Articles | Volume 13, issue 9
https://doi.org/10.5194/gmd-13-4595-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-13-4595-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| Highlight paper
| 
29 Sep 2020
Model evaluation paper | Highlight paper |
| 29 Sep 2020
| 29 Sep 2020
Impact of horizontal resolution on global ocean–sea ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)
Center for Ocean–Atmospheric Prediction Studies, Florida State
University, Tallahassee, FL, USA
Stephen G. Yeager
National Center for Atmospheric Research, Boulder, CO, USA
Baylor Fox-Kemper
Brown University, Providence, RI, USA
Alexandra Bozec
Center for Ocean–Atmospheric Prediction Studies, Florida State
University, Tallahassee, FL, USA
Frederic Castruccio
National Center for Atmospheric Research, Boulder, CO, USA
Gokhan Danabasoglu
National Center for Atmospheric Research, Boulder, CO, USA
Christopher Horvat
Brown University, Providence, RI, USA
Who M. Kim
National Center for Atmospheric Research, Boulder, CO, USA
Nikolay Koldunov
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und
Meeresforschung (AWI), Bremerhaven, Germany
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
Pengfei Lin
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
Hailong Liu
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
Dmitry V. Sein
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und
Meeresforschung (AWI), Bremerhaven, Germany
Shirshov Institute of Oceanology, Russian Academy of Science, Moscow, Russia
Dmitry Sidorenko
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und
Meeresforschung (AWI), Bremerhaven, Germany
Qiang Wang
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und
Meeresforschung (AWI), Bremerhaven, Germany
Xiaobiao Xu
Center for Ocean–Atmospheric Prediction Studies, Florida State
University, Tallahassee, FL, USA
Related authors
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
Short summary
Short summary
Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
State Planet, 1-osr7, 2, https://doi.org/10.5194/sp-1-osr7-2-2023, https://doi.org/10.5194/sp-1-osr7-2-2023, 2023
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
Short summary
Short summary
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.
Taylor A. Shropshire, Steven L. Morey, Eric P. Chassignet, Alexandra Bozec, Victoria J. Coles, Michael R. Landry, Rasmus Swalethorp, Glenn Zapfe, and Michael R. Stukel
Biogeosciences, 17, 3385–3407, https://doi.org/10.5194/bg-17-3385-2020, https://doi.org/10.5194/bg-17-3385-2020, 2020
Short summary
Short summary
Zooplankton are the smallest animals in the ocean and important food for fish. Despite their importance, zooplankton have been relatively undersampled. To better understand the zooplankton community in the Gulf of Mexico (GoM), we developed a model to simulate their dynamics. We found that heterotrophic protists are important for supporting mesozooplankton, which are the primary prey of larval fish. The model developed in this study has the potential to improve fisheries management in the GoM.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Alexei Koldunov, Tobias Kölling, Josh Kousal, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Domokos Sármány, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
EGUsphere, https://doi.org/10.5194/egusphere-2024-913, https://doi.org/10.5194/egusphere-2024-913, 2024
Short summary
Short summary
Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale"), and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
Short summary
Short summary
Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Momme C. Hell and Christopher Horvat
The Cryosphere, 18, 341–361, https://doi.org/10.5194/tc-18-341-2024, https://doi.org/10.5194/tc-18-341-2024, 2024
Short summary
Short summary
Sea ice is heavily impacted by waves on its margins, and we currently do not have routine observations of waves in sea ice. Here we propose two methods to separate the surface waves from the sea-ice height observations along each ICESat-2 track using machine learning. Both methods together allow us to follow changes in the wave height through the sea ice.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
Short summary
Short summary
Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dimitry Sidorenko
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-208, https://doi.org/10.5194/gmd-2023-208, 2024
Preprint under review for GMD
Short summary
Short summary
In this paper we propose a new alternative to one of the functionalities of sea-ice model FESOM2. The alternative we propose allows for the model to capture and simulate more accurately fast changes in quantities like sea-surface-elevation. We also demonstrate that the new alternative is faster and is more adept in taking advantages of highly parallelised computing infrastructure. We show that this new alternative can in future became a great addition to the sea-ice model FESOM2.
Shunya Koseki, Rúben Vázquez, William Cabos, Claudia Gutiérrez, Dmitry V. Sein, and Marie-Lou Bachèlery
EGUsphere, https://doi.org/10.5194/egusphere-2023-2494, https://doi.org/10.5194/egusphere-2023-2494, 2023
Short summary
Short summary
Using a high-resolution regionally-coupled model, we have suggested that Dakar Niño variability will be reinforced under RCP8.5 scenario. This may be induced by the intensified meridional surface wind variability along the west African coast. In addition, the stronger wind variability can be attributed to the amplified surface temperature anomalies between ocean and land.
Roberto Bilbao, Pablo Ortega, Didier Swingedouw, Leon Hermanson, Panos Athanasiadis, Rosie Eade, Marion Devilliers, Francisco Doblas-Reyes, Nick Dunstone, An-Chi Ho, William Merryfield, Juliette Mignot, Dario Nicolì, Margarida Samsó, Reinel Sospedra-Alfonso, Xian Wu, and Stephen Yeager
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2023-36, https://doi.org/10.5194/esd-2023-36, 2023
Revised manuscript accepted for ESD
Short summary
Short summary
In recent decades three major volcanic eruptions have occurred: Mount Agung in 1963, El Chichón in 1982 and Mount Pinatubo in 1991. In this article we explore the climatic impacts of these volcanic eruptions with a purposefully designed set of simulations from six CMIP6 decadal prediction systems. We analyse the radiative and dynamical responses and show that including the volcanic forcing in these predictions is important to reproduce the observed surface temperature variations.
Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
State Planet, 1-osr7, 2, https://doi.org/10.5194/sp-1-osr7-2-2023, https://doi.org/10.5194/sp-1-osr7-2-2023, 2023
Xiaoxu Shi, Alexandre Cauquoin, Gerrit Lohmann, Lukas Jonkers, Qiang Wang, Hu Yang, Yuchen Sun, and Martin Werner
Geosci. Model Dev., 16, 5153–5178, https://doi.org/10.5194/gmd-16-5153-2023, https://doi.org/10.5194/gmd-16-5153-2023, 2023
Short summary
Short summary
We developed a new climate model with isotopic capabilities and simulated the pre-industrial and mid-Holocene periods. Despite certain regional model biases, the modeled isotope composition is in good agreement with observations and reconstructions. Based on our analyses, the observed isotope–temperature relationship in polar regions may have a summertime bias. Using daily model outputs, we developed a novel isotope-based approach to determine the onset date of the West African summer monsoon.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Francis Auclair, Peter P. Sullivan, and Paul S. Hall
EGUsphere, https://doi.org/10.5194/egusphere-2023-1657, https://doi.org/10.5194/egusphere-2023-1657, 2023
Short summary
Short summary
Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are similarly accurate, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
Short summary
Short summary
This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Yanan Wang, Byongjun Hwang, Adam William Bateson, Yevgeny Aksenov, and Christopher Horvat
The Cryosphere, 17, 3575–3591, https://doi.org/10.5194/tc-17-3575-2023, https://doi.org/10.5194/tc-17-3575-2023, 2023
Short summary
Short summary
Sea ice is composed of small, discrete pieces of ice called floes, whose size distribution plays a critical role in the interactions between the sea ice, ocean and atmosphere. This study provides an assessment of sea ice models using new high-resolution floe size distribution observations, revealing considerable differences between them. These findings point not only to the limitations in models but also to the need for more high-resolution observations to validate and calibrate models.
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.
Iván M. Parras-Berrocal, Rubén Vázquez, William Cabos, Dimitry V. Sein, Oscar Álvarez, Miguel Bruno, and Alfredo Izquierdo
Ocean Sci., 19, 941–952, https://doi.org/10.5194/os-19-941-2023, https://doi.org/10.5194/os-19-941-2023, 2023
Short summary
Short summary
Global warming may strongly affect dense water formation in the eastern Mediterranean, potentially impacting basin circulation and water properties. We find that at the end of the century dense water formation is reduced by 75 % for the Adriatic, 84 % for the Aegean, and 83 % for the Levantine Sea. This reduction is caused by changes in the temperature and salinity of surface and intermediate waters, which strengthen the vertical stratification, hampering deep convection.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
Short summary
Short summary
Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Laura C. Jackson, Eduardo Alastrué de Asenjo, Katinka Bellomo, Gokhan Danabasoglu, Helmuth Haak, Aixue Hu, Johann Jungclaus, Warren Lee, Virna L. Meccia, Oleg Saenko, Andrew Shao, and Didier Swingedouw
Geosci. Model Dev., 16, 1975–1995, https://doi.org/10.5194/gmd-16-1975-2023, https://doi.org/10.5194/gmd-16-1975-2023, 2023
Short summary
Short summary
The Atlantic meridional overturning circulation (AMOC) has an important impact on the climate. There are theories that freshening of the ocean might cause the AMOC to cross a tipping point (TP) beyond which recovery is difficult; however, it is unclear whether TPs exist in global climate models. Here, we outline a set of experiments designed to explore AMOC tipping points and sensitivity to additional freshwater input as part of the North Atlantic Hosing Model Intercomparison Project (NAHosMIP).
Pengyang Song, Dmitry Sidorenko, Patrick Scholz, Maik Thomas, and Gerrit Lohmann
Geosci. Model Dev., 16, 383–405, https://doi.org/10.5194/gmd-16-383-2023, https://doi.org/10.5194/gmd-16-383-2023, 2023
Short summary
Short summary
Tides have essential effects on the ocean and climate. Most previous research applies parameterised tidal mixing to discuss their effects in models. By comparing the effect of a tidal mixing parameterisation and tidal forcing on the ocean state, we assess the advantages and disadvantages of the two methods. Our results show that tidal mixing in the North Pacific Ocean strongly affects the global thermohaline circulation. We also list some effects that are not considered in the parameterisation.
Sergei Kirillov, Igor Dmitrenko, David G. Babb, Jens K. Ehn, Nikolay Koldunov, Søren Rysgaard, David Jensen, and David G. Barber
Ocean Sci., 18, 1535–1557, https://doi.org/10.5194/os-18-1535-2022, https://doi.org/10.5194/os-18-1535-2022, 2022
Short summary
Short summary
The sea ice bridge usually forms during winter in Nares Strait and prevents ice drifting south. However, this bridge has recently become unstable, and in this study we investigate the role of oceanic heat flux in this decline. Using satellite data, we identify areas where sea ice is relatively thin and further attribute those areas to the heat fluxes from the warm subsurface water masses. We also discuss the potential role of such an impact on ice bridge instability and earlier ice break up.
Gustavo M. Marques, Nora Loose, Elizabeth Yankovsky, Jacob M. Steinberg, Chiung-Yin Chang, Neeraja Bhamidipati, Alistair Adcroft, Baylor Fox-Kemper, Stephen M. Griffies, Robert W. Hallberg, Malte F. Jansen, Hemant Khatri, and Laure Zanna
Geosci. Model Dev., 15, 6567–6579, https://doi.org/10.5194/gmd-15-6567-2022, https://doi.org/10.5194/gmd-15-6567-2022, 2022
Short summary
Short summary
We present an idealized ocean model configuration and a set of simulations performed using varying horizontal grid spacing. While the model domain is idealized, it resembles important geometric features of the Atlantic and Southern oceans. The simulations described here serve as a framework to effectively study mesoscale eddy dynamics, to investigate the effect of mesoscale eddies on the large-scale dynamics, and to test and evaluate eddy parameterizations.
Stephen G. Yeager, Nan Rosenbloom, Anne A. Glanville, Xian Wu, Isla Simpson, Hui Li, Maria J. Molina, Kristen Krumhardt, Samuel Mogen, Keith Lindsay, Danica Lombardozzi, Will Wieder, Who M. Kim, Jadwiga H. Richter, Matthew Long, Gokhan Danabasoglu, David Bailey, Marika Holland, Nicole Lovenduski, Warren G. Strand, and Teagan King
Geosci. Model Dev., 15, 6451–6493, https://doi.org/10.5194/gmd-15-6451-2022, https://doi.org/10.5194/gmd-15-6451-2022, 2022
Short summary
Short summary
The Earth system changes over a range of time and space scales, and some of these changes are predictable in advance. Short-term weather forecasts are most familiar, but recent work has shown that it is possible to generate useful predictions several seasons or even a decade in advance. This study focuses on predictions over intermediate timescales (up to 24 months in advance) and shows that there is promising potential to forecast a variety of changes in the natural environment.
Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, https://doi.org/10.5194/gmd-15-6399-2022, 2022
Short summary
Short summary
We developed a new atmosphere–ocean coupled climate model, AWI-CM3. Our model is significantly more computationally efficient than its predecessors AWI-CM1 and AWI-CM2. We show that the model, although cheaper to run, provides results of similar quality when modeling the historic period from 1850 to 2014. We identify the remaining weaknesses to outline future work. Finally we preview an improved simulation where the reduction in computational cost has to be invested in higher model resolution.
Takaya Uchida, Julien Le Sommer, Charles Stern, Ryan P. Abernathey, Chris Holdgraf, Aurélie Albert, Laurent Brodeau, Eric P. Chassignet, Xiaobiao Xu, Jonathan Gula, Guillaume Roullet, Nikolay Koldunov, Sergey Danilov, Qiang Wang, Dimitris Menemenlis, Clément Bricaud, Brian K. Arbic, Jay F. Shriver, Fangli Qiao, Bin Xiao, Arne Biastoch, René Schubert, Baylor Fox-Kemper, William K. Dewar, and Alan Wallcraft
Geosci. Model Dev., 15, 5829–5856, https://doi.org/10.5194/gmd-15-5829-2022, https://doi.org/10.5194/gmd-15-5829-2022, 2022
Short summary
Short summary
Ocean and climate scientists have used numerical simulations as a tool to examine the ocean and climate system since the 1970s. Since then, owing to the continuous increase in computational power and advances in numerical methods, we have been able to simulate increasing complex phenomena. However, the fidelity of the simulations in representing the phenomena remains a core issue in the ocean science community. Here we propose a cloud-based framework to inter-compare and assess such simulations.
Jill Brouwer, Alexander D. Fraser, Damian J. Murphy, Pat Wongpan, Alberto Alberello, Alison Kohout, Christopher Horvat, Simon Wotherspoon, Robert A. Massom, Jessica Cartwright, and Guy D. Williams
The Cryosphere, 16, 2325–2353, https://doi.org/10.5194/tc-16-2325-2022, https://doi.org/10.5194/tc-16-2325-2022, 2022
Short summary
Short summary
The marginal ice zone is the region where ocean waves interact with sea ice. Although this important region influences many sea ice, ocean and biological processes, it has been difficult to accurately measure on a large scale from satellite instruments. We present new techniques for measuring wave attenuation using the NASA ICESat-2 laser altimeter. By measuring how waves attenuate within the sea ice, we show that the marginal ice zone may be far wider than previously realised.
Xiaoxu Shi, Martin Werner, Carolin Krug, Chris M. Brierley, Anni Zhao, Endurance Igbinosa, Pascale Braconnot, Esther Brady, Jian Cao, Roberta D'Agostino, Johann Jungclaus, Xingxing Liu, Bette Otto-Bliesner, Dmitry Sidorenko, Robert Tomas, Evgeny M. Volodin, Hu Yang, Qiong Zhang, Weipeng Zheng, and Gerrit Lohmann
Clim. Past, 18, 1047–1070, https://doi.org/10.5194/cp-18-1047-2022, https://doi.org/10.5194/cp-18-1047-2022, 2022
Short summary
Short summary
Since the orbital parameters of the past are different from today, applying the modern calendar to the past climate can lead to an artificial bias in seasonal cycles. With the use of multiple model outputs, we found that such a bias is non-ignorable and should be corrected to ensure an accurate comparison between modeled results and observational records, as well as between simulated past and modern climates, especially for the Last Interglacial.
