Articles | Volume 9, issue 6
https://doi.org/10.5194/os-9-1089-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/os-9-1089-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A practical scheme to introduce explicit tidal forcing into an OGCM
K. Sakamoto
Meteorological Research Institute, Nagamine, Tsukuba, Ibaraki 305-0052, Japan
H. Tsujino
Meteorological Research Institute, Nagamine, Tsukuba, Ibaraki 305-0052, Japan
H. Nakano
Meteorological Research Institute, Nagamine, Tsukuba, Ibaraki 305-0052, Japan
M. Hirabara
Meteorological Research Institute, Nagamine, Tsukuba, Ibaraki 305-0052, Japan
G. Yamanaka
Meteorological Research Institute, Nagamine, Tsukuba, Ibaraki 305-0052, Japan
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Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-519, https://doi.org/10.5194/essd-2024-519, 2024
Preprint under review for ESSD
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The Global Carbon Budget 2024 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Alban Planchat, Lester Kwiatkowski, Laurent Bopp, Olivier Torres, James R. Christian, Momme Butenschön, Tomas Lovato, Roland Séférian, Matthew A. Chamberlain, Olivier Aumont, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, Tatiana Ilyina, Hiroyuki Tsujino, Kristen M. Krumhardt, Jörg Schwinger, Jerry Tjiputra, John P. Dunne, and Charles Stock
Biogeosciences, 20, 1195–1257, https://doi.org/10.5194/bg-20-1195-2023, https://doi.org/10.5194/bg-20-1195-2023, 2023
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Ocean alkalinity is critical to the uptake of atmospheric carbon and acidification in surface waters. We review the representation of alkalinity and the associated calcium carbonate cycle in Earth system models. While many parameterizations remain present in the latest generation of models, there is a general improvement in the simulated alkalinity distribution. This improvement is related to an increase in the export of biotic calcium carbonate, which closer resembles observations.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Pradeebane Vaittinada Ayar, Laurent Bopp, Jim R. Christian, Tatiana Ilyina, John P. Krasting, Roland Séférian, Hiroyuki Tsujino, Michio Watanabe, Andrew Yool, and Jerry Tjiputra
Earth Syst. Dynam., 13, 1097–1118, https://doi.org/10.5194/esd-13-1097-2022, https://doi.org/10.5194/esd-13-1097-2022, 2022
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The El Niño–Southern Oscillation is the main driver for the natural variability of global atmospheric CO2. It modulates the CO2 fluxes in the tropical Pacific with anomalous CO2 influx during El Niño and outflux during La Niña. This relationship is projected to reverse by half of Earth system models studied here under the business-as-usual scenario. This study shows models that simulate a positive bias in surface carbonate concentrations simulate a shift in the ENSO–CO2 flux relationship.
Ann Keen, Ed Blockley, David A. Bailey, Jens Boldingh Debernard, Mitchell Bushuk, Steve Delhaye, David Docquier, Daniel Feltham, François Massonnet, Siobhan O'Farrell, Leandro Ponsoni, José M. Rodriguez, David Schroeder, Neil Swart, Takahiro Toyoda, Hiroyuki Tsujino, Martin Vancoppenolle, and Klaus Wyser
The Cryosphere, 15, 951–982, https://doi.org/10.5194/tc-15-951-2021, https://doi.org/10.5194/tc-15-951-2021, 2021
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We compare the mass budget of the Arctic sea ice in a number of the latest climate models. New output has been defined that allows us to compare the processes of sea ice growth and loss in a more detailed way than has previously been possible. We find that that the models are strikingly similar in terms of the major processes causing the annual growth and loss of Arctic sea ice and that the budget terms respond in a broadly consistent way as the climate warms during the 21st century.
