fronts, J. Mar. Res., 56, 589–612, https://doi.org/10.1357/002224098765213595, 1998. a
Kolmogorov, A. N.: Dissipation of Energy in Locally Isotropic Turbulence, Akademiia Nauk SSSR Doklady, 32, 16–18, 1941. a
Kolodziejczyk, N., Reverdin, G., Boutin, J., and Hernandez, O.: Observation of the surface horizontal thermohaline variability at mesoscale to submesoscale in the north-eastern subtropical Atlantic Ocean, J. Geophys. Res.-Oceans, 120, 2588–2600, https://doi.org/10.1002/2014JC010455, 2015. a, b
Kraichnan, R. H.: Inertial Ranges in Two Dimensional Turbulence, Phys. Fluids, 10, 1417–1423, https://doi.org/10.1063/1.1762301, 1967. a
Lahaye, N., Gula, J., and Roullet, G.: Sea Surface Signature of Internal Tides, Geophys. Res. Lett., 46, 3880–3890, https://doi.org/10.1029/2018GL081848, 2019. a, b
Lévy, M., Ferrari, R., Franks, S. P. J., Martin, A. P., and Rivière, P.: Bringing physics to life at the submesoscale, Geophys. Res. Lett., 39, L14602, https://doi.org/10.1029/2012GL052756, 2012. a
Li, Q. and Lindborg, E.: Weakly or Strongly Nonlinear Mesoscale Dynamics Close to the Tropopause?, J. Atmos. Sci., 75, 1215–1229, https://doi.org/10.1175/JAS-D-17-0063.1, 2018. a, b
Lindborg, E.: The energy cascade in a strongly stratified fluid, J. Fluid Mech., 550, 207–242, https://doi.org/10.1017/S0022112005008128, 2006. a
Lindborg, E.: A Helmholtz decomposition of structure functions and spectra calculated from aircraft data, J. Fluid Mech., 762, R4, https://doi.org/10.1017/jfm.2014.685, 2015. a, b, c, d
Lindborg, E. and Brethouwer, G.: Stratified turbulence forced in rotational and divergent modes, J. Fluid Mech., 586, 83–108, https://doi.org/10.1017/S0022112007007082, 2007. a
Lindborg, E. and Cho, J. Y. N.: Horizontal velocity structure functions in the upper troposphere and lower stratosphere: 2. Theoretical considerations, J. Geophys. Res.-Atmos., 106, 10233–10241, https://doi.org/10.1029/2000JD900815, 2001. a
MacKinnon, J. A., Zhao, Z., Whalen, C. B., Waterhouse, A. F., Trossman, D. S., Sun, O. M., St. Laurent, L. C., Simmons, H. L., Polzin, K., Pinkel, R., Pickering, A., Norton, N. J., Nash, J. D., Musgrave, R., Merchant, L. M., Melet, A. V., Mater, B., Legg, S., Large, W. G., Kunze, E., Klymak, J. M., Jochum, M., Jayne, S. R., Hallberg, R. W., Griffies, S. M., Diggs, S.,Danabasoglu, G., Chassignet, E. P., Buijsman, M. C., Bryan, F. O., Briegleb, B. P., Barna, A., Arbic, B. K., Ansong, J. K., and Alford, M. H.: Climate Process Team on Internal Wave–Driven Ocean Mixing, B. Am. Meteorol. Soc., 98, 2429–2454, https://doi.org/10.1175/BAMS-D-16-0030.1, 2017. a
Mahadevan, A.: The Impact of Submesoscale Physics on Primary Productivity of Plankton, Annu. Rev. Mar. Sci., 8, 161–184, https://doi.org/10.1146/annurev-marine-010814-015912, 2016. a
Marchesiello, P., Lefèvre, J., Vega, A., Couvelard, X., and Menkes, C.: Coastal upwelling, circulation and heat balance around New Caledonia's barrier reef, Mar. Pollut. Bull., 61, 432–448, https://doi.org/10.1016/j.marpolbul.2010.06.043, 2010. a
McCaffrey, K., Fox-Kemper, B., and Forget, G.: Estimates of Ocean Macroturbulence: Structure Function and Spectral Slope from Argo Profiling Floats, J. Phys. Oceanogr., 45, 1773–1793, https://doi.org/10.1175/JPO-D-14-0023.1, 2015. a, b
McWilliams, J. C.: Submesoscale currents in the ocean, P. Roy. Soc. A-Math. Phy., 472, 20160117, https://doi.org/10.1098/rspa.2016.0117, 2016. a, b
Obukhov, A. M.: Structure of the temperature field in turbulent flow, Izv. AN SSSR, Ser. Geograf. Geofiz., 13, 58–69, 1949. a