Dmitry V. Sein, Anton Y. Dvornikov, Stanislav D. Martyanov, William Cabos, Vladimir A. Ryabchenko, Matthias Gröger, Daniela Jacob, Alok Kumar Mishra, and Pankaj Kumar
Earth Syst. Dynam., 13, 809–831, https://doi.org/10.5194/esd-13-809-2022, https://doi.org/10.5194/esd-13-809-2022, 2022
Short summary
Short summary
The effect of the marine biogeochemical variability upon the South Asian regional climate has been investigated. In the experiment where its full impact is activated, the average sea surface temperature is lower over most of the ocean. When the biogeochemical coupling is included, the main impacts include the enhanced phytoplankton primary production, a shallower thermocline, decreased SST and water temperature in subsurface layers.
Matthias Gröger, Christian Dieterich, Cyril Dutheil, H. E. Markus Meier, and Dmitry V. Sein
Earth Syst. Dynam., 13, 613–631, https://doi.org/10.5194/esd-13-613-2022, https://doi.org/10.5194/esd-13-613-2022, 2022
Short summary
Short summary
Atmospheric rivers transport high amounts of water from subtropical regions to Europe. They are an important driver of heavy precipitation and flooding. Their response to a warmer future climate in Europe has so far been assessed only by global climate models. In this study, we apply for the first time a high-resolution regional climate model that allow to better resolve and understand the fate of atmospheric rivers over Europe.
Alba de la Vara, Iván M. Parras-Berrocal, Alfredo Izquierdo, Dmitry V. Sein, and William Cabos
Earth Syst. Dynam., 13, 303–319, https://doi.org/10.5194/esd-13-303-2022, https://doi.org/10.5194/esd-13-303-2022, 2022
Short summary
Short summary
We study with the regionally coupled climate model ROM the impact of climate change on the Tyrrhenian Sea circulation, as well as the possible mechanisms and consequences in the NW Mediterranean Sea. Our results show a shift towards the summer circulation pattern by the end of the century. Also, water flowing via the Corsica Channel is more stratified and smaller in volume. Both factors may contribute to the interruption of deep water formation in the Gulf of Lions in the future.
Christopher Horvat and Lettie A. Roach
Geosci. Model Dev., 15, 803–814, https://doi.org/10.5194/gmd-15-803-2022, https://doi.org/10.5194/gmd-15-803-2022, 2022
Short summary
Short summary
Sea ice is a composite of individual pieces, called floes, ranging in horizontal size from meters to kilometers. Variations in sea ice geometry are often forced by ocean waves, a process that is an important target of global climate models as it affects the rate of sea ice melting. Yet directly simulating these interactions is computationally expensive. We present a neural-network-based model of wave–ice fracture that allows models to incorporate their effect without added computational cost.
Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, Qiang Wang, Nikolay Koldunov, Dmitry Sein, and Thomas Jung
Geosci. Model Dev., 15, 335–363, https://doi.org/10.5194/gmd-15-335-2022, https://doi.org/10.5194/gmd-15-335-2022, 2022
Short summary
Short summary
Structured-mesh ocean models are still the most mature in terms of functionality due to their long development history. However, unstructured-mesh ocean models have acquired new features and caught up in their functionality. This paper continues the work by Scholz et al. (2019) of documenting the features available in FESOM2.0. It focuses on the following two aspects: (i) partial bottom cells and embedded sea ice and (ii) dealing with mixing parameterisations enabled by using the CVMix package.
Keith B. Rodgers, Sun-Seon Lee, Nan Rosenbloom, Axel Timmermann, Gokhan Danabasoglu, Clara Deser, Jim Edwards, Ji-Eun Kim, Isla R. Simpson, Karl Stein, Malte F. Stuecker, Ryohei Yamaguchi, Tamás Bódai, Eui-Seok Chung, Lei Huang, Who M. Kim, Jean-François Lamarque, Danica L. Lombardozzi, William R. Wieder, and Stephen G. Yeager
Earth Syst. Dynam., 12, 1393–1411, https://doi.org/10.5194/esd-12-1393-2021, https://doi.org/10.5194/esd-12-1393-2021, 2021
Short summary
Short summary
A large ensemble of simulations with 100 members has been conducted with the state-of-the-art CESM2 Earth system model, using historical and SSP3-7.0 forcing. Our main finding is that there are significant changes in the variance of the Earth system in response to anthropogenic forcing, with these changes spanning a broad range of variables important to impacts for human populations and ecosystems.
Vera Fofonova, Tuomas Kärnä, Knut Klingbeil, Alexey Androsov, Ivan Kuznetsov, Dmitry Sidorenko, Sergey Danilov, Hans Burchard, and Karen Helen Wiltshire
Geosci. Model Dev., 14, 6945–6975, https://doi.org/10.5194/gmd-14-6945-2021, https://doi.org/10.5194/gmd-14-6945-2021, 2021
Short summary
Short summary
We present a test case of river plume spreading to evaluate coastal ocean models. Our test case reveals the level of numerical mixing (due to parameterizations used and numerical treatment of processes in the model) and the ability of models to reproduce complex dynamics. The major result of our comparative study is that accuracy in reproducing the analytical solution depends less on the type of applied model architecture or numerical grid than it does on the type of advection scheme.
Qiang Wang, Sergey Danilov, Longjiang Mu, Dmitry Sidorenko, and Claudia Wekerle
The Cryosphere, 15, 4703–4725, https://doi.org/10.5194/tc-15-4703-2021, https://doi.org/10.5194/tc-15-4703-2021, 2021
Short summary
Short summary
Using simulations, we found that changes in ocean freshwater content induced by wind perturbations can significantly affect the Arctic sea ice drift, thickness, concentration and deformation rates years after the wind perturbations. The impact is through changes in sea surface height and surface geostrophic currents and the most pronounced in warm seasons. Such a lasting impact might become stronger in a warming climate and implies the importance of ocean initialization in sea ice prediction.
Pengfei Wang, Jinrong Jiang, Pengfei Lin, Mengrong Ding, Junlin Wei, Feng Zhang, Lian Zhao, Yiwen Li, Zipeng Yu, Weipeng Zheng, Yongqiang Yu, Xuebin Chi, and Hailong Liu
Geosci. Model Dev., 14, 2781–2799, https://doi.org/10.5194/gmd-14-2781-2021, https://doi.org/10.5194/gmd-14-2781-2021, 2021
Short summary
Short summary
Global ocean general circulation models are a fundamental tool for oceanography research, ocean forecast, and climate change research. The increasing resolution will greatly improve simulations of the models, but it also demands much more computing resources. In this study, we have ported an ocean general circulation model to a heterogeneous computing system and have developed a 3–5 km model version. A 14-year integration has been conducted and the preliminary results have been evaluated.
Pablo Ortega, Jon I. Robson, Matthew Menary, Rowan T. Sutton, Adam Blaker, Agathe Germe, Jöel J.-M. Hirschi, Bablu Sinha, Leon Hermanson, and Stephen Yeager
Earth Syst. Dynam., 12, 419–438, https://doi.org/10.5194/esd-12-419-2021, https://doi.org/10.5194/esd-12-419-2021, 2021
Short summary
Short summary
Deep Labrador Sea densities are receiving increasing attention because of their link to many of the processes that govern decadal climate oscillations in the North Atlantic and their potential use as a precursor of those changes. This article explores those links and how they are represented in global climate models, documenting the main differences across models. Models are finally compared with observational products to identify the ones that reproduce the links more realistically.
James Keeble, Birgit Hassler, Antara Banerjee, Ramiro Checa-Garcia, Gabriel Chiodo, Sean Davis, Veronika Eyring, Paul T. Griffiths, Olaf Morgenstern, Peer Nowack, Guang Zeng, Jiankai Zhang, Greg Bodeker, Susannah Burrows, Philip Cameron-Smith, David Cugnet, Christopher Danek, Makoto Deushi, Larry W. Horowitz, Anne Kubin, Lijuan Li, Gerrit Lohmann, Martine Michou, Michael J. Mills, Pierre Nabat, Dirk Olivié, Sungsu Park, Øyvind Seland, Jens Stoll, Karl-Hermann Wieners, and Tongwen Wu
Atmos. Chem. Phys., 21, 5015–5061, https://doi.org/10.5194/acp-21-5015-2021, https://doi.org/10.5194/acp-21-5015-2021, 2021
Short summary
Short summary
Stratospheric ozone and water vapour are key components of the Earth system; changes to both have important impacts on global and regional climate. We evaluate changes to these species from 1850 to 2100 in the new generation of CMIP6 models. There is good agreement between the multi-model mean and observations, although there is substantial variation between the individual models. The future evolution of both ozone and water vapour is strongly dependent on the assumed future emissions scenario.
Tingfeng Dou, Cunde Xiao, Jiping Liu, Qiang Wang, Shifeng Pan, Jie Su, Xiaojun Yuan, Minghu Ding, Feng Zhang, Kai Xue, Peter A. Bieniek, and Hajo Eicken
The Cryosphere, 15, 883–895, https://doi.org/10.5194/tc-15-883-2021, https://doi.org/10.5194/tc-15-883-2021, 2021
Short summary
Short summary
Rain-on-snow (ROS) events can accelerate the surface ablation of sea ice, greatly influencing the ice–albedo feedback. We found that spring ROS events have shifted to earlier dates over the Arctic Ocean in recent decades, which is correlated with sea ice melt onset in the Pacific sector and most Eurasian marginal seas. There has been a clear transition from solid to liquid precipitation, leading to a reduction in spring snow depth on sea ice by more than −0.5 cm per decade since the 1980s.
Claudia Wekerle, Tore Hattermann, Qiang Wang, Laura Crews, Wilken-Jon von Appen, and Sergey Danilov
Ocean Sci., 16, 1225–1246, https://doi.org/10.5194/os-16-1225-2020, https://doi.org/10.5194/os-16-1225-2020, 2020
Short summary
Short summary
The high-resolution ocean models ROMS and FESOM configured for the Fram Strait reveal very energetic ocean conditions there. The two main currents meander strongly and shed circular currents of water, called eddies. Our analysis shows that this region is characterised by small and short-lived eddies (on average around a 5 km radius and 10 d lifetime). Both models agree on eddy properties and show similar patterns of baroclinic and barotropic instability of the West Spitsbergen Current.
Shaoqing Zhang, Haohuan Fu, Lixin Wu, Yuxuan Li, Hong Wang, Yunhui Zeng, Xiaohui Duan, Wubing Wan, Li Wang, Yuan Zhuang, Hongsong Meng, Kai Xu, Ping Xu, Lin Gan, Zhao Liu, Sihai Wu, Yuhu Chen, Haining Yu, Shupeng Shi, Lanning Wang, Shiming Xu, Wei Xue, Weiguo Liu, Qiang Guo, Jie Zhang, Guanghui Zhu, Yang Tu, Jim Edwards, Allison Baker, Jianlin Yong, Man Yuan, Yangyang Yu, Qiuying Zhang, Zedong Liu, Mingkui Li, Dongning Jia, Guangwen Yang, Zhiqiang Wei, Jingshan Pan, Ping Chang, Gokhan Danabasoglu, Stephen Yeager, Nan Rosenbloom, and Ying Guo
Geosci. Model Dev., 13, 4809–4829, https://doi.org/10.5194/gmd-13-4809-2020, https://doi.org/10.5194/gmd-13-4809-2020, 2020
Short summary
Short summary
Science advancement and societal needs require Earth system modelling with higher resolutions that demand tremendous computing power. We successfully scale the 10 km ocean and 25 km atmosphere high-resolution Earth system model to a new leading-edge heterogeneous supercomputer using state-of-the-art optimizing methods, promising the solution of high spatial resolution and time-varying frequency. Corresponding technical breakthroughs are of significance in modelling and HPC design communities.
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
Short summary
Short summary
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.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
Short summary
Short summary
The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Hailun He, Yuan Wang, Xiqiu Han, Yanzhou Wei, Pengfei Lin, Zhongyan Qiu, and Yejian Wang
Ocean Sci., 16, 895–906, https://doi.org/10.5194/os-16-895-2020, https://doi.org/10.5194/os-16-895-2020, 2020
Short summary
Short summary
Ocean profiling observation in the Indian Ocean is not sufficient. We conducted a hydrographic survey on the Carlsberg Ridge, which is a mid-ocean ridge in the northwest Indian Ocean, to obtain snapshots of sectional temperature, salinity, and density fields by combining the ARGO data. The results show mesoscale eddies located along the specific ridge and the existence of a west-propagating planetary wave. The results provide references in the regional ocean circulation.
Dmitry Sidorenko, Sergey Danilov, Nikolay Koldunov, Patrick Scholz, and Qiang Wang
Geosci. Model Dev., 13, 3337–3345, https://doi.org/10.5194/gmd-13-3337-2020, https://doi.org/10.5194/gmd-13-3337-2020, 2020
Short summary
Short summary
Computation of barotropic and meridional overturning streamfunctions for models formulated on unstructured meshes is commonly preceded by interpolation to a regular mesh. This operation destroys the original conservation, which can be then be artificially imposed to make the computation possible. An elementary method is proposed that avoids interpolation and preserves conservation in a strict model sense.
Taylor A. Shropshire, Steven L. Morey, Eric P. Chassignet, Alexandra Bozec, Victoria J. Coles, Michael R. Landry, Rasmus Swalethorp, Glenn Zapfe, and Michael R. Stukel
Biogeosciences, 17, 3385–3407, https://doi.org/10.5194/bg-17-3385-2020, https://doi.org/10.5194/bg-17-3385-2020, 2020
Short summary
Short summary
Zooplankton are the smallest animals in the ocean and important food for fish. Despite their importance, zooplankton have been relatively undersampled. To better understand the zooplankton community in the Gulf of Mexico (GoM), we developed a model to simulate their dynamics. We found that heterotrophic protists are important for supporting mesozooplankton, which are the primary prey of larval fish. The model developed in this study has the potential to improve fisheries management in the GoM.
Ivan M. Parras-Berrocal, Ruben Vazquez, William Cabos, Dmitry Sein, Rafael Mañanes, Juan Perez-Sanz, and Alfredo Izquierdo
Ocean Sci., 16, 743–765, https://doi.org/10.5194/os-16-743-2020, https://doi.org/10.5194/os-16-743-2020, 2020
Short summary
Short summary
This work presents high-resolution simulations of a coupled regional model in the Mediterranean basin. The approach allows us to assess the role of ocean feedbacks in the downscaled climate. Our results show good skills in simulating present climate; the model's robustness introduces improvements in reproducing physical processes at local scales. Our climate projections reveal that by the end of the 21st century the Mediterranean Sea will be warmer and saltier although not in a homogeneous way.
Reinhard Schiemann, Panos Athanasiadis, David Barriopedro, Francisco Doblas-Reyes, Katja Lohmann, Malcolm J. Roberts, Dmitry V. Sein, Christopher D. Roberts, Laurent Terray, and Pier Luigi Vidale
Weather Clim. Dynam., 1, 277–292, https://doi.org/10.5194/wcd-1-277-2020, https://doi.org/10.5194/wcd-1-277-2020, 2020
Short summary
Short summary
In blocking situations the westerly atmospheric flow in the midlatitudes is blocked by near-stationary high-pressure systems. Blocking can be associated with extremes such as cold spells and heat waves. Climate models are known to underestimate blocking occurrence. Here, we assess the latest generation of models and find improvements in simulated blocking, partly due to increases in model resolution. These new models are therefore more suitable for studying climate extremes related to blocking.
Torben Koenigk, Ramon Fuentes-Franco, Virna Meccia, Oliver Gutjahr, Laura C. Jackson, Adrian L. New, Pablo Ortega, Christopher Roberts, Malcolm Roberts, Thomas Arsouze, Doroteaciro Iovino, Marie-Pierre Moine, and Dmitry V. Sein
Ocean Sci. Discuss., https://doi.org/10.5194/os-2020-41, https://doi.org/10.5194/os-2020-41, 2020
Revised manuscript not accepted
Short summary
Short summary
The mixing of water masses into the deep ocean in the North Atlantic is important for the entire global ocean circulation. We use seven global climate models to investigate the effect of increasing the model resolution on this deep ocean mixing. The main result is that increased model resolution leads to a deeper mixing of water masses in the Labrador Sea but has less effect in the Greenland Sea. However, most of the models overestimate the deep ocean mixing compared to observations.