Hiroyuki Tsujino, L. Shogo Urakawa, Stephen M. Griffies, Gokhan Danabasoglu, Alistair J. Adcroft, Arthur E. Amaral, Thomas Arsouze, Mats Bentsen, Raffaele Bernardello, Claus W. Böning, Alexandra Bozec, Eric P. Chassignet, Sergey Danilov, Raphael Dussin, Eleftheria Exarchou, Pier Giuseppe Fogli, Baylor Fox-Kemper, Chuncheng Guo, Mehmet Ilicak, Doroteaciro Iovino, Who M. Kim, Nikolay Koldunov, Vladimir Lapin, Yiwen Li, Pengfei Lin, Keith Lindsay, Hailong Liu, Matthew C. Long, Yoshiki Komuro, Simon J. Marsland, Simona Masina, Aleksi Nummelin, Jan Klaus Rieck, Yohan Ruprich-Robert, Markus Scheinert, Valentina Sicardi, Dmitry Sidorenko, Tatsuo Suzuki, Hiroaki Tatebe, Qiang Wang, Stephen G. Yeager, and Zipeng Yu
Geosci. Model Dev., 13, 3643–3708, https://doi.org/10.5194/gmd-13-3643-2020, https://doi.org/10.5194/gmd-13-3643-2020, 2020
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The OMIP-2 framework for global ocean–sea-ice model simulations is assessed by comparing multi-model means from 11 CMIP6-class global ocean–sea-ice models calculated separately for the OMIP-1 and OMIP-2 simulations. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet key improvements in transitioning from OMIP-1 to OMIP-2 are also identified. Thus, the present assessment justifies that future ocean–sea-ice model development and analysis studies use the OMIP-2 framework.
Lester Kwiatkowski, Olivier Torres, Laurent Bopp, Olivier Aumont, Matthew Chamberlain, James R. Christian, John P. Dunne, Marion Gehlen, Tatiana Ilyina, Jasmin G. John, Andrew Lenton, Hongmei Li, Nicole S. Lovenduski, James C. Orr, Julien Palmieri, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Charles A. Stock, Alessandro Tagliabue, Yohei Takano, Jerry Tjiputra, Katsuya Toyama, Hiroyuki Tsujino, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, and Tilo Ziehn
Biogeosciences, 17, 3439–3470, https://doi.org/10.5194/bg-17-3439-2020, https://doi.org/10.5194/bg-17-3439-2020, 2020
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We assess 21st century projections of marine biogeochemistry in the CMIP6 Earth system models. These models represent the most up-to-date understanding of climate change. The models generally project greater surface ocean warming, acidification, subsurface deoxygenation, and euphotic nitrate reductions but lesser primary production declines than the previous generation of models. This has major implications for the impact of anthropogenic climate change on marine ecosystems.
Stephen M. Griffies, Gokhan Danabasoglu, Paul J. Durack, Alistair J. Adcroft, V. Balaji, Claus W. Böning, Eric P. Chassignet, Enrique Curchitser, Julie Deshayes, Helge Drange, Baylor Fox-Kemper, Peter J. Gleckler, Jonathan M. Gregory, Helmuth Haak, Robert W. Hallberg, Patrick Heimbach, Helene T. Hewitt, David M. Holland, Tatiana Ilyina, Johann H. Jungclaus, Yoshiki Komuro, John P. Krasting, William G. Large, Simon J. Marsland, Simona Masina, Trevor J. McDougall, A. J. George Nurser, James C. Orr, Anna Pirani, Fangli Qiao, Ronald J. Stouffer, Karl E. Taylor, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Maria Valdivieso, Qiang Wang, Michael Winton, and Stephen G. Yeager
Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, https://doi.org/10.5194/gmd-9-3231-2016, 2016
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The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This document defines OMIP and details a protocol both for simulating global ocean/sea-ice models and for analysing their output.
C. Laufkötter, M. Vogt, N. Gruber, M. Aita-Noguchi, O. Aumont, L. Bopp, E. Buitenhuis, S. C. Doney, J. Dunne, T. Hashioka, J. Hauck, T. Hirata, J. John, C. Le Quéré, I. D. Lima, H. Nakano, R. Seferian, I. Totterdell, M. Vichi, and C. Völker
Biogeosciences, 12, 6955–6984, https://doi.org/10.5194/bg-12-6955-2015, https://doi.org/10.5194/bg-12-6955-2015, 2015
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We analyze changes in marine net primary production (NPP) and its drivers for the 21st century in 9 marine ecosystem models under the RCP8.5 scenario. NPP decreases in 5 models and increases in 1 model; 3 models show no significant trend. The main drivers include stronger nutrient limitation, but in many models warming-induced increases in phytoplankton growth outbalance the nutrient effect. Temperature-driven increases in grazing and other loss processes cause a net decrease in biomass and NPP.