Qiu, B. and Chen, S.: Seasonal Modulations in the Eddy Field of the South Pacific Ocean, J. Phys. Oceanogr., 34, 1515–1527, https://doi.org/10.1175/1520-0485(2004)034<1515:SMITEF>2.0.CO;2, 2004. a, b, c
Qiu, B., Chen, S., and Kessler, W. S.: Source of the 70-Day Mesoscale Eddy Variability in the Coral Sea and the North Fiji Basin, J. Phys. Oceanogr., 39, 404–420, https://doi.org/10.1175/2008JPO3988.1, 2009. a
Rocha, C. B., Gille, S. T., Chereskin, T. K., and Menemenlis, D.: Seasonality of submesoscale dynamics in the Kuroshio Extension, Geophys. Res. Lett., 43, 11304–11311, https://doi.org/10.1002/2016GL071349, 2016. a
Roemmich, D. and Gilson, J.: The 2004–2008 mean and annual cycle of temperature, salinity, and steric height in the global ocean from the Argo Program, Prog. Oceanogr., 82, 81–100, https://doi.org/10.1016/j.pocean.2009.03.004, 2009. a
Salmon, R.: Lectures on Geophysical Fluid Dynamics, OUP USA, Oxford University Press, New York, 1998. a
Sérazin, G.: Scale-dependent analysis of in situ observations in the mesoscale to submesoscale range around New Caledonia, GitHub, available at: https://github.com/serazing/serazin2019_scale-dependent (last access: 20 July 2020). a
Shcherbina, A. Y., Sundermeyer, M. A., Kunze, E., D'Asaro, E., Badin, G., Birch, D., Brunner-Suzuki, A.-M. E. G., Callies, J., Kuebel Cervantes, B. T., Claret, M., Concannon, B., Early, J., Ferrari, R., Goodman, L., Harcourt, R. R., Klymak, J. M., Lee, C. M., Lelong, M.-P., Levine, M. D., Lien, R.-C., Mahadevan, A., McWilliams, J. C., Molemaker, M. J., Mukherjee, S., Nash, J. D., Özgökmen, T., Pierce, S. D., Ramachandran, S., Samelson, R. M., Sanford, T. B., Shearman, R. K., Skyllingstad, E. D., Smith, K. S., Tandon, A., Taylor, J. R., Terray, E. A., Thomas, L. N., and Ledwell, J. R.: The LatMix Summer Campaign: Submesoscale Stirring in the Upper Ocean, B. Am. Meteorol. Soc., 96, 1257–1279, https://doi.org/10.1175/BAMS-D-14-00015.1, 2014.
a
Srinivasan, K., McWilliams, J. C., Renault, L., Hristova, H. G., Molemaker, J., and Kessler, W. S.: Topographic and Mixed Layer Submesoscale Currents in the Near-Surface Southwestern Tropical Pacific, J. Phys. Oceanogr., 47, 1221–1242, https://doi.org/10.1175/JPO-D-16-0216.1, 2017. a
Srinivasan, K., McWilliams, J. C., Molemaker, M. J., and Barkan, R.: Submesoscale Vortical Wakes in the Lee of Topography, J. Phys. Oceanogr., 49, 1949–1971, https://doi.org/10.1175/JPO-D-18-0042.1, 2019. a
Su, Z., Wang, J., Klein, P., Thompson, A. F., and Menemenlis, D.: Ocean submesoscales as a key component of the global heat budget, Nat.
Commun., 9, 775, https://doi.org/10.1038/s41467-018-02983-w, 2018. a
Vic, C., Naveira Garabato, A. C., Green, J. A. M., Waterhouse, A. F., Zhao, Z., Melet, A., de Lavergne, C., Buijsman, M. C., and Stephenson, G. R.: Deep-ocean mixing driven by small-scale internal tides, Nat. Commun., 10, 2099, https://doi.org/10.1038/s41467-019-10149-5, 2019. a, b
Webb, E. K.: Ratio of spectrum and structure-function constants in the inertial subrange, Q. J. Roy. Meteor. Soc., 90, 344–346, https://doi.org/10.1002/qj.49709038520, 1964. a, b
Zaron, E. D.: Mapping the nonstationary internal tide with satellite altimetry, J. Geophys. Res.-Oceans, 122, 539–554, https://doi.org/10.1002/2016JC012487, 2017. a
Zhao, Z.: The Global Mode-1 S2 Internal Tide, J. Geophys. Res.-Oceans, 122, 8794–8812, https://doi.org/10.1002/2017JC013112, 2017. a
Zhao, Z.: The Global Mode-2 M2 Internal Tide, J. Geophys. Res.-Oceans, 123, 7725–7746, https://doi.org/10.1029/2018JC014475, 2018. a, b, c, d