Valentin Resseguier, Wei Pan, and Baylor Fox-Kemper
Nonlin. Processes Geophys., 27, 209–234, https://doi.org/10.5194/npg-27-209-2020, https://doi.org/10.5194/npg-27-209-2020, 2020
Short summary
Short summary
Geophysical flows span a broader range of temporal and spatial scales than can be resolved numerically. One way to alleviate the ensuing numerical errors is to combine simulations with measurements, taking account of the accuracies of these two sources of information. Here we quantify the distribution of numerical simulation errors without relying on high-resolution numerical simulations. Specifically, small-scale random vortices are added to simulations while conserving energy or circulation.
Mattia Righi, Bouwe Andela, Veronika Eyring, Axel Lauer, Valeriu Predoi, Manuel Schlund, Javier Vegas-Regidor, Lisa Bock, Björn Brötz, Lee de Mora, Faruk Diblen, Laura Dreyer, Niels Drost, Paul Earnshaw, Birgit Hassler, Nikolay Koldunov, Bill Little, Saskia Loosveldt Tomas, and Klaus Zimmermann
Geosci. Model Dev., 13, 1179–1199, https://doi.org/10.5194/gmd-13-1179-2020, https://doi.org/10.5194/gmd-13-1179-2020, 2020
Short summary
Short summary
This paper describes the second major release of ESMValTool, a community diagnostic and performance metrics tool for the evaluation of Earth system models. This new version features a brand new design, with an improved interface and a revised preprocessor. It takes advantage of state-of-the-art computational libraries and methods to deploy efficient and user-friendly data processing, improving the performance over its predecessor by more than a factor of 30.
Anson Cheung, Baylor Fox-Kemper, and Timothy Herbert
Clim. Past, 15, 1985–1998, https://doi.org/10.5194/cp-15-1985-2019, https://doi.org/10.5194/cp-15-1985-2019, 2019
Short summary
Short summary
We test two assumptions that are often made in paleoclimate studies by using observations and ask whether temperature and productivity proxy records in the Southern California Current can be used to reconstruct Ekman upwelling. By examining the covariation between alongshore wind stress, temperature, and productivity, we found that the dominant covarying pattern does not reflect Ekman upwelling. Other upwelling patterns found are timescale dependent. Multiple proxies can improve reconstruction.
Patrick Scholz, Dmitry Sidorenko, Ozgur Gurses, Sergey Danilov, Nikolay Koldunov, Qiang Wang, Dmitry Sein, Margarita Smolentseva, Natalja Rakowsky, and Thomas Jung
Geosci. Model Dev., 12, 4875–4899, https://doi.org/10.5194/gmd-12-4875-2019, https://doi.org/10.5194/gmd-12-4875-2019, 2019
Short summary
Short summary
This paper is the first in a series documenting and assessing important key components of the Finite-volumE Sea ice-Ocean Model version 2.0 (FESOM2.0). We assess the hydrographic biases, large-scale circulation, numerical performance and scalability of FESOM2.0 compared with its predecessor, FESOM1.4. The main conclusion is that the results of FESOM2.0 compare well to FESOM1.4 in terms of model biases but with a remarkable performance speedup with a 3 times higher throughput.
Christopher Horvat, Lettie A. Roach, Rachel Tilling, Cecilia M. Bitz, Baylor Fox-Kemper, Colin Guider, Kaitlin Hill, Andy Ridout, and Andrew Shepherd
The Cryosphere, 13, 2869–2885, https://doi.org/10.5194/tc-13-2869-2019, https://doi.org/10.5194/tc-13-2869-2019, 2019
Short summary
Short summary
Changes in the floe size distribution (FSD) are important for sea ice evolution but to date largely unobserved and unknown. Climate models, forecast centres, ship captains, and logistic specialists cannot currently obtain statistical information about sea ice floe size on demand. We develop a new method to observe the FSD at global scales and high temporal and spatial resolution. With refinement, this method can provide crucial information for polar ship routing and real-time forecasting.
Nikolay V. Koldunov, Vadym Aizinger, Natalja Rakowsky, Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, and Thomas Jung
Geosci. Model Dev., 12, 3991–4012, https://doi.org/10.5194/gmd-12-3991-2019, https://doi.org/10.5194/gmd-12-3991-2019, 2019
Short summary
Short summary
We measure how computational performance of the global FESOM2 ocean model (formulated on an unstructured mesh) changes with the increase in the number of computational cores. We find that for many components of the model the performance increases linearly but we also identify two bottlenecks: sea ice and ssh submodules. We show that FESOM2 is on par with the state-of-the-art ocean models in terms of throughput that reach 16 simulated years per day for eddy resolving configuration (1/10°).
Özgür Gürses, Vanessa Kolatschek, Qiang Wang, and Christian Bernd Rodehacke
The Cryosphere, 13, 2317–2324, https://doi.org/10.5194/tc-13-2317-2019, https://doi.org/10.5194/tc-13-2317-2019, 2019
Short summary
Short summary
The warming of the Earth's climate system causes sea level rise. In Antarctica, ice streams flow into the sea and develop ice shelves. These are floating extensions of the ice streams. Ocean water melts these ice shelves. It has been proposed that a submarine wall could shield these ice shelves from the warm water. Our model simulation shows that the wall protects ice shelves. However, the warm water flows to neighboring ice shelves. There, enhanced melting reduces the effectiveness of the wall.
Thomas Rackow, Dmitry V. Sein, Tido Semmler, Sergey Danilov, Nikolay V. Koldunov, Dmitry Sidorenko, Qiang Wang, and Thomas Jung
Geosci. Model Dev., 12, 2635–2656, https://doi.org/10.5194/gmd-12-2635-2019, https://doi.org/10.5194/gmd-12-2635-2019, 2019
Short summary
Short summary
Current climate models show errors in the deep ocean that are larger than the level of natural variability and the response to enhanced greenhouse gas concentrations. These errors are larger than the signals we aim to predict. With the AWI Climate Model, we show that increasing resolution to resolve eddies can lead to major reductions in deep ocean errors. AWI's next-generation (CMIP6) model configuration will thus use locally eddy-resolving computational grids for projecting climate change.
Xiaolong Zhao, Chun Zhou, Xiaobiao Xu, Ruijie Ye, Jiwei Tian, and Wei Zhao
Ocean Sci. Discuss., https://doi.org/10.5194/os-2019-29, https://doi.org/10.5194/os-2019-29, 2019
Preprint withdrawn
Short summary
Short summary
This study presents a detailed spatial structure and temporal variability of the deep circulation under enhanced mixing in the South China Sea (SCS) based on eddy-resolving model simulations verified by continuous current-meter observations and enables us to investigate sensitivity to distribution of mixing. Comparing the northern shelf of the SCS with the Luzon Strait, deep circulation in the SCS is more sensitive to the large vertical mixing parameters in the Zhongsha Island Chain area.
Nicole S. Lovenduski, Stephen G. Yeager, Keith Lindsay, and Matthew C. Long
Earth Syst. Dynam., 10, 45–57, https://doi.org/10.5194/esd-10-45-2019, https://doi.org/10.5194/esd-10-45-2019, 2019
Short summary
Short summary
This paper shows that the absorption of carbon dioxide by the ocean is predictable several years in advance. This is important because fossil-fuel-derived carbon dioxide is largely responsible for anthropogenic global warming and because carbon dioxide emission management and global carbon cycle budgeting exercises can benefit from foreknowledge of ocean carbon absorption. The promising results from this new forecast system justify the need for additional oceanic observations.
Nikolay V. Koldunov and Luisa Cristini
Adv. Geosci., 45, 295–303, https://doi.org/10.5194/adgeo-45-295-2018, https://doi.org/10.5194/adgeo-45-295-2018, 2018
Short summary
Short summary
We believe that project managers can benefit from using programming languages in their work. In this paper we show several simple examples of how python programming language can be used for some of the basic text manipulation tasks, as well as describe more complicated test cases using a HORIZON 2020 type European project as an example.
Ali Aydoğdu, Nadia Pinardi, Emin Özsoy, Gokhan Danabasoglu, Özgür Gürses, and Alicia Karspeck
Ocean Sci., 14, 999–1019, https://doi.org/10.5194/os-14-999-2018, https://doi.org/10.5194/os-14-999-2018, 2018
Short summary
Short summary
A 6-year simulation of the Turkish Straits System is presented. The simulation is performed by a model using unstructured triangular mesh and realistic atmospheric forcing. The dynamics and circulation of the Marmara Sea are analysed and the mean state of the system is discussed on annual averages. Volume fluxes computed throughout the simulation are presented and the response of the model to severe storms is shown. Finally, it was possible to assess the kinetic energy budget in the Marmara Sea.
Qiang Wang, Claudia Wekerle, Sergey Danilov, Xuezhu Wang, and Thomas Jung
Geosci. Model Dev., 11, 1229–1255, https://doi.org/10.5194/gmd-11-1229-2018, https://doi.org/10.5194/gmd-11-1229-2018, 2018
Short summary
Short summary
For developing a system for Arctic research, we evaluate the Arctic Ocean simulated by FESOM. We use two global meshes differing in the horizontal resolution only in the Arctic Ocean (24 vs. 4.5 km). The high resolution significantly improves the model's representation of the Arctic Ocean. The most pronounced improvement is in the Arctic intermediate layer. The high resolution also improves the ocean surface circulation, mainly through a better representation of the Canadian Arctic Archipelago.
Seonmin Ahn, Baylor Fox-Kemper, Timothy Herbert, and Charles Lawrence
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-1, https://doi.org/10.5194/cp-2018-1, 2018
Revised manuscript not accepted
Nikolay V. Koldunov, Armin Köhl, Nuno Serra, and Detlef Stammer
The Cryosphere, 11, 2265–2281, https://doi.org/10.5194/tc-11-2265-2017, https://doi.org/10.5194/tc-11-2265-2017, 2017
Short summary
Short summary
The paper describes one of the first attempts to use the so-called adjoint data assimilation method to bring Arctic Ocean model simulations closer to observation, especially in terms of the sea ice. It is shown that after assimilation the model bias in simulating the Arctic sea ice is considerably reduced. There is also additional improvement in the sea ice thickens representation that is not assimilated directly.
James C. Orr, Raymond G. Najjar, Olivier Aumont, Laurent Bopp, John L. Bullister, Gokhan Danabasoglu, Scott C. Doney, John P. Dunne, Jean-Claude Dutay, Heather Graven, Stephen M. Griffies, Jasmin G. John, Fortunat Joos, Ingeborg Levin, Keith Lindsay, Richard J. Matear, Galen A. McKinley, Anne Mouchet, Andreas Oschlies, Anastasia Romanou, Reiner Schlitzer, Alessandro Tagliabue, Toste Tanhua, and Andrew Yool
Geosci. Model Dev., 10, 2169–2199, https://doi.org/10.5194/gmd-10-2169-2017, https://doi.org/10.5194/gmd-10-2169-2017, 2017
Short summary
Short summary
The Ocean Model Intercomparison Project (OMIP) is a model comparison effort under Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Its physical component is described elsewhere in this special issue. Here we describe its ocean biogeochemical component (OMIP-BGC), detailing simulation protocols and analysis diagnostics. Simulations focus on ocean carbon, other biogeochemical tracers, air-sea exchange of CO2 and related gases, and chemical tracers used to evaluate modeled circulation.
Anton Y. Dvornikov, Stanislav D. Martyanov, Vladimir A. Ryabchenko, Tatjana R. Eremina, Alexey V. Isaev, and Dmitry V. Sein
Earth Syst. Dynam., 8, 265–282, https://doi.org/10.5194/esd-8-265-2017, https://doi.org/10.5194/esd-8-265-2017, 2017
Sergey Danilov, Dmitry Sidorenko, Qiang Wang, and Thomas Jung
Geosci. Model Dev., 10, 765–789, https://doi.org/10.5194/gmd-10-765-2017, https://doi.org/10.5194/gmd-10-765-2017, 2017
Short summary
Short summary
Numerical models of global ocean circulation are used to learn about future climate. The ocean circulation is characterized by processes on different spatial scales which are still beyond the reach of present computers. We describe a new model setup that allows one to vary a model's spatial resolution and hence focus the computational power on regional dynamics, reaching a better description of local processes in areas of interest.
Arin D. Nelson, Jeffrey B. Weiss, Baylor Fox-Kemper, Royce K. P. Zia, and Fabienne Gaillard
Ocean Sci. Discuss., https://doi.org/10.5194/os-2016-105, https://doi.org/10.5194/os-2016-105, 2017
Revised manuscript has not been submitted
Short summary
Short summary
We quantify the skill in observing the variability of global upper ocean heat content (OHC) by applying the ISAS13 observing strategy to a CCSM simulation. We find that variability is unreliably observed before 2005, while observed annual running means for 2005–2013 correlate well with model "truth" to a median of 95 %. When scaled to the real ocean, we find signal-to-noise ratios of 1.9 for pre-Argo times (1990–2005) and 14.7 after Argo is introduced (2005–2013). The global warming is robust.
George J. Boer, Douglas M. Smith, Christophe Cassou, Francisco Doblas-Reyes, Gokhan Danabasoglu, Ben Kirtman, Yochanan Kushnir, Masahide Kimoto, Gerald A. Meehl, Rym Msadek, Wolfgang A. Mueller, Karl E. Taylor, Francis Zwiers, Michel Rixen, Yohan Ruprich-Robert, and Rosie Eade
Geosci. Model Dev., 9, 3751–3777, https://doi.org/10.5194/gmd-9-3751-2016, https://doi.org/10.5194/gmd-9-3751-2016, 2016
Short summary
Short summary
The Decadal Climate Prediction Project (DCPP) investigates our ability to skilfully predict climate variations from a year to a decade ahead by means of a series of retrospective forecasts. Quasi-real-time forecasts are also produced for potential users. In addition, the DCPP investigates how perturbations such as volcanoes affect forecasts and, more broadly, what new information can be learned about the mechanisms governing climate variations by means of case studies of past climate behaviour.
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
Short summary
Short summary
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. Horvat and E. Tziperman
The Cryosphere, 9, 2119–2134, https://doi.org/10.5194/tc-9-2119-2015, https://doi.org/10.5194/tc-9-2119-2015, 2015
Short summary
Short summary
Sea-ice cover is composed of floes of different sizes and thicknesses, whose distribution varies in space and time, and may affect the interaction between sea ice and the ocean and atmosphere, yet is not represented in climate models. We develop and demonstrate a model for the evolution of the joint distribution of floe sizes and thicknesses, subject to melting and freezing, mechanical interactions between floes, and the fracture of floes by waves, forced by atmospheric and ocean forcing fields.
S. Danilov, Q. Wang, R. Timmermann, N. Iakovlev, D. Sidorenko, M. Kimmritz, T. Jung, and J. Schröter
Geosci. Model Dev., 8, 1747–1761, https://doi.org/10.5194/gmd-8-1747-2015, https://doi.org/10.5194/gmd-8-1747-2015, 2015
Short summary
Short summary
Unstructured meshes allow multi-resolution modeling of ocean dynamics. Sea ice models formulated on unstructured meshes are a necessary component of ocean models intended for climate studies. This work presents a description of a finite-element sea ice model which is used as a component of a finite-element sea ice ocean circulation model. The principles underlying its design can be of interest to other groups pursuing ocean modelling on unstructured meshes.