M. Ishii, R. A. Feely, K. B. Rodgers, G.-H. Park, R. Wanninkhof, D. Sasano, H. Sugimoto, C. E. Cosca, S. Nakaoka, M. Telszewski, Y. Nojiri, S. E. Mikaloff Fletcher, Y. Niwa, P. K. Patra, V. Valsala, H. Nakano, I. Lima, S. C. Doney, E. T. Buitenhuis, O. Aumont, J. P. Dunne, A. Lenton, and T. Takahashi
Biogeosciences, 11, 709–734, https://doi.org/10.5194/bg-11-709-2014, https://doi.org/10.5194/bg-11-709-2014, 2014
Related subject area
Approach: Numerical Models | Depth range: All Depths | Geographical range: All Geographic Regions | Phenomena: Tides
Radiational tides: their double-counting in storm surge forecasts and contribution to the Highest Astronomical Tide
Joanne Williams, Maialen Irazoqui Apecechea, Andrew Saulter, and Kevin J. Horsburgh
Ocean Sci., 14, 1057–1068, https://doi.org/10.5194/os-14-1057-2018, https://doi.org/10.5194/os-14-1057-2018, 2018
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Tide predictions based on tide-gauge observations are not just astronomical tides; they also contain periodic sea level changes due to the weather. Forecasts of total water level during storm surges add the immediate effects of the weather to the astronomical tide prediction and thus risk double-counting these effects. We use a global model to see how much double-counting may affect these forecasts and also how much of the Highest Astronomical Tide may be due to recurrent weather patterns.
Cited articles
Arbic, B. K., Garner, S. T., Hallberg, R. W., and Simmons, H. L.: The accuracy of surface elevations in forward global barotropic and baroclinic tide models, Deep-Sea Res. II, 51, 3069–3101, https://doi.org/10.1016/j.dsr2.2004.09.014, 2004.
Arbic, B. K., Wallcraft, A. J., and Metzger, E. J.: Concurrent simulation of the eddying general circulation and tides in a global ocean model, Ocean\ Modell., 32, 175–187, https://doi.org/10.1016/j.ocemod.2010.01.007, 2010.
Bessiéres, L., Madec, G., and Lyard, F.: Global tidal residual mean circulation: Does it affect a climate OGCM?, Geophys. Res. Lett., 35, L03 609, https://doi.org/10.1029/2007GL032644, 2008.
Davies, A. M.: On determining current profiles in oscillatory flows, Appl. Math. Modelling, 9, 419–428, https://doi.org/10.1016/0307-904X(85)90107-6, 1985.
Egbert, G. D. and Ray, R. D.: Estimates of M2 tidal energy dissipation from TOPEX/Poseidon altimeter data, J. Geophys. Res., 106, 22 475–22 502, https://doi.org/10.1029/2000JC000699, 2001.
Egbert, G. D. and Ray, R. D.: Semi-diurnal and diurnal tidal dissipation from TOPEX/Poseidon altimetry, Geophys. Res. Lett., 30, 1907, https://doi.org/10.1029/2003GL017676, 2003.
Gent, P. R. and Mcwilliams, J. C.: Isopycnal Mixing in Ocean Circulation Models, J. Phys. Oceanogr., 20, 150–155, https://doi.org/10.1175/1520-0485(1990)020<0150:IMIOCM>2.0.CO;2, 1990.
Griffies, S. M. and Hallberg, R. W.: Biharmonic friction with a Smagorinsky-like viscosity for use in large-scale eddy-permitting ocean models, Mon. Wea. Rev., 128, 2935–2946, https://doi.org/10.1175/1520-0493(2000)128<2935:BFWASL>2.0.CO;2, 2000.