N. Sudarchikova, U. Mikolajewicz, C. Timmreck, D. O'Donnell, G. Schurgers, D. Sein, and K. Zhang
Clim. Past, 11, 765–779, https://doi.org/10.5194/cp-11-765-2015, https://doi.org/10.5194/cp-11-765-2015, 2015
V. Schourup-Kristensen, D. Sidorenko, D. A. Wolf-Gladrow, and C. Völker
Geosci. Model Dev., 7, 2769–2802, https://doi.org/10.5194/gmd-7-2769-2014, https://doi.org/10.5194/gmd-7-2769-2014, 2014
I. A. Dmitrenko, S. A. Kirillov, N. Serra, N. V. Koldunov, V. V. Ivanov, U. Schauer, I. V. Polyakov, D. Barber, M. Janout, V. S. Lien, M. Makhotin, and Y. Aksenov
Ocean Sci., 10, 719–730, https://doi.org/10.5194/os-10-719-2014, https://doi.org/10.5194/os-10-719-2014, 2014
P. Lin, Y. Song, Y. Yu, and H. Liu
Clim. Past Discuss., https://doi.org/10.5194/cpd-10-2519-2014, https://doi.org/10.5194/cpd-10-2519-2014, 2014
Revised manuscript not accepted
Q. Wang, S. Danilov, D. Sidorenko, R. Timmermann, C. Wekerle, X. Wang, T. Jung, and J. Schröter
Geosci. Model Dev., 7, 663–693, https://doi.org/10.5194/gmd-7-663-2014, https://doi.org/10.5194/gmd-7-663-2014, 2014
Related subject area
Oceanography
CAR36, a regional high-resolution ocean forecasting system for improving drift and beaching of Sargassum in the Caribbean archipelago
Implementation of additional spectral wave field exchanges in a three-dimensional wave–current coupled WAVEWATCH-III (version 6.07) and CROCO (version 1.2) configuration: assessment of their implications for macro-tidal coastal hydrodynamics
Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system
LOCATE v1.0: numerical modelling of floating marine debris dispersion in coastal regions using Parcels v2.4.2
New insights into the South China Sea throughflow and water budget seasonal cycle: evaluation and analysis of a high-resolution configuration of the ocean model SYMPHONIE version 2.4
MQGeometry-1.0: a multi-layer quasi-geostrophic solver on non-rectangular geometries
Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on El Niño–Southern Oscillation forecasts
Great Lakes wave forecast system on high-resolution unstructured meshes
Impact of increased resolution on Arctic Ocean simulations in Ocean Model Intercomparison Project phase 2 (OMIP-2)
StraitFlux – Precise computations of Water Strait fluxes on various Modelling Grids
A high-resolution physical–biogeochemical model for marine resource applications in the northwest Atlantic (MOM6-COBALT-NWA12 v1.0)
A flexible z-layers approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)
Implementation and assessment of a model including mixotrophs and the carbonate cycle (Eco3M_MIX-CarbOx v1.0) in a highly dynamic Mediterranean coastal environment (Bay of Marseille, France) – Part 1: Evolution of ecosystem composition under limited light and nutrient conditions
Ocean wave tracing v.1: a numerical solver of the wave ray equations for ocean waves on variable currents at arbitrary depths
Design and evaluation of an efficient high-precision ocean surface wave model with a multiscale grid system (MSG_Wav1.0)
Evaluation of the CMCC global eddying ocean model for the Ocean Model Intercomparison Project (OMIP2)
Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard
Open-ocean tides simulated by ICON-O, version icon-2.6.6
Comparison of the Coastal and Regional Ocean Community Model (CROCO) and NCAR-LES in Non-hydrostatic Simulations
Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll
Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var
Using the COAsT Python package to develop a standardised validation workflow for ocean physics models
Improving Antarctic Bottom Water precursors in NEMO for climate applications
Formulation, optimization, and sensitivity of NitrOMZv1.0, a biogeochemical model of the nitrogen cycle in oceanic oxygen minimum zones
Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu
Adding sea ice effects to a global operational model (NEMO v3.6) for forecasting total water level: approach and impact
DELWAVE 1.0: Deep-learning surrogate model of surface wave climate in the Adriatic Basin
Enhanced ocean wave modeling by including effect of breaking under both deep- and shallow-water conditions
An internal solitary wave forecasting model in the northern South China Sea (ISWFM-NSCS)
Intercomparisons of five ocean particle tracking software packages
The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methylmercury in fish
Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0)
Arctic Ocean simulations in the CMIP6 Ocean Model Intercomparison Project (OMIP)
ChemicalDrift 1.0: an open-source Lagrangian chemical-fate and transport model for organic aquatic pollutants
The Met Office operational wave forecasting system: the evolution of the regional and global models
4DVarNet-SSH: end-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry
Development and validation of a global 1∕32° surface-wave–tide–circulation coupled ocean model: FIO-COM32
Reproducible and relocatable regional ocean modelling: fundamentals and practices
Barotropic tides in MPAS-Ocean (E3SM V2): impact of ice shelf cavities
Using the two-way nesting technique AGRIF with MARS3D V11.2 to improve hydrodynamics and estimate environmental indicators
Multidecadal and climatological surface current simulations for the southwestern Indian Ocean at 1∕50° resolution
The tidal effects in the Finite-volumE Sea ice–Ocean Model (FESOM2.1): a comparison between parameterised tidal mixing and explicit tidal forcing
HIDRA2: deep-learning ensemble sea level and storm tide forecasting in the presence of seiches – the case of the northern Adriatic
Moana Ocean Hindcast – a > 25-year simulation for New Zealand waters using the Regional Ocean Modeling System (ROMS) v3.9 model
A nonhydrostatic oceanic regional model, ORCTM v1, for internal solitary wave simulation
How does 4DVar data assimilation affect the vertical representation of mesoscale eddies? A case study with observing system simulation experiments (OSSEs) using ROMS v3.9
An ensemble Kalman filter-based ocean data assimilation system improved by adaptive observation error inflation (AOEI)
GULF18, a high-resolution NEMO-based tidal ocean model of the Arabian/Persian Gulf
The Baltic Sea Model Intercomparison Project (BMIP) – a platform for model development, evaluation, and uncertainty assessment
An ensemble Kalman filter system with the Stony Brook Parallel Ocean Model v1.0
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173, https://doi.org/10.5194/gmd-17-3157-2024, https://doi.org/10.5194/gmd-17-3157-2024, 2024
Short summary
Short summary
In order to improve Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher-resolution ocean currents. To this goal a 3 km resolution regional ocean model has been developed. Its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation was found to be quite realistic.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
Geosci. Model Dev., 17, 2829–2853, https://doi.org/10.5194/gmd-17-2829-2024, https://doi.org/10.5194/gmd-17-2829-2024, 2024
Short summary
Short summary
Here a new method of modelling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean currents and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave–current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
Short summary
Short summary
Ocean forecasting relies on the combination of numerical models and ocean observations through data assimilation (DA). Here we assess the performance of two DA systems in a dynamic western boundary current, the East Australian Current, across a common modelling and observational framework. We show that the more advanced, time-dependent method outperforms the time-independent method for forecast horizons of 5 d. This advocates the use of advanced methods for highly variable oceanic regions.
Ivan Hernandez, Leidy M. Castro-Rosero, Manuel Espino, and Jose M. Alsina Torrent
Geosci. Model Dev., 17, 2221–2245, https://doi.org/10.5194/gmd-17-2221-2024, https://doi.org/10.5194/gmd-17-2221-2024, 2024
Short summary
Short summary
The LOCATE numerical model was developed to conduct Lagrangian simulations of the transport and dispersion of marine debris at coastal scales. High-resolution hydrodynamic data and a beaching module that used particle distance to the shore for land–water boundary detection were used on a realistic debris discharge scenario comparing hydrodynamic data at various resolutions. Coastal processes and complex geometric structures were resolved when using nested grids and distance-to-shore beaching.
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
Short summary
Short summary
A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
Geosci. Model Dev., 17, 1749–1764, https://doi.org/10.5194/gmd-17-1749-2024, https://doi.org/10.5194/gmd-17-1749-2024, 2024
Short summary
Short summary
We present a new way of solving the quasi-geostrophic (QG) equations, a simple set of equations describing ocean dynamics. Our method is solely based on the numerical methods used to solve the equations and requires no parameter tuning. Moreover, it can handle non-rectangular geometries, opening the way to study QG equations on realistic domains. We release a PyTorch implementation to ease future machine-learning developments on top of the presented method.
Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song
Geosci. Model Dev., 17, 1651–1665, https://doi.org/10.5194/gmd-17-1651-2024, https://doi.org/10.5194/gmd-17-1651-2024, 2024
Short summary
Short summary
Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.
Ali Abdolali, Saeideh Banihashemi, Jose Henrique Alves, Aron Roland, Tyler J. Hesser, Mary Anderson Bryant, and Jane McKee Smith
Geosci. Model Dev., 17, 1023–1039, https://doi.org/10.5194/gmd-17-1023-2024, https://doi.org/10.5194/gmd-17-1023-2024, 2024
Short summary
Short summary
This article presents an overview of the development and implementation of Great Lake Wave Unstructured (GLWUv2.0), including the core model and workflow design and development. The validation was conducted against in situ data for the re-forecasted duration for summer and wintertime (ice season). The article describes the limitations and challenges encountered in the operational environment and the path forward for the next generation of wave forecast systems in enclosed basins like the GL.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
Short summary
Short summary
Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
EGUsphere, https://doi.org/10.5194/egusphere-2023-2883, https://doi.org/10.5194/egusphere-2023-2883, 2024
Short summary
Short summary
Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data is complicated by the distortion of the used modelling grids and the large number of different grid-types. We present two new methods that allow to calculate oceanic fluxes of volume, heat, salinity and ice through almost arbitrary sections for various models and reanalyses, independent of the used modelling grids.
Andrew C. Ross, Charles A. Stock, Alistair Adcroft, Enrique Curchitser, Robert Hallberg, Matthew J. Harrison, Katherine Hedstrom, Niki Zadeh, Michael Alexander, Wenhao Chen, Elizabeth J. Drenkard, Hubert du Pontavice, Raphael Dussin, Fabian Gomez, Jasmin G. John, Dujuan Kang, Diane Lavoie, Laure Resplandy, Alizée Roobaert, Vincent Saba, Sang-Ik Shin, Samantha Siedlecki, and James Simkins
Geosci. Model Dev., 16, 6943–6985, https://doi.org/10.5194/gmd-16-6943-2023, https://doi.org/10.5194/gmd-16-6943-2023, 2023
Short summary
Short summary
We evaluate a model for northwest Atlantic Ocean dynamics and biogeochemistry that balances high resolution with computational economy by building on the new regional features in the MOM6 ocean model and COBALT biogeochemical model. We test the model's ability to simulate impactful historical variability and find that the model simulates the mean state and variability of most features well, which suggests the model can provide information to inform living-marine-resource applications.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
Short summary
Short summary
We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, France Van Wambeke, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 16, 6701–6739, https://doi.org/10.5194/gmd-16-6701-2023, https://doi.org/10.5194/gmd-16-6701-2023, 2023
Short summary
Short summary
While several studies have shown that mixotrophs play a crucial role in the carbon cycle, the impact of environmental forcings on their dynamics remains poorly investigated. Using a biogeochemical model that considers mixotrophs, we study the impact of light and nutrient concentration on the ecosystem composition in a highly dynamic Mediterranean coastal area: the Bay of Marseille. We show that mixotrophs cope better with oligotrophic conditions compared to strict auto- and heterotrophs.
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, and Øyvind Breivik
Geosci. Model Dev., 16, 6515–6530, https://doi.org/10.5194/gmd-16-6515-2023, https://doi.org/10.5194/gmd-16-6515-2023, 2023
Short summary
Short summary
Surface waves that propagate in oceanic or coastal environments get influenced by their surroundings. Changes in the ambient current or the depth profile affect the wave propagation path, and the change in wave direction is called refraction. Some analytical solutions to the governing equations exist under ideal conditions, but for realistic situations, the equations must be solved numerically. Here we present such a numerical solver under an open-source license.
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev., 16, 6393–6412, https://doi.org/10.5194/gmd-16-6393-2023, https://doi.org/10.5194/gmd-16-6393-2023, 2023
Short summary
Short summary
Ocean surface waves play an important role in the air–sea interface but are rarely activated in high-resolution Earth system simulations due to their expensive computational costs. To alleviate this situation, this paper designs a new wave modeling framework with a multiscale grid system. Evaluations of a series of numerical experiments show that it has good feasibility and applicability in the WAVEWATCH III model, WW3, and can achieve the goals of efficient and high-precision wave simulation.
Doroteaciro Iovino, Pier Giuseppe Fogli, and Simona Masina
Geosci. Model Dev., 16, 6127–6159, https://doi.org/10.5194/gmd-16-6127-2023, https://doi.org/10.5194/gmd-16-6127-2023, 2023
Short summary
Short summary
This paper describes the model performance of three global ocean–sea ice configurations, from non-eddying (1°) to eddy-rich (1/16°) resolutions. Model simulations are obtained following the Ocean Model Intercomparison Project phase 2 (OMIP2) protocol. We compare key global climate variables across the three models and against observations, emphasizing the relative advantages and disadvantages of running forced ocean–sea ice models at higher resolution.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
Short summary
Short summary
A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, and Vikram Singh
Geosci. Model Dev., 16, 5179–5196, https://doi.org/10.5194/gmd-16-5179-2023, https://doi.org/10.5194/gmd-16-5179-2023, 2023
Short summary
Short summary
The new ocean general circulation model ICON-O is developed for running experiments at kilometer scales and beyond. One targeted application is to simulate internal tides crucial for ocean mixing. To ensure their realism, which is difficult to assess, we evaluate the barotropic tides that generate internal tides. We show that ICON-O is able to realistically simulate the major aspects of the observed barotropic tides and discuss the aspects that impact the quality of the simulated tides.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Francis Auclair, Peter P. Sullivan, and Paul S. Hall
EGUsphere, https://doi.org/10.5194/egusphere-2023-1657, https://doi.org/10.5194/egusphere-2023-1657, 2023
Short summary
Short summary
Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are similarly accurate, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Bror F. Jönsson, Christopher L. Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael L. Forget, Christian Müller, Marie-Fanny Racault, Christopher N. Hill, Thomas Jackson, and Shubha Sathyendranath
Geosci. Model Dev., 16, 4639–4657, https://doi.org/10.5194/gmd-16-4639-2023, https://doi.org/10.5194/gmd-16-4639-2023, 2023
Short summary
Short summary
While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover's distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.
Rafael Santana, Helen Macdonald, Joanne O'Callaghan, Brian Powell, Sarah Wakes, and Sutara H. Suanda
Geosci. Model Dev., 16, 3675–3698, https://doi.org/10.5194/gmd-16-3675-2023, https://doi.org/10.5194/gmd-16-3675-2023, 2023
Short summary
Short summary
We show the importance of assimilating subsurface temperature and velocity data in a model of the East Auckland Current. Assimilation of velocity increased the representation of large oceanic vortexes. Assimilation of temperature is needed to correctly simulate temperatures around 100 m depth, which is the most difficult region to simulate in ocean models. Our simulations showed improved results in comparison to the US Navy global model and highlight the importance of regional models.
David Byrne, Jeff Polton, Enda O'Dea, and Joanne Williams
Geosci. Model Dev., 16, 3749–3764, https://doi.org/10.5194/gmd-16-3749-2023, https://doi.org/10.5194/gmd-16-3749-2023, 2023
Short summary
Short summary
Validation is a crucial step during the development of models for ocean simulation. The purpose of validation is to assess how accurate a model is. It is most commonly done by comparing output from a model to actual observations. In this paper, we introduce and demonstrate usage of the COAsT Python package to standardise the validation process for physical ocean models. We also discuss our five guiding principles for standardised validation.
Katherine Hutchinson, Julie Deshayes, Christian Éthé, Clément Rousset, Casimir de Lavergne, Martin Vancoppenolle, Nicolas C. Jourdain, and Pierre Mathiot
Geosci. Model Dev., 16, 3629–3650, https://doi.org/10.5194/gmd-16-3629-2023, https://doi.org/10.5194/gmd-16-3629-2023, 2023
Short summary
Short summary
Bottom Water constitutes the lower half of the ocean’s overturning system and is primarily formed in the Weddell and Ross Sea in the Antarctic due to interactions between the atmosphere, ocean, sea ice and ice shelves. Here we use a global ocean 1° resolution model with explicit representation of the three large ice shelves important for the formation of the parent waters of Bottom Water. We find doing so reduces salt biases, improves water mass realism and gives realistic ice shelf melt rates.
Daniele Bianchi, Daniel McCoy, and Simon Yang
Geosci. Model Dev., 16, 3581–3609, https://doi.org/10.5194/gmd-16-3581-2023, https://doi.org/10.5194/gmd-16-3581-2023, 2023
Short summary
Short summary
We present NitrOMZ, a new model of the oceanic nitrogen cycle that simulates chemical transformations within oxygen minimum zones (OMZs). We describe the model formulation and its implementation in a one-dimensional representation of the water column before evaluating its ability to reproduce observations in the eastern tropical South Pacific. We conclude by describing the model sensitivity to parameter choices and environmental factors and its application to nitrogen cycling in the ocean.
Rui Sun, Alison Cobb, Ana B. Villas Bôas, Sabique Langodan, Aneesh C. Subramanian, Matthew R. Mazloff, Bruce D. Cornuelle, Arthur J. Miller, Raju Pathak, and Ibrahim Hoteit
Geosci. Model Dev., 16, 3435–3458, https://doi.org/10.5194/gmd-16-3435-2023, https://doi.org/10.5194/gmd-16-3435-2023, 2023
Short summary
Short summary
In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS. We then performed a case study using the newly implemented model to study Tropical Cyclone Mekunu, which occurred in the Arabian Sea. We found that the coupled model better simulates the cyclone than the uncoupled model, but the impact of waves on the cyclone is not significant. However, the waves change the sea surface temperature and mixed layer, especially in the cold waves produced due to the cyclone.
Pengcheng Wang and Natacha B. Bernier
Geosci. Model Dev., 16, 3335–3354, https://doi.org/10.5194/gmd-16-3335-2023, https://doi.org/10.5194/gmd-16-3335-2023, 2023
Short summary
Short summary
Effects of sea ice are typically neglected in operational flood forecast systems. In this work, we capture these effects via the addition of a parameterized ice–ocean stress. The parameterization takes advantage of forecast fields from an advanced ice–ocean model and features a novel, consistent representation of the tidal relative ice–ocean velocity. The new parameterization leads to improved forecasts of tides and storm surges in polar regions. Associated physical processes are discussed.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
EGUsphere, https://doi.org/10.5194/egusphere-2023-718, https://doi.org/10.5194/egusphere-2023-718, 2023
Short summary
Short summary
We propose a new point-prediction DEep Learning WAVe Emulating model (DELWAVE) which successfully emulates the ocean wave model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modeling is substantially weaker than the climate change signal.
Yue Xu and Xiping Yu
Geosci. Model Dev., 16, 2811–2831, https://doi.org/10.5194/gmd-16-2811-2023, https://doi.org/10.5194/gmd-16-2811-2023, 2023
Short summary
Short summary
An accurate description of the wind energy input into ocean waves is crucial to ocean wave modeling, and a physics-based consideration of the effect of wave breaking is absolutely necessary to obtain such an accurate description, particularly under extreme conditions. This study evaluates the performance of a recently improved formula, taking into account not only the effect of breaking but also the effect of airflow separation on the leeside of steep wave crests in a reasonably consistent way.
Yankun Gong, Xueen Chen, Jiexin Xu, Jieshuo Xie, Zhiwu Chen, Yinghui He, and Shuqun Cai
Geosci. Model Dev., 16, 2851–2871, https://doi.org/10.5194/gmd-16-2851-2023, https://doi.org/10.5194/gmd-16-2851-2023, 2023
Short summary
Short summary
Internal solitary waves (ISWs) play crucial roles in mass transport and ocean mixing in the northern South China Sea. Massive numerical investigations have been conducted in this region, but there was no systematic evaluation of a three-dimensional model about precisely simulating ISWs. Here, an ISW forecasting model is employed to evaluate the roles of resolution, tidal forcing and stratification in accurately reproducing wave properties via comparison to field and remote-sensing observations.
Jilian Xiong and Parker MacCready
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-45, https://doi.org/10.5194/gmd-2023-45, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
A new offline particle tracking model, Tracker, was introduced to work with the Regional Ocean Modeling System (ROMS). Its performance was compared with four other particle tracking models and passive dye, which span a representative range of tracking algorithms. All tracking models perform similarly, especially for the first day. The comparison of multiple tracking codes in the same circulation model establishes confidence in all, and allows comparison of performance and ease of use.
Johannes Bieser, David J. Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Soerensen, and Corinna Schrum
Geosci. Model Dev., 16, 2649–2688, https://doi.org/10.5194/gmd-16-2649-2023, https://doi.org/10.5194/gmd-16-2649-2023, 2023
Short summary
Short summary
MERCY is a 3D model to study mercury (Hg) cycling in the ocean. Hg is a highly harmful pollutant regulated by the UN Minamata Convention on Mercury due to widespread human emissions. These emissions eventually reach the oceans, where Hg transforms into the even more toxic and bioaccumulative pollutant methylmercury. MERCY predicts the fate of Hg in the ocean and its buildup in the food chain. It is the first model to consider Hg accumulation in fish, a major source of Hg exposure for humans.
Y. Joseph Zhang, Tomas Fernandez-Montblanc, William Pringle, Hao-Cheng Yu, Linlin Cui, and Saeed Moghimi
Geosci. Model Dev., 16, 2565–2581, https://doi.org/10.5194/gmd-16-2565-2023, https://doi.org/10.5194/gmd-16-2565-2023, 2023
Short summary
Short summary
Simulating global ocean from deep basins to coastal areas is a daunting task but is important for disaster mitigation efforts. We present a new 3D global ocean model on flexible mesh to study both tidal and nontidal processes and total water prediction. We demonstrate the potential for
seamlesssimulation, on a single mesh, from the global ocean to a few estuaries along the US West Coast. The model can serve as the backbone of a global tide surge and compound flooding forecasting framework.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
Short summary
Short summary
Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Manuel Aghito, Loris Calgaro, Knut-Frode Dagestad, Christian Ferrarin, Antonio Marcomini, Øyvind Breivik, and Lars Robert Hole
Geosci. Model Dev., 16, 2477–2494, https://doi.org/10.5194/gmd-16-2477-2023, https://doi.org/10.5194/gmd-16-2477-2023, 2023
Short summary
Short summary
The newly developed ChemicalDrift model can simulate the transport and fate of chemicals in the ocean and in coastal regions. The model combines ocean physics, including transport due to currents, turbulence due to surface winds and the sinking of particles to the sea floor, with ocean chemistry, such as the partitioning, the degradation and the evaporation of chemicals. The model will be utilized for risk assessment of ocean and sea-floor contamination from pollutants emitted from shipping.
Nieves G. Valiente, Andrew Saulter, Breogan Gomez, Christopher Bunney, Jian-Guo Li, Tamzin Palmer, and Christine Pequignet
Geosci. Model Dev., 16, 2515–2538, https://doi.org/10.5194/gmd-16-2515-2023, https://doi.org/10.5194/gmd-16-2515-2023, 2023
Short summary
Short summary
We document the Met Office operational global and regional wave models which provide wave forecasts up to 7 d ahead. Our models present coarser resolution offshore to higher resolution near the coastline. The increased resolution led to replication of the extremes but to some overestimation during modal conditions. If currents are included, wave directions and long period swells near the coast are significantly improved. New developments focus on the optimisation of the models with resolution.
Maxime Beauchamp, Quentin Febvre, Hugo Georgenthum, and Ronan Fablet
Geosci. Model Dev., 16, 2119–2147, https://doi.org/10.5194/gmd-16-2119-2023, https://doi.org/10.5194/gmd-16-2119-2023, 2023
Short summary
Short summary
4DVarNet is a learning-based method based on traditional data assimilation (DA). This new class of algorithms can be used to provide efficient reconstructions of a dynamical system based on single observations. We provide a 4DVarNet application to sea surface height reconstructions based on nadir and future Surface Water and Ocean and Topography data. It outperforms other methods, from optimal interpolation to sophisticated DA algorithms. This work is part of on-going AI Chair Oceanix projects.
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev., 16, 1755–1777, https://doi.org/10.5194/gmd-16-1755-2023, https://doi.org/10.5194/gmd-16-1755-2023, 2023
Short summary
Short summary
A new global surface-wave–tide–circulation coupled ocean model (FIO-COM32) with a resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are shown to be important contributors to the significant improvements in FIO-COM32 simulations. It is time to merge these separated model components (surface waves, tidal currents and ocean circulation) and start a new generation of ocean model development.
Jeff Polton, James Harle, Jason Holt, Anna Katavouta, Dale Partridge, Jenny Jardine, Sarah Wakelin, Julia Rulent, Anthony Wise, Katherine Hutchinson, David Byrne, Diego Bruciaferri, Enda O'Dea, Michela De Dominicis, Pierre Mathiot, Andrew Coward, Andrew Yool, Julien Palmiéri, Gennadi Lessin, Claudia Gabriela Mayorga-Adame, Valérie Le Guennec, Alex Arnold, and Clément Rousset
Geosci. Model Dev., 16, 1481–1510, https://doi.org/10.5194/gmd-16-1481-2023, https://doi.org/10.5194/gmd-16-1481-2023, 2023
Short summary
Short summary
The aim is to increase the capacity of the modelling community to respond to societally important questions that require ocean modelling. The concept of reproducibility for regional ocean modelling is developed: advocating methods for reproducible workflows and standardised methods of assessment. Then, targeting the NEMO framework, we give practical advice and worked examples, highlighting key considerations that will the expedite development cycle and upskill the user community.
Nairita Pal, Kristin N. Barton, Mark R. Petersen, Steven R. Brus, Darren Engwirda, Brian K. Arbic, Andrew F. Roberts, Joannes J. Westerink, and Damrongsak Wirasaet
Geosci. Model Dev., 16, 1297–1314, https://doi.org/10.5194/gmd-16-1297-2023, https://doi.org/10.5194/gmd-16-1297-2023, 2023
Short summary
Short summary
Understanding tides is essential to accurately predict ocean currents. Over the next several decades coastal processes such as flooding and erosion will be severely impacted due to climate change. Tides affect currents along the coastal regions the most. In this paper we show the results of implementing tides in a global ocean model known as MPAS–Ocean. We also show how Antarctic ice shelf cavities affect global tides. Our work points towards future research with tide–ice interactions.
Sébastien Petton, Valérie Garnier, Matthieu Caillaud, Laurent Debreu, and Franck Dumas
Geosci. Model Dev., 16, 1191–1211, https://doi.org/10.5194/gmd-16-1191-2023, https://doi.org/10.5194/gmd-16-1191-2023, 2023
Short summary
Short summary
The nesting AGRIF library is implemented in the MARS3D hydrodynamic model, a semi-implicit, free-surface numerical model which uses a time scheme as an alternating-direction implicit (ADI) algorithm. Two applications at the regional and coastal scale are introduced. We compare the two-nesting approach to the classic offline one-way approach, based on an in situ dataset. This method is an efficient means to significantly improve the physical hydrodynamics and unravel ecological challenges.
Noam S. Vogt-Vincent and Helen L. Johnson
Geosci. Model Dev., 16, 1163–1178, https://doi.org/10.5194/gmd-16-1163-2023, https://doi.org/10.5194/gmd-16-1163-2023, 2023
Short summary
Short summary
Ocean currents transport things over large distances across the ocean surface. Predicting this transport is key for tackling many environmental problems, such as marine plastic pollution and coral reef resilience. However, doing this requires a good understanding ocean currents, which is currently lacking. Here, we present and validate state-of-the-art simulations for surface currents in the southwestern Indian Ocean, which will support future marine dispersal studies across this region.
Pengyang Song, Dmitry Sidorenko, Patrick Scholz, Maik Thomas, and Gerrit Lohmann
Geosci. Model Dev., 16, 383–405, https://doi.org/10.5194/gmd-16-383-2023, https://doi.org/10.5194/gmd-16-383-2023, 2023
Short summary
Short summary
Tides have essential effects on the ocean and climate. Most previous research applies parameterised tidal mixing to discuss their effects in models. By comparing the effect of a tidal mixing parameterisation and tidal forcing on the ocean state, we assess the advantages and disadvantages of the two methods. Our results show that tidal mixing in the North Pacific Ocean strongly affects the global thermohaline circulation. We also list some effects that are not considered in the parameterisation.
Marko Rus, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev., 16, 271–288, https://doi.org/10.5194/gmd-16-271-2023, https://doi.org/10.5194/gmd-16-271-2023, 2023
Short summary
Short summary
We propose a new fast and reliable deep-learning architecture HIDRA2 for sea level and storm surge modeling. HIDRA2 features new feature encoders and a fusion-regression block. We test HIDRA2 on Adriatic storm surges, which depend on an interaction between tides and seiches. We demonstrate that HIDRA2 learns to effectively mimic the timing and amplitude of Adriatic seiches. This is essential for reliable HIDRA2 predictions of total storm surge sea levels.
Joao Marcos Azevedo Correia de Souza, Sutara H. Suanda, Phellipe P. Couto, Robert O. Smith, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 211–231, https://doi.org/10.5194/gmd-16-211-2023, https://doi.org/10.5194/gmd-16-211-2023, 2023
Short summary
Short summary
The current paper describes the configuration and evaluation of the Moana Ocean Hindcast, a > 25-year simulation of the ocean state around New Zealand using the Regional Ocean Modeling System v3.9. This is the first open-access, long-term, continuous, realistic ocean simulation for this region and provides information for improving the understanding of the ocean processes that affect the New Zealand exclusive economic zone.
Hao Huang, Pengyang Song, Shi Qiu, Jiaqi Guo, and Xueen Chen
Geosci. Model Dev., 16, 109–133, https://doi.org/10.5194/gmd-16-109-2023, https://doi.org/10.5194/gmd-16-109-2023, 2023
Short summary
Short summary
The Oceanic Regional Circulation and Tide Model (ORCTM) is developed to reproduce internal solitary wave dynamics. The three-dimensional nonlinear momentum equations are involved with the nonhydrostatic pressure obtained via solving the Poisson equation. The validation experimental results agree with the internal wave theories and observations, demonstrating that the ORCTM can successfully describe the life cycle of nonlinear internal solitary waves under different oceanic environments.
David E. Gwyther, Shane R. Keating, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 157–178, https://doi.org/10.5194/gmd-16-157-2023, https://doi.org/10.5194/gmd-16-157-2023, 2023
Short summary
Short summary
Ocean eddies are important for weather, climate, biology, navigation, and search and rescue. Since eddies change rapidly, models that incorporate or assimilate observations are required to produce accurate eddy timings and locations, yet the model accuracy is rarely assessed below the surface. We use a unique type of ocean model experiment to assess three-dimensional eddy structure in the East Australian Current and explore two pathways in which this subsurface structure is being degraded.
Shun Ohishi, Takemasa Miyoshi, and Misako Kachi
Geosci. Model Dev., 15, 9057–9073, https://doi.org/10.5194/gmd-15-9057-2022, https://doi.org/10.5194/gmd-15-9057-2022, 2022
Short summary
Short summary
An adaptive observation error inflation (AOEI) method was proposed for atmospheric data assimilation to mitigate erroneous analysis updates caused by large observation-minus-forecast differences for satellite brightness temperature around clear- and cloudy-sky boundaries. This study implemented the AOEI with an ocean data assimilation system, leading to an improvement of analysis accuracy and dynamical balance around the frontal regions with large meridional temperature differences.