Griffies, S. M., Biastoch, A., Böning, C., Bryan, F., Danabasoglu, G., Chassignet, E. P., England, M. H., Gerdes, R., Haak, H., Hallberg, R. W., Hazeleger, W., Jungclaus, J., Large, W. G., Madec, G., Pirani, A., Samuels, B. L., Scheinert, M., Gupta, A. S., Severijns, C. A., Simmons, H. L., Treguier, A. M., Winton, M., Yeager, S., and Yin, J.: Coordinated Ocean-ice Reference Experiments (COREs), Ocean Modell., 26, 1–26, https://doi.org/10.1016/j.ocemod.2008.08.007, 2009.
Hendershott, M. C.: The effects of solid earth deformation on global ocean tides, Gyophys. J. R. Astr. Soc., 29, 389–402, https://doi.org/10.1111/j.1365-246X.1972.tb06167.x, 1972.
Hunke, E. C. and Dukowicz, J. K.: An elastic-viscous-plastic model for sea ice dynamics, J. Phys. Oceanogr., 27, 1849–1867, https://doi.org/10.1175/1520-0485(1997)027<1849:AEVPMF>2.0.CO;2, 1997.
Hunke, E. C. and Dukowicz, J. K.: The elastic-viscous-plastic sea ice dynamics model in general orthogonal curvilinear coordinates on a sphere: Incorporation of metric terms, Mon. Wea. Rev., 130, 1848–1865, https://doi.org/10.1175/1520-0493(2002)130<1848:TEVPSI>2.0.CO;2, 2002.
Jayne, S. R. and St. Laurent, L. C.: Parameterizing tidal dissipation over rough topography, Geophys. Res. Lett., 28, 811–814, https://doi.org/10.1029/2000GL012044, 2001.
Kantha, L. H. and Clayson, C. A.: Numerical Models of Oceans and Oceanic Processes, Academic Press, 2000.
Komori, N., Ohfuchi, W., Taguchi, B., Sasaki, H., and Klein, P.: Deep ocean inertia-gravity waves simulated in a high-resolution global coupled atmosphere-ocean GCM, Geophys. Res. Lett., 35, L04 610, https://doi.org/10.1029/2007GL032807, 2008.
Kurapov, A. L., Allen, J. S., and Egbert, G. D.: Combined effects of wind-driven upwelling and internal tide on the continental shelf, J. Phys.\ Oceanogr., 40, 737–756, https://doi.org/10.1175/2009JPO4183.1, 2010.
Large, W. G. and Yeager, S. G.: Diurnal to decadal global forcing for coean and sea-ice models: T}he data sets and flux climatologies, {NCAR Tech. Note: TN-460+STR, CGD Division of the Natinal Center for Atmospheric Research, 2004.
Lee, H. C., Rosati, A., and Spelman, M. J.: Barotropic tidal mixing effects in a coupled climate model: O}ceanic conditions in the {Northern Atlantic, Ocean Modell., 11, 464–477, https://doi.org/10.1016/j.ocemod.2005.03.003, 2006.
Matsumoto, K., Takanezawa, T., and Ooe, N.: Ocean tide models developed by assimilating TOPEX/POSEIDON altimeter data into hydrodynamical model: A global model and a regional model around Japan, J. Oceanogr., 56, 567–581, https://doi.org/10.1023/A:1011157212596, 2000.
Mellor, G. L. and Kantha, L.: An ice-ocean coupled model, J. Geophys. Res., 94, 10 937–10 954, https://doi.org/10.1029/JC094iC08p10937, 1989.
Moon, J. H., Hirose, N., Yoon, J. H., and Pang, I. C.: Offshore detachment process of the low-salinity water around Changjiang Bank in the East China Sea, J. Phys. Oceanogr., 40, 1035–1053, https://doi.org/10.1175/2010JPO4167.1, 2010.
Müller, M., Haak, H., Jüngclaus, J. H., Sundermann, J., and Thomas, M.: The effect of ocean tides on a climate model simulation, Ocean Modell., 35, 304–313, https://doi.org/10.1016/j.ocemod.2010.09.001, 2010.
Munk, W. and Wunsch, C.: Abyssal recipes II: Energetics of tidal and wind mixing, Deep-Sea Res. I, 45, 1977–2010, https://doi.org/10.1016/S0967-0637(98)00070-3, 1998.
Murray, R. J.: Explicit generation of orthogonal grids for ocean models, J. Comput. Phys., 126, 251–273, https://doi.org/10.1006/jcph.1996.0136, 1996.
Nagai, T. and Hibiya, T.: Numerical simulation of tidally induced eddies in the Bungo Channel: A possible role for sporadic Kuroshio-water intrusion (kyucho), J. Oceanogr., 68, 797–806, https://doi.org/10.1007/s10872-012-0141-9, 2012.
Nakamura, T. and Awaji, T.: Tidally induced diapycnal mixing in the Kuril Straits and its role in water transformation and transport: A three-dimensional nonhydrostatic model experiment, J. Geophys. Res., 109, C09S07, https://doi.org/10.1029/2003JC001850, 2004.
Nakano, H. and Suginohara, N.: Effects of Bottom Boundary Layer parameterization on reproducing deep and bottom waters in a world ocean model, J. Phys. Oceanogr., 32, 1209–1227, 2002.
Niwa, Y. and Hibiya, T.: Estimation of baroclinic tide energy available for deep ocean mixing based on three-dimensional global numerical simulations, J. Oceanogr., 67, 493–502, https://doi.org/10.1007/s10872-011-0052-1, 2011.
Osafune, S. and Yasuda, I.: Bidecadal variability in the intermediate waters of the northwestern subarctic P}acific and the {Okhotsk Sea in relation to 18.6-year period nodal tidal cycle, J. Geophys. Res., 111, C05 007, https://doi.org/10.1029/2005JC003277, 2006.
Osborne, J. J., Kurapov, A. L., Egbert, G. D., and Kosro, P. M.: Spatial and temporal variability of the M2 internal tide generation and propagation on the Oregon Shelf, J. Phys. Oceanogr., 41, 2037–2062, https://doi.org/10.1175/JPO-D-11-02.1, 2011.
Pereira, F. P., Beckmann, A., and Hellmer, H. H.: Tidal mixing in the southern Weddell Sea: Results from a three-dimensional model, J. Phys.\ Oceanogr., 32, 2151–2170, https://doi.org/10.1175/1520-0485(2002)032<2151:TMITSW>2.0.CO;2, 2002.
Polzin, K. L.: Mesoscale eddy-internal wave coupling. Part I: S}ymmetry, wave capture, and results from the {Mid-Ocean Dynamics Experiment, J. Phys.\ Oceanogr., 38, 2556–2574, https://doi.org/10.1175/2008JPO3666.1, 2008.
Postlethwaite, C. F., Maqueda, M. A. M., Fouest, V. L., Tattersall, G. R., Holt, J., and Willmott, A. J.: The effect of tides on dense water formation in Arctic shelf seas, Ocean Sci., 7, 203–217, https://doi.org/10.5194/os-7-203-2011, 2011.
Prather, M. J.: Numerical advection by conservation of second-order moments, J. Geophys. Res., 91, 6671–6681, https://doi.org/10.1029/JD091iD06p06671, 1986.
Robertson, R.: Internal tides and baroclinicity in the southern Weddell Sea 1. Model description, J. Geophys. Res., 106, 27 001–27 016, https://doi.org/10.1029/2000JC000475, 2001a.
Robertson, R.: Internal tides and baroclinicity in the southern Weddell Sea 2. Effects of the critical latitude and stratification, J. Geophys. Res., 106, 27 017–27 034, https://doi.org/10.1029/2000JC000476, 2001b.
Sakamoto, K. and Akitomo, K.: Instabilities of the tidally induced bottom boundary layer in the rotating frame and their mixing effect, Dyn. Atmos.\ Oceans, 41, 191–211, https://doi.org/10.1016/j.dynatmoce.2006.06.001, 2006.