Diego Bruciaferri, Marina Tonani, Isabella Ascione, Fahad Al Senafi, Enda O'Dea, Helene T. Hewitt, and Andrew Saulter
Geosci. Model Dev., 15, 8705–8730, https://doi.org/10.5194/gmd-15-8705-2022, https://doi.org/10.5194/gmd-15-8705-2022, 2022
Short summary
Short summary
More accurate predictions of the Gulf's ocean dynamics are needed. We investigate the impact on the predictive skills of a numerical shelf sea model of the Gulf after changing a few key aspects. Increasing the lateral and vertical resolution and optimising the vertical coordinate system to best represent the leading physical processes at stake significantly improve the accuracy of the simulated dynamics. Additional work may be needed to get real benefit from using a more realistic bathymetry.
Matthias Gröger, Manja Placke, H. E. Markus Meier, Florian Börgel, Sandra-Esther Brunnabend, Cyril Dutheil, Ulf Gräwe, Magnus Hieronymus, Thomas Neumann, Hagen Radtke, Semjon Schimanke, Jian Su, and Germo Väli
Geosci. Model Dev., 15, 8613–8638, https://doi.org/10.5194/gmd-15-8613-2022, https://doi.org/10.5194/gmd-15-8613-2022, 2022
Short summary
Short summary
Comparisons of oceanographic climate data from different models often suffer from different model setups, forcing fields, and output of variables. This paper provides a protocol to harmonize these elements to set up multidecadal simulations for the Baltic Sea, a marginal sea in Europe. First results are shown from six different model simulations from four different model platforms. Topical studies for upwelling, marine heat waves, and stratification are also assessed.
Shun Ohishi, Tsutomu Hihara, Hidenori Aiki, Joji Ishizaka, Yasumasa Miyazawa, Misako Kachi, and Takemasa Miyoshi
Geosci. Model Dev., 15, 8395–8410, https://doi.org/10.5194/gmd-15-8395-2022, https://doi.org/10.5194/gmd-15-8395-2022, 2022
Short summary
Short summary
We develop an ensemble-Kalman-filter-based regional ocean data assimilation system in which satellite and in situ observations are assimilated at a daily frequency. We find the best setting for dynamical balance and accuracy based on sensitivity experiments focused on how to inflate the ensemble spread and how to apply the analysis update to the model evolution. This study has a broader impact on more general data assimilation systems in which the initial shocks are a significant issue.
Cited articles
Ajayi, A., Le Sommer, J., Chassignet, E., Molines, J.-M., Xu, X., Albert, A.,
and Cosme, E.: Spatial and temporal variability of the North Atlantic eddy
field from two kilometric-resolution ocean models, J. Geophy. Res.-Oceans,
125, e2019JC015827, https://doi.org/10.1029/2019JC015827, 2020.
Bamber, J. L., Tedstone, A. J., King, M. D., Howat, I. M., Enderlin, E. M.,
van den Broeke, M. R., and Noel, B.: Land ice freshwater budget of the Arctic and North Atlantic Oceans: 1. Data, methods, and results, J. Geophys. Res.-Oceans, 123, 1827–1837, https://doi.org/10.1002/2017JC013605, 2018.
Bamber, J., van den Broeke, M., Ettema, J., Lenaerts, J., and Rignot, E.:
Recent large increases in freshwater fluxes from Greenland into the North
Atlantic, Geophys. Res. Lett., 39, L19501, https://doi.org/10.1029/2012GL052552, 2012.
Banzon, V. F., Reynolds, R. W., Stokes, D., and Xue, Y.: A 1/4∘
spatial-resolution daily sea surface temperature climatology
based on a blended satellite and in situ analysis, J. Climate, 27, 8221–8228,
https://doi.org/10.1175/JCLI-D-14-00293.1, 2014.
Bao, Q., Lin, P., Zhou, T., Liu, Y., Yu, Y., Wu, G., He, B., He, J., Li, L.,
Li, J., Li, Y., Liu, H., Qiao, F., Song, Z., Wang, B., Wang, J., Wang, P.,
Wang, X., Wang, Z., Wu, B., Wu, T., Xu, Y., Yu, H., Zhao, W., Zheng, W., and
Zhou, L.: The Flexible Global Ocean-Atmosphere-Land system model, Spectral
Version 2: FGOALS-s2, Adv. Atmos. Sci., 30, 561–576,
https://doi.org/10.1007/s00376-012-2113-9, 2013.
Baringer, M. O. and Garzoli, S. L.: Meridional heat transport determined
with expendable bathythermographs-Part I: Error estimates from model and
hydrographic data, Deep-Sea Res. Pt. I, 54, 1390–1401,
https://doi.org/10.1016/j.dsr.2007.03.011, 2007.
Bateson, A. W., Feltham, D. L., Schröder, D., Hosekova, L., Ridley, J. K., and Aksenov, Y.: Impact of sea ice floe size distribution on seasonal fragmentation and melt of Arctic sea ice, The Cryosphere, 14, 403–428, https://doi.org/10.5194/tc-14-403-2020, 2020.
Bleck, R.: An oceanic general circulation model framed in hybrid
isopycnic-Cartesian coordinates, Ocean Model., 4, 55–88,
https://doi.org/10.1016/S1463-5003(01)00012-9, 2002.
Böning, C. W., Scheinert, M., Dengg, J., Biastoch, A., and Funk, A.:
Decadal variability of subpolar gyre transport and its reverberation in the
North Atlantic overturning, Geophys. Res. Lett., 33, L21S01,
https://doi.org/10.1029/2006GL026906, 2006.
Bryan, F. O., Tomas, R., Dennis, J. M., Chelton, D. B., Loeb, N. G., and
McClean, J. L.: Frontal Scale Air–Sea Interaction in High-Resolution
Coupled Climate Models, J. Climate, 23, 6277–6291,
https://doi.org/10.1175/2010JCLI3665.1, 2010.
Callies, J., Flierl, G., Ferrari, R., and Fox-Kemper, B.: The role of
mixed-layer instabilities in submesoscale turbulence, J. Fluid Mech., 788,
5–41, https://doi.org/10.1017/jfm.2015.700, 2016.
Canuto, V. M., Howard, A., Cheng, Y., and Dubovikov, M. S.: Ocean turbulence.
Part I: One-point closure model–momentum and heat vertical diffusivities,
J. Phys. Oceanogr., 31, 1413–1426,
https://doi.org/10.1175/1520-0485(2001)031<1413:OTPIOP>2.0.CO;2,
2001.
Canuto, V. M., Howard, A., Cheng, Y., and Dubovikov, M. S.: Ocean turbulence.
Part II: Vertical diffusivities of momentum, heat, salt, mass, and passive
scalars, J. Phys. Oceanogr., 32, 240–264,
https://doi.org/10.1175/1520-0485(2002)032<0240:OTPIVD>2.0.CO;2,
2002.
Carnes, M., Helber, R. W., Barron, C. N., and Dastugue, J. M.: Validation test report for GDEM4, Technical Report NRL, Stennis, MS, 66 pp., 2010.
Chassignet, E. P., Smith, L. T., Halliwell, G. R., and Bleck, R.: North
Atlantic simulations with the Hybrid Coordinate Ocean Model (HYCOM): Impact
of the vertical coordinate choice, reference pressure, and thermobaricity,
J. Phys. Oceanogr., 33, 2504–2526,
https://doi.org/10.1175/1520-0485(2003)033<2504:NASWTH>2.0.CO;2,
2003.
Chassignet, E. P. and Marshall, D. P.: Gulf Stream separation in numerical
ocean models, in: Geophysical Monograph Series, 177, 39–61, 2008.
Chassignet, E. P. and Xu, X.: Impact of horizontal resolution
(1/12∘ to 1/50∘) on Gulf Stream separation,
penetration, and variability, J. Phys. Oceanogr., 47, 1999–2021,
https://doi.org/10.1175/JPO-D-17-0031.1, 2017.
Chassignet, E. P., Yeager, S. G., Fox-Kemper, B., Bozec, A., Castruccio, F.,
Danabasoglu, G., Kim, W. M., Koldunov, N., Li, Y., Lin, P., Liu, H., Sein,
D., Sidorenko, D., Wang, Q., and Xu, X.: Impact of horizontal resolution on
the energetics of global ocean-sea-ice model simulations, CLIVAR
Variations/Exchanges, 18, 23–30, https://doi.org/10.5065/g8w0-fy32, 2020a.
Chassignet, E. P., Yeager, S. G., Fox-Kemper, B., Bozec, A., Castruccio,
F., Danabasoglu, G., Kim, W. M., Koldunov, N., Li, Y.,
Lin, P., Liu, H., Sein, D., Sidorenko, D., Wang, Q., and Xu, X.: Impact of horizontal resolution on global ocean-sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2) (Version v2.0) [Data set], Geoscientific Model Development, Zenodo, https://doi.org/10.5281/zenodo.3934822, 2020b.
Chidichimo, M. P., Donohue, K. A., Watts, D. R., and Tracey, K. L.:
Baroclinic transport time series of the Antarctic Circumpolar Current
measured in Drake Passage, J. Phys. Oceanogr., 44, 1829–1853,
https://doi.org/10.1175/JPO-D-13-071.1, 2014.
Craig, A. P., Vertenstein, M., and Jacob, R.: A new flexible coupler for
earth system modeling developed for CCSM4 and CESM1, Int. J. High Perform.
Comput. Appl., 26, 31–42, https://doi.org/10.1177/1094342011428141, 2012.
Cunningham, S. A.: Transport and variability of the Antarctic Circumpolar
Current in Drake Passage, J. Geophys. Res., 108, 8084,
https://doi.org/10.1029/2001JC001147, 2003.
Danabasoglu, G., Bates, S. C., Briegleb, B. P., Jayne, S. R., Jochum, M.,
Large, W. G., Peacock, S., and Yeager, S. G.: The CCSM4 Ocean Component, J. Climate, 25, 1361–1389, https://doi.org/10.1175/JCLI-D-11-00091.1, 2012.
Danabasoglu, G., Ferrari, R., and McWilliams, J. C.: Sensitivity of an ocean
general circulation model to a parameterization of near-surface eddy fluxes,
J. Climate, 21, 1192–1208, https://doi.org/10.1175/2007JCLI1508.1, 2008.
Danabasoglu, G., Large, W. G., and Briegleb, B. P.: Climate impacts of
parameterized Nordic Sea overflows, J. Geophys. Res., 115, C11005,
https://doi.org/10.1029/2010JC006243, 2010.
Danabasoglu, G. and Marshall, J.: Effects of vertical variations of
thickness diffusivity in an ocean general circulation model, Ocean Model.,
18, 122–141, https://doi.org/10.1016/j.ocemod.2007.03.006, 2007.
Danabasoglu, G., Yeager, S. G., Bailey, D., Behrens, E., Bentsen, M., Bi,
D., Biastoch, A., Böning, C., Bozec, A., Canuto, V. M., Cassou, C.,
Chassignet, E., Coward, A. C., Danilov, S., Diansky, N., Drange, H.,
Farneti, R., Fernandez, E., Fogli, P. G., Forget, G., Fujii, Y., Griffies,
S. M., Gusev, A., Heimbach, P., Howard, A., Jung, T., Kelley, M., Large, W.
G., Leboissetier, A., Lu, J., Madec, G., Marsland, S. J., Masina, S.,
Navarra, A., George Nurser, A. J., Pirani, A., y Mélia, D. S., Samuels,
B. L., Scheinert, M., Sidorenko, D., Treguier, A. M., Tsujino, H., Uotila,
P., Valcke, S., Voldoire, A., and Wang, Q.: North Atlantic simulations in
Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part I: Mean
states, Ocean Model., 73, 76–107, https://doi.org/10.1016/j.ocemod.2013.10.005, 2014.
Danabasoglu, G., Yeager, S. G., Kim, W. M., Behrens, E., Bentsen, M., Bi,
D., Biastoch, A., Bleck, R., Böning, C., Bozec, A., Canuto, V. M.,
Cassou, C., Chassignet, E., Coward, A. C., Danilov, S., Diansky, N., Drange,
H., Farneti, R., Fernandez, E., Fogli, P. G., Forget, G., Fujii, Y.,
Griffies, S. M., Gusev, A., Heimbach, P., Howard, A., Ilicak, M., Jung, T.,
Karspeck, A. R., Kelley, M., Large, W. G., Leboissetier, A., Lu, J., Madec,
G., Marsland, S. J., Masina, S., Navarra, A., Nurser, A. J. G., Pirani, A.,
Romanou, A., David, S. y. M., Samuels, B. L., Scheinert, M., Sidorenko, D.,
Sun, S., Treguier, A. M., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A.,
Wang, Q., and Yashayaev, I.: North Atlantic simulations in Coordinated
Ocean-ice Reference Experiments phase II (CORE-II). Part II: Inter-annual to
decadal variability, Ocean Model., 97, 65–90,
https://doi.org/10.1016/j.ocemod.2015.11.007, 2016.
Danabasoglu, G., Lamarque, J. -F., Bachmeister, J., Bailey, D. A., DuVivier, A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A., Hannay, C., Holland, M. M., Large, W. G., Lawrence, D. M., Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R., Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S., van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C., Fischer, C., Fox-Kember, B., Kay, J. E., Kinnison, D., Kushner, P. J., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L., Rasch, P. J., and Strand, W. G.: The Community Earth System Model version 2 (CESM2), J. Adv. Model. Earth Sys., 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020.
Danilov, S., Wang, Q., Timmermann, R., Iakovlev, N., Sidorenko, D., Kimmritz, M., Jung, T., and Schröter, J.: Finite-Element Sea Ice Model (FESIM), version 2, Geosci. Model Dev., 8, 1747–1761, https://doi.org/10.5194/gmd-8-1747-2015, 2015.
Danilov, S., Kivman, G., and Schröter, J.: A finite-element ocean model:
Principles and evaluation, Ocean Model., 6, 125–150,
https://doi.org/10.1016/S1463-5003(02)00063-X, 2004.
Depoorter, M. A., Bamber, J. L., Griggs, J. A., Lenaerts, J. T. M.,
Ligtenberg, S. R. M., Van Den Broeke, M. R., and Moholdt, G.: Calving fluxes
and basal melt rates of Antarctic ice shelves, Nature, 502, 89–92,
https://doi.org/10.1038/nature12567, 2013.
Dong, S., Baringer, M. O., Goni, G. J., Meinen, C. S., and Garzoli, S. L.:
Seasonal variations in the South Atlantic Meridional Overturning Circulation
from observations and numerical models, Geophys. Res. Lett., 41,
4611–4618, https://doi.org/10.1002/2014GL060428, 2014.
Dong, S., Garzoli, S., Baringer, M., Meinen, C., and Goni, G.: Interannual
variations in the Atlantic meridional overturning circulation and its
relationship with the net northward heat transport in the South Atlantic,
Geophys. Res. Lett., 36, L20606, https://doi.org/10.1029/2009GL039356, 2009.
Dong, S., Goni, G., and Bringas, F.: Temporal variability of the South
Atlantic Meridional Overturning Circulation between 20∘ S and
35∘ S, Geophys. Res. Lett., 42, 7655–7662,
https://doi.org/10.1002/2015GL065603, 2015.
Donohue, K. A., Tracey, K. L., Watts, D. R., Chidichimo, M. P., and
Chereskin, T. K.: Mean Antarctic Circumpolar Current transport measured in
Drake Passage, Geophys. Res. Lett., 43, 11760–11767,
https://doi.org/10.1002/2016GL070319, 2016.