Sakamoto, K. and Akitomo, K.: The tidally induced bottom boundary layer in the rotating frame: Similarity of turbulence, J. Fluid Mech., 615, 1–25, https://doi.org/10.1017/S0022112008003340, 2008.
Sakamoto, K. and Akitomo, K.: The tidally induced bottom boundary layer in the rotating frame: Development of the turbulent mixed layer under stratification, J. Fluid Mech., 619, 235–259, https://doi.org/10.1017/S0022112008004503, 2009.
Schiller, A.: Effects of explicit tidal forcing in an OGCM on the water-mass structure and circulation in the Indonesian throughflow region, Ocean\ Modell., 6, 31–49, https://doi.org/10.1016/S1463-5003(02)00057-4, 2004.
Schiller, A. and Fiedler, R.: Explicit tidal forcing in an ocean general circulation model, Geophys. Res. Lett., 34, L03 611, https://doi.org/10.1029/2006GL028363, 2007.
Schwiderski, E. W.: On charting global ocean tides, Rev. Geophys. Space\ Phys., 18, 243–268, https://doi.org/10.1029/RG018i001p00243, 1980.
Simmons, H. L., Hallberg, R. W., and Arbic, B. K.: Internal wave generation in a global baroclinic tide model, Deep-Sea Res. II, 51, 3043–3068, https://doi.org/10.1016/j.dsr2.2004.09.015, 2004.
Simpson, J. H. and Hunter, J. R.: Fronts in the Irish Sea, Nature, 250, 404–406, https://doi.org/10.1038/250404a0, 1974.
Simpson, J. H. and Sharples, J.: Introduction to the physical and biological oceanography of shelf seas, Cambridge University Press, 2012.
St. Laurent, L. and Garrett, G.: The role of internal tides in mixing the deep ocean, J. Phys. Oceanogr., 32, 2882–2899, https://doi.org/10.1175/1520-0485(2002)032<2882:TROITI>2.0.CO;2, 2002.
Taylor, G. I.: Tidal friction in the Irish Sea, Phil. Trans. R. Soc. Lond. A, 220, 1–33, https://doi.org/10.1098/rsta.1920.0001, 1920.
Thomas, M., Jürgen Sündermann, and Maier-Reimer, E.: Consideration of ocean tides in an OGCM and impacts on subseasonal to decadal polar motion excitation, Geophys. Res. Lett., 28, 2457–2460, https://doi.org/10.1029/2000GL012234, 2001.
Tsujino, H., Motoi, T., Ishikawa, I., Hirabara, M., Nakano, H., Yamanaka, G., Yasuda, T., and Ishizaki, H.: Reference manual for the Meteorological Research Institute Community Ocean Model (MRI.COM) version 3, Technical reports of the Meteorological Research Institute 59, Meteorological Research Institute, Japan, 2010.
Tsujino, H., Hirabara, M., Nakano, H., Yasuda, T., Motoi, T., and Yamanaka, G.: Simulating present climate of the global ocean-ice system using the Meteorological Research Institute Community Ocean Model (MRI.COM)}: simulation characteristics and variability in the {Pacific sector, J.\ Oceanogr., 67, 449–479, https://doi.org/10.1007/s10872-011-0050-3, 2011.
Umlauf, L. and Burchard, H.: A generic length-scale equation for geophysical turbulence models, J. Marine Res., 61, 235–265, https://doi.org/10.1357/002224003322005087, 2003.
Weatherly, G. L., Blumsack, S. L., and Bird, A. A.: On the effect of diurnal tidal currents in determining the thickness of the turbulent Ekman bottom boundary layer, J. Phys. Oceanogr., 10, 297–300, https://doi.org/10.1175/1520-0485(1980)010<0297:OTEODT>2.0.CO;2, 1980.
Xing, J. and Davies, A. M.: The influence of wind effects upon internal tides in shelf edge regions, J. Phys. Oceanogr., 27, 2100–2125, https://doi.org/10.1175/1520-0485(1997)027<2100:TIOWEU>2.0.CO;2, 1997.