Downes, S. M., Farneti, R., Uotila, P., Griffies, S. M., Marsland, S. J.,
Bailey, D., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, C.,
Bozec, A., Canuto, V. M., Chassignet, E., Danabasoglu, G., Danilov, S.,
Diansky, N., Drange, H., Fogli, P. G., Gusev, A., Howard, A., Ilicak, M.,
Jung, T., Kelley, M., Large, W. G., Leboissetier, A., Long, M., Lu, J.,
Masina, S., Mishra, A., Navarra, A., George Nurser, A. J., Patara, L.,
Samuels, B. L., Sidorenko, D., Spence, P., Tsujino, H., Wang, Q., and Yeager,
S. G.: An assessment of Southern Ocean water masses and sea ice during
1988-2007 in a suite of interannual CORE-II simulations, Ocean Model., 94,
67–94, https://doi.org/10.1016/j.ocemod.2015.07.022, 2015.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Farneti, R., Downes, S. M., Griffies, S. M., Marsland, S. J., Behrens, E.,
Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Canuto, V. M.,
Chassignet, E., Danabasoglu, G., Danilov, S., Diansky, N., Drange, H.,
Fogli, P. G., Gusev, A., Hallberg, R. W., Howard, A., Ilicak, M., Jung, T.,
Kelley, M., Large, W. G., Leboissetier, A., Long, M., Lu, J., Masina, S.,
Mishra, A., Navarra, A., George Nurser, A. J., Patara, L., Samuels, B. L.,
Sidorenko, D., Tsujino, H., Uotila, P., Wang, Q., and Yeager, S. G.: An
assessment of Antarctic Circumpolar Current and Southern Ocean meridional
overturning circulation during 1958–2007 in a suite of interannual CORE-II
simulations, Ocean Model., 93, 84–120, https://doi.org/10.1016/j.ocemod.2015.07.009,
2015.
Ferrari, R., McWilliams, J. C., Canuto, V. M., and Dubovikov, M.:
Parameterization of eddy fluxes near oceanic boundaries, J. Climate, 21,
2770–2789, https://doi.org/10.1175/2007JCLI1510.1, 2008.
Ferreira, D., Marshall, J., and Heimbach, P.: Estimating eddy
stresses by fitting dynamics to observations using a residual-mean ocean circulation model and its adjoint, J. Phys. Oceanogr., 35, 1891–1910,
https://doi.org/10.1175/JPO2785.1, 2005.
Fetterer, F., Knowles, K., Meier, W., Savoie, M., and Windnagel, A. K.: Sea
Ice Index, Version 3, Boulder, CO, USA, 2017.
Firing, Y. L., Chereskin,
T. K., and Mazloff, M. R.: Vertical structure and transport of the Antarctic
Circumpolar Current in Drake Passage from direct velocity observations, J.
Geophys. Res., 116, C08015, https://doi.org/10.1029/2011JC006999, 2011.
Fox-Kemper, B., Danabasoglu, G., Ferrari, R., Griffies, S. M., Hallberg, R.
W., Holland, M. M., Maltrud, M. E., Peacock, S., and Samuels, B. L.:
Parameterization of mixed layer eddies. III: Implementation and impact in
global ocean climate simulations, Ocean Model., 39, 61–78,
https://doi.org/10.1016/j.ocemod.2010.09.002, 2011.
Fox-Kemper, B., Adcroft, A., Böning, C. W., Chassignet, E. P.,
Curchitser, E., Danabasoglu, G., Eden, C., England, M. H., Gerdes, R.,
Greatbatch, R. J., Griffies, S. M., Hallberg, R. W., Hanert, E., Heimbach,
P., Hewitt, H. T., Hill, C. N., Komuro, Y., Legg, S., Sommer, J. Le, Masina,
S., Marsland, S. J., Penny, S. G., Qiao, F., Ringler, T. D., Treguier, A.
M., Tsujino, H., Uotila, P., and Yeager, S. G.: Challenges and prospects in
ocean circulation models, Front. Mar. Sci., 6, 65,
https://doi.org/10.3389/fmars.2019.00065, 2019.
Fox-Kemper, B., Ferrari, R., and Hallberg, R.: Parameterization of mixed
layer eddies. Part I: Theory and diagnosis, J. Phys. Oceanogr., 38,
1145–1165, https://doi.org/10.1175/2007JPO3792.1, 2008.
Garzoli, S. L., Baringer, M. O., Dong, S., Perez, R. C., and Yao, Q.: South Atlantic meridional fluxes, Deep-Sea Res. Pt. I, 71, 21–32, https://doi.org/10.1016/j.dsr.2012.09.003, 2013.
Gent, P. R. and Danabasoglu, G.: Response to increasing southern hemisphere
winds in CCSM4, J. Climate, 24, 4992–4998, https://doi.org/10.1175/JCLI-D-10-05011.1,
2011.
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.
Godfrey, J. S.: A Sverdrup model of the depth-integrated flow for the world
ocean allowing for island circulations, Geophys. Astrophys. Fluid Dyn.,
45, 89–112, https://doi.org/10.1080/03091928908208894, 1989.
Goes, M., Goni, G., and Dong, S.: An optimal XBT-based monitoring system for
the South Atlantic meridional overturning circulation at 34∘ S, J.
Geophys. Res.-Oceans, 120, 161–181, https://doi.org/10.1002/2014JC010202, 2015.
Good, S. A., Martin, M. J., and Rayner, N. A.: EN4: Quality controlled ocean
temperature and salinity profiles and monthly objective analyses with
uncertainty estimates, J. Geophys. Res.-Oceans, 118, 6704–6716,
https://doi.org/10.1002/2013JC009067, 2013.
Gordon, A. L., Sprintall, J., Van Aken, H. M., Susanto, R. D., Wijffels, S.,
Molcard, R., Ffield, A., Pranowo, W., and Wirasantosa, S.: The Indonesian
throughflow during 2004–2006 as observed by the INSTANT program, Dyn. Atmos.
Ocean., 50, 115–128, https://doi.org/10.1016/j.dynatmoce.2009.12.002, 2010.
Gordon, A. L.: Oceanography of the Indonesian seas and their throughflow,
Oceanography, 18, 15–27, https://doi.org/10.5670/oceanog.2005.01,
2005.
Gordon, A. L.: Interocean exchange of thermocline water, J. Geophys.
Res., 91, 5037, https://doi.org/10.1029/jc091ic04p05037, 1986.
Gregory, J. M., Griffies, S. M., Hughes, C. W., Lowe, J. A., Church, J. A.,
Fukimori, I., Gomez, N., Kopp, R. E., Landerer, F., Cozannet, G. Le, Ponte,
R. M., Stammer, D., Tamisiea, M. E., and van de Wal, R. S. W.: Concepts and terminology for sea level:
Mean, variability and change, both local and global, Surv. Geophys., 40, 1251–1289, https://doi.org/10.1007/s10712-019-09525-z,
2019.
Griffies, S. M.: The Gent–McWilliams Skew Flux, J. Phys. Oceanogr., 28,
831–841, https://doi.org/10.1175/1520-0485(1998)028<0831:TGMSF>2.0.CO;2, 1998.
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. Sen, Severijns, C. A., Simmons, H. L.,
Treguier, A. M., Winton, M., Yeager, S., and Yin, J.: Coordinated Ocean-ice
Reference Experiments (COREs), Ocean Model., 26, 1–46,
https://doi.org/10.1016/j.ocemod.2008.08.007, 2009.
Griffies, S. M., Yin, J., Durack, P. J., Goddard, P., Bates, S. C., Behrens,
E., Bentsen, M., Bi, D., Biastoch, A., Böning, C. W., Bozec, A.,
Chassignet, E., Danabasoglu, G., Danilov, S., Domingues, C. M., Drange, H.,
Farneti, R., Fernandez, E., Greatbatch, R. J., Holland, D. M., Ilicak, M.,
Large, W. G., Lorbacher, K., Lu, J., Marsland, S. J., Mishra, A., George
Nurser, A. J., Salas y Mélia, D., Palter, J. B., Samuels, B. L.,
Schröter, J., Schwarzkopf, F. U., Sidorenko, D., Treguier, A. M., Tseng,
Y. heng, Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., Wang, Q.,
Winton, M., and Zhang, X.: An assessment of global and regional sea level for
years 1993–2007 in a suite of interannual CORE-II simulations, Ocean Model.,
78, 35–89, https://doi.org/10.1016/j.ocemod.2014.03.004, 2014.
Griffies, S. M., Winton, M., Anderson, W. G., Benson, R., Delworth, T. L.,
Dufour, C. O., Dunne, J. P., Goddard, P., Morrison, A. K., Rosati, A.,
Wittenberg, A. T., Yin, J. J., and Zhang, R.: Impacts on ocean heat from transient mesoscale eddies in a hierarchy of climate models, J. Climate, 28,
952–977, 2015.
Griffies, S. M., Danabasoglu, G., Durack, P. J., Adcroft, A. J., Balaji, V., Böning, C. W., Chassignet, E. P., Curchitser, E., Deshayes, J., Drange, H., Fox-Kemper, B., Gleckler, P. J., Gregory, J. M., Haak, H., Hallberg, R. W., Heimbach, P., Hewitt, H. T., Holland, D. M., Ilyina, T., Jungclaus, J. H., Komuro, Y., Krasting, J. P., Large, W. G., Marsland, S. J., Masina, S., McDougall, T. J., Nurser, A. J. G., Orr, J. C., Pirani, A., Qiao, F., Stouffer, R. J., Taylor, K. E., Treguier, A. M., Tsujino, H., Uotila, P., Valdivieso, M., Wang, Q., Winton, M., and Yeager, S. G.: OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project, Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, 2016.
Haarsma, R. J., Roberts, M. J., Vidale, P. L., Senior, C. A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N. S., Guemas, V., von Hardenberg, J., Hazeleger, W., Kodama, C., Koenigk, T., Leung, L. R., Lu, J., Luo, J.-J., Mao, J., Mizielinski, M. S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., Small, J., and von Storch, J.-S.: High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6, Geosci. Model Dev., 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, 2016.
Häkkinen, S. and Rhines, P. B.: Decline of Subpolar North Atlantic
Circulation during the 1990s, Science, 304, 555–559,
https://doi.org/10.1126/science.1094917, 2004.
Hallberg, R.: Using a resolution function to regulate parameterizations of
oceanic mesoscale eddy effects, Ocean Model., 72, 92–103,
https://doi.org/10.1016/j.ocemod.2013.08.007, 2013.
Hallberg, R. and Gnanadesikan, A.: The role of Eddies in determining the
structure and response of the wind-driven Southern hemisphere overturning:
Results from the Modeling Eddies in the Southern Ocean (MESO) project, J.
Phys. Oceanogr., 36, 2232–2252, https://doi.org/10.1175/JPO2980.1, 2006.
Halliwell, G. R.: Evaluation of vertical coordinate and vertical mixing
algorithms in the HYbrid-Coordinate Ocean Model (HYCOM), Ocean Model.,
7, 285–322, https://doi.org/10.1016/j.ocemod.2003.10.002, 2004.
Hirschi, J. J.-M., Barnier, B., Böning, C., Biastoch, A., Blaker, A. T.,
Coward, A., Danilov, S., Drijfhout, S., Getzlaff, K., Griffies, S. M.,
Hasumi, H., Hewitt, H., Iovino, D., Kawasaki, T., Kiss, A. E., Koldunov, N.,
Marzocchi, A., Moat, B., Molines, J.-M., Myers, P. G., Penduff, T., Roberts,
M., Treguier, A.-M., Sein, D. V., Sidorenko, D., Small1, J., Spence, P.,
Thompson, L., Weijer, W., and Xu, X.: The Atlantic meridional overturning
circulation in high resolution models, J. Geophys. Res.-Oceans, 125, e2019JC015522, https://doi.org/10.1029/2019JC015522, 2020.
Horvat, C. and Tziperman, E.: A prognostic model of the sea-ice floe size and thickness distribution, The Cryosphere, 9, 2119–2134, https://doi.org/10.5194/tc-9-2119-2015, 2015.
Horvat, C., Blanchard-Wrigglesworth, E., and Petty, A.: Observing waves in
sea ice with ICESat-2, Geophys, Res. Lett., 47, e2020GL087629, https://doi.org/10.1029/2020GL087629, 2020.
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 Lipscomb, W. H.: CICE: the Los Alamos sea ice model, documentation and software user's manual, Version 4.1. Los Alamos, NM, Los Alamos National Laboratory, Tech. Rep. LA-CC-06-012, 2010.
Hunke, E. C., Lipscomb, W. H., Turner, A. K., Jeffery, N., and Elliott, S.:
CICE: the Los Alamos Sea Ice Model Documentation and Software User's Manual
Version 4.1 LA-CC-06-012, 2010.
Hunke, E. C., Hebert, D. A., and Lecomte, O.: Level-ice melt ponds in the Los
Alamos sea ice model, CICE, Ocean Model., 71, 26–42,
https://doi.org/10.1016/j.ocemod.2012.11.008, 2013.
Hunke, E. C., Lipscomb, W. H., Turner, A. K., Jeffery, N., and Elliott, S.:
CICE: the Los Alamos Sea Ice Model documentation and software user's manual,
Version 5.1, LA-CC-06-012, T-3 Fluid Dyn. Group, Los Alamos Natl. Lab., 116,
2015.
Ilicak, M., Drange, H., Wang, Q., Gerdes, R., Aksenov, Y., Bailey, D.,
Bentsen, M., Biastoch, A., Bozec, A., Böning, C., Cassou, C.,
Chassignet, E., Coward, A. C., Curry, B., Danabasoglu, G., Danilov, S.,
Fernandez, E., Fogli, P. G., Fujii, Y., Griffies, S. M., Iovino, D., Jahn,
A., Jung, T., Large, W. G., Lee, C., Lique, C., Lu, J., Masina, S., George
Nurser, A. J., Roth, C., Salas y Mélia, D., Samuels, B. L., Spence, P.,
Tsujino, H., Valcke, S., Voldoire, A., Wang, X., and Yeager, S. G.: An
assessment of the Arctic Ocean in a suite of interannual CORE-II
simulations. Part III: Hydrography and fluxes, Ocean Model., 100, 141–161,
https://doi.org/10.1016/j.ocemod.2016.02.004, 2016.
Jayne, S. R.: The Impact of Abyssal Mixing Parameterizations in an Ocean
General Circulation Model, J. Phys. Oceanogr., 39, 1756–1775,
https://doi.org/10.1175/2009JPO4085.1, 2009.
Jochum, M., Fox-Kemper, B., Molnar, P. H., and Shields, C.: Differences in
the Indonesian seaway in a coupled climate model and their relevance to
Pliocene climate and El Niño, Paleoceanography, 24, PA1212,
https://doi.org/10.1029/2008PA001678, 2009.
Johns, W. E., Baringer, M. O., Beal, L. M., Cunningham, S. A., Kanzow, T.,
Bryden, H. L., Hirschi, J. J. M., Marotzke, J., Meinen, C. S., Shaw, B., and
Curry, R.: Continuous, Array-Based Estimates of Atlantic Ocean Heat
Transport at 26.5∘ N, J. Climate, 24, 2429–2449,
https://doi.org/10.1175/2010JCLI3997.1, 2011.
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi,
K., Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., and Kiyotoshi, T.:
The JRA-55 reanalysis: General specifications and basic characteristics, J.
Meteorol. Soc. Jpn., 93, 5–48, https://doi.org/10.2151/jmsj.2015-001, 2015.
Koenig, Z., Provost, C., Ferrari, R., Sennéchael, N., and Rio, M.-H.:
Volume transport of the Antarctic Circumpolar Current: Production and
validation of a 20 year long time series obtained from in situ and satellite
observations, J. Geophys. Res.-Oceans, 119, 5407–5433,
https://doi.org/10.1002/2014jc009966, 2014.
Kohout, A., Williams, M., Dean, S., and Meylan, M. H.: Storm-induced sea-ice
breakup and the implications for ice extent, Nature, 509, 604–607,
https://doi.org/10.1038/nature13262, 2014.
Kurian, J., P., Li, P., Chang, P., Patricola, C. M., and Small, J.: Impact of
the Benguela coastal low-level jet on the Southeast Tropical Atlantic SST
bias in a regional ocean model, Clim. Dynam., in review, 2020.
Kurtz, N. T. and Markus, T.: Satellite observations of Antarctic sea ice thickness and volume, J. Geophys. Res., 117, C08025, https://doi.org/10.1029/2012JC008141, 2012.
Large, W. G. and Yeager, S. G.: Diurnal to decadal global forcing for ocean
and sea–ice models: The data sets and flux climatologies, NCAR Tech. Note,
TN–460+ST(May), 105 pp., https://doi.org/10.5065/D6KK98Q6, 2004.
Large, W. G., McWilliams, J. C., and Doney, S. C.: Oceanic vertical mixing: A
review and a model with a nonlocal boundary layer parameterization, Rev.
Geophys., 32, 363–403, https://doi.org/10.1029/94RG01872, 1994.
Large, W. G. and Yeager, S. G.: The global climatology of an interannually
varying air – Sea flux data set, Clim. Dynam., 33, 341–364,
https://doi.org/10.1007/s00382-008-0441-3, 2009.
Large, W. G., Danabasoglu, G., Doney, S. C., and McWilliams, J. C.:
Sensitivity to surface forcing and boundary layer mixing
in a global ocean model: Annual-mean climatology, J. Phys. Oceanogr., 27, 2418–2447,
https://doi.org/10.1175/1520-0485(1997)027<2418:STSFAB>2.0.CO;2,
1997.
Laurindo, L. C., Siqueira, L., Mariano, A. J., and Kirtman, B. P.:
Cross-spectral analysis of the SST/10-m wind speed coupling resolved by
satellite products and climate model simulations, Clim. Dynam., 52,
5071–5098, https://doi.org/10.1007/s00382-018-4434-6, 2019.
Li, L., Lin, P., Yu, Y., Wang, B., Zhou, T., Liu, L., Liu, J., Bao, Q., Xu,
S., Huang, W., Xia, K., Pu, Y., Dong, L., Shen, S., Liu, Y., Hu, N., Liu,
M., Sun, W., Shi, X., Zheng, W., Wu, B., Song, M., Liu, H., Zhang, X., Wu,
G., Xue, W., Huang, X., Yang, G., Song, Z., and Qiao, F.: The flexible global
ocean-atmosphere-land system model, Grid-point Version 2: FGOALS-g2, Adv.
Atmos. Sci., 30, 543–560, https://doi.org/10.1007/s00376-012-2140-6, 2013.
Li, Q., Webb, A., Fox-Kemper, B., Craig, A., Danabasoglu, G., Large, W. G.,
and Vertenstein, M.: Langmuir mixing effects on global climate: WAVEWATCH
III in CESM, Ocean Model., 103, 145–160, https://doi.org/10.1016/j.ocemod.2015.07.020,
2016.
Li, Y, Liu, H., Ding, M., Lin, P., Yu, Z., Yu, Y., Meng, Y., Li, Y., Jian,
X., Jiang, J., Chen, K., Yang, Q., Wang, Y., Zhao, B., Wei, J., Ma, J.,
Zheng, W., and Wang, P.: Eddy-resolving simulation of CAS-LICOM3 for the
Ocean Model Intercomparison Project phase 2 (OMIP-2), Adv. Atmos. Sci., 37, 1067–1080,
https://doi.org/10.1007/s00376-020-0057-z, 2020.
Lin, P., Liu, H., Xue, W., Li, H., Jiang, J., Song, M., Song, Y., Wang,
F., and Zhang, M.: A coupled experiment with LICOM2 as the ocean component of
CESM1, J. Meteorol. Res., 30, 76–92, https://doi.org/10.1007/s13351-015-5045-3,
2016.
Lin, P. F., Yu, Z., Liu, H., Yu, Y., Li, Y,Jiang, J., Xue, W., Chen, K., Yang, Q., Zhao, B., Wei, J., Ding, M., Sun, Z., Wang, Y., Meng, Y., Zheng, W., and Ma, J: LICOM model datasets for the CMIP6 Ocean model intercomparison project, Adv. Atmos. Sci., 37, 239-−249, https://doi.org/10.1007/s00376-019-9208-5, 2020.
Liu, H. L., Zhang, X. H., Li, W., Yu, Y. Q., and Yu, R. C.: An eddy-permitting
oceanic general circulation model and its preliminary evaluation, Adv.
Atmos. Sci., 21, 675–690, https://doi.org/10.1007/bf02916365, 2004.
Liu, H., Lin, P., Yu, Y., and Zhang, X.: The baseline evaluation of LASG/IAP
Climate system Ocean Model (LICOM) version 2, Acta Meteorol. Sin., 26,
318–329, https://doi.org/10.1007/s13351-012-0305-y, 2012.
Locarnini, R. A., Mishonov, A. V., Antonov, J. I., Boyer, T. P., Garcia, H.
E., Baranova, O. K., Zweng, M. M., Paver, C. R., Reagan, J. R., Johnson, D.
R., Hamilton, M., Seidov, D., and Levitus, S.: World Ocean Atlas 2013, Volume
1, Temperature, https://doi.org/10.7289/V55X26VD, 2013.
Lumpkin, R. and Speer, K.: Global Ocean Meridional Overturning, J. Phys.
Oceanogr., 37, 2550–2562, https://doi.org/10.1175/JPO3130.1, 2007.
Ma, X., Chang,
P., Saravanan, R., Montuoro, R., Nakamura, H., Wu, D., Lin, X., and Wu, L.:
Importance of resolving Kuroshio
front and eddy influence in simulating the North Pacific storm
track, J. Climate, 30, 1861–1880,
https://doi.org/10.1175/JCLI-D-16-0154.1, 2017.
Ma, X., Jing, Z., Chang, P., Liu, X., Montuoro, R., Small, R. J., Bryan, F.
O., Greatbatch, R. J., Brandt, P., Wu, D., Lin, X., and Wu, L.: Western
boundary currents regulated by interaction between ocean eddies and the
atmosphere, Nature, 535, 533–537, https://doi.org/10.1038/nature18640, 2016.
Maltrud, M. E. and McClean, J. L.: An eddy resolving global 1/10∘
ocean simulation, Ocean Model., 8, 31–54,
https://doi.org/10.1016/j.ocemod.2003.12.001, 2005.
McClean, J. L., Bader, D. C., Bryan, F. O., Maltrud, M. E., Dennis, J. M.,
Mirin, A. A., Jones, P. W., Kim, Y. Y., Ivanova, D. P., Vertenstein, M.,
Boyle, J. S., Jacob, R. L., Norton, N., Craig, A., and Worley, P. H.: A
prototype two-decade fully-coupled fine-resolution CCSM simulation, Ocean
Model., 39, 10–30, https://doi.org/10.1016/j.ocemod.2011.02.011, 2011.
Meinen, C. S., Speich, S., Perez, R. C., Dong, S., Piola, A. R., Garzoli, S.
L., Baringer, M. O., Gladyshev, S., and Campos, E. J. D.: Temporal
variability of the meridional overturning circulation at 34.5∘ S:
Results from two pilot boundary arrays in the South Atlantic, J. Geophys.
Res.-Oceans, 118, 6461–6478, https://doi.org/10.1002/2013JC009228, 2013.
Meinen, C. S., Speich, S., Piola, A. R., Ansorge, I., Campos, E.,
Kersalé, M., Terre, T., Chidichimo, M. P., Lamont, T., Sato, O. T.,
Perez, R. C., Valla, D., van den Berg, M., Le Hénaff, M., Dong, S., and
Garzoli, S. L.: Meridional overturning circulation transport variability at 34.5∘S during 2009–2017: Baroclinic and barotropic flows and the dueling influence of the boundaries, Geophys. Res. Lett., 45, 4180–4188,
https://doi.org/10.1029/2018GL077408, 2018.
Mesinger, F. and Janjic, Z. I.: Problems and numerical methods of the
incorporation of mountains in atmospheric models, Lect. Appl. Math., 22,
81–120, 1985.
Meyers, G.: Variation of Indonesian throughflow and the El Niño-Southern
Oscillation, J. Geophys. Res.-Oceans, 101,, 12255–12263,
https://doi.org/10.1029/95JC03729@10.1002/(ISSN)2169-9291.PACLLWBC1, 1996.
Morrison, A. K. and Hogg, A. McC.:On the relationship between Southern Ocean overturning and ACC transport, J. Phys. Oceanogr., 43, 140–148,
https://doi.org/10.1175/JPO-D-12-057.1, 2013.
Msadek, R., Johns, W. E., Yeager, S. G., Danabasoglu, G., Delworth, T. L.,
and Rosati, A.: The Atlantic Meridional Heat Transport at 26.5∘ N
and Its Relationship with the MOC in the RAPID Array and the GFDL and NCAR
Coupled Models, J. Climate, 26, 4335–4356, https://doi.org/10.1175/JCLI-D-12-00081.1,
2013.
Munday, D. R., Johnson, H. L., and Marshall, D. P.:Eddy saturation of equilibrated circumpolar currents, J. Phys. Oceanogr., 43, 507–532,
https://doi.org/10.1175/JPO-D-12-095.1, 2013.
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.
Notz, D., Dörr, J., Bailey, D. A., Blockley, E., Bushuk, M., Debernard,
J. B., Dekker, E., DeRepentigny, P., Docquier, D., Fuckar, N. S., Fyfe, J.
C., Jahn, A., Holland, M., Hunke, E., Iovino, D., Khosravi, N., Massonnet,
F., Madec, G., O'Farrell, S., Petty, A., Rana, A., Roach, L., Rosenblum, E.,
Rousset, C., Semmler, T., Stroeve, J., Tremblay, B., Toyoda, T., Tsujino, H.
and Vancoppenolle, M.: Arctic sea ice in CMIP6, Geophys. Res. Lett., 47,
e2019GL086749, https://doi.org/10.1029/2019GL086749, 2020.
Ollitrault, M. and Colin de Verdière, A.: The ocean general circulation
near 1000 m depth, J. Phys. Oceanogr., 44, 384–408,
https://doi.org/10.1175/JPO-D-13-030.1, 2014.
Olonscheck, D., Mauritsen, T., and Notz, D.: Arctic sea-ice variability is
primarily driven by atmospheric temperature fluctuations, Nat. Geosci.,
12, 430–434, https://doi.org/10.1038/s41561-019-0363-1, 2019.
Parkinson, C. L. and Washington, W. M.: Large-scale numerical model of sea
ice, J Geophys Res, 84, 311–337, https://doi.org/10.1029/jc084ic01p00311, 1979.
Pearson, B., Fox-Kemper, B., Bachman, S., and Bryan, F.: Evaluation of
scale-aware subgrid mesoscale eddy models in a global eddy-rich model, Ocean
Model., 115, 42–58, https://doi.org/10.1016/j.ocemod.2017.05.007, 2017.
Rackow, T., Goessling, H. F., Jung, T., Sidorenko, D., Semmler, T., Barbi,
D., and Handorf, D.: Towards multi-resolution global climate modeling with
ECHAM6-FESOM. Part II: climate variability, Clim. Dyn., 50,
2369–2394, https://doi.org/10.1007/s00382-016-3192-6, 2018.
Rackow, T., Sein, D. V., Semmler, T., Danilov, S., Koldunov, N. V., Sidorenko, D., Wang, Q., and Jung, T.: Sensitivity of deep ocean biases to horizontal resolution in prototype CMIP6 simulations with AWI-CM1.0, Geosci. Model Dev., 12, 2635–2656, https://doi.org/10.5194/gmd-12-2635-2019, 2019.
Rahaman, H., Srinivasu, U., Panickal, S., Durgadoo, J. V., Griffies, S. M.,
Ravichandran, M., Bozec, A., Cherchi, A., Voldoire, A., Sidorenko, D.,
Chassignet, E. P., Danabasoglu, G., Tsujino, H., Getzlaff, K., Ilicak, M.,
Bentsen, M., Long, M. C., Fogli, P. G., Farneti, R., Danilov, S., Marsland,
S. J., Valcke, S., Yeager, S. G., and Wang, Q.: An assessment of the Indian
Ocean mean state and seasonal cycle in a suite of interannual CORE-II
simulations, Ocean Model., 145, 101503, https://doi.org/10.1016/j.ocemod.2019.101503, 2020.
Redi, M. H.: Oceanic isopycnal mixing by coordinate rotation, J. Phys.
Oceanogr., 12, 1154–1158, https://doi.org/10.1175/1520-0485(1982)012<1154:OIMBCR>2.0.CO;2, 1982.
Renault, L., Masson, S., Arsouze, T., Madec, G., and McWilliams, J. C.:
Recipes for how to force oceanic model dynamics, J. Adv. Model. Earth Sy.,
2019MS001715, https://doi.org/10.1029/2019MS001715, 2020.
Renault, L., McWilliams, J. C., and Penven, P.: Modulation of the Agulhas
Current retroflection and leakage by oceanic current interaction with the
atmosphere in coupled simulations, J. Phys. Oceanogr., 47, 2077–2100,
https://doi.org/10.1175/JPO-D-16-0168.1, 2017.
Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., and
Schlax, M. G.: Daily high-resolution-blended analyses for sea surface
temperature, J. Climate, 20, 5473–5496, https://doi.org/10.1175/2007JCLI1824.1, 2007.
Richardson, P. L.: A census of eddies observed in North Atlantic SOFAR float
data, Prog. Oceanogr., 31, 1–50, https://doi.org/10.1016/0079-6611(93)90022-6, 1993.
Roach, L. A., Horvat, C., Dean, S. M., and Bitz, C. M.: An emergent sea ice
floe size distribution in a global coupled ocean-sea ice model, J.
Geophys. Res.-Oceans, 123, 4322–4337, https://doi.org/10.1029/2017JC013692,
2018.
Roach, L. A., Dörr, J., Holmes, C. R., Massonnet, F., Blockley, E. W.,
Notz, D., Rackow, T., Raphael, M. N., O'Farrell, S. P., Bailey, D. A., and
Bitz, C. M.: Antarctic sea ice area in CMIP6, Geophys. Res. Lett., 47,
e2019GL086729, https://doi.org/10.1029/2019GL086729, 2020.
Rossby, T.: The North Atlantic Current and surrounding waters: At the
crossroads, Rev. Geophys., 34, 463–481, https://doi.org/10.1029/96RG02214,
1996.
Schmitz Jr., W. J.: On the World Ocean Circulation, vol. 1, Some Global
Features/North Atlantic Circulation, 1996.
Schweiger, A., Lindsay, R., Zhang, J., Steele, M., Stern, H., and Kwok, R.:
Uncertainty in modeled Arctic sea ice volume, J. Geophys. Res., 116, C00D06,
https://doi.org/10.1029/2011JC007084, 2011.
Scott, R. B., Arbic, B. K., Chassignet, E. P., Coward, A. C., Maltrud, M.,
Merryfield, W. J., Srinivasan, A., and Varghese, A.: Total kinetic energy in
four global eddying ocean circulation models and over 5000 current meter
records, Ocean Model., 32, 157–169, https://doi.org/10.1016/j.ocemod.2010.01.005,
2010.
Sein, D. V., Danilov, S., Biastoch, A., Durgadoo, J. V., Sidorenko, D.,
Harig, S., and Wang, Q.: Designing variable ocean model resolution based on
the observed ocean variability, J. Adv. Model. Earth Sy., 8, 904–916,
https://doi.org/10.1002/2016MS000650, 2016.
Sein, D. V., Koldunov, N. V., Danilov, S., Sidorenko, D., Wekerle, C.,
Cabos, W., Rackow, T., Scholz, P., Semmler, T., Wang, Q., and Jung, T.: The relative influence of atmospheric and oceanic
model resolution on the circulation of the North Atlantic Ocean
in a coupled climate model, J. Adv.
Model. Earth Syst., 10, 2026–2041, https://doi.org/10.1029/2018MS001327, 2018.
Semtner, A. J.: A model for the thermodynamic growth of sea ice in numerical
investigations of climate, J. Phys. Oceanogr., 6, 379–389,
https://doi.org/10.1175/1520-0485(1976)006<0379:amfttg>2.0.co;2,
1976.
Shu, Q., Wang, Q., Song, Z., Qiao, F., Zhao, J., Chu, M., and Li, X.:
Assessment of sea ice extent in CMIP6 with comparison to observations and
CMIP5, Geophys. Res. Lett., 47, e2020GL087965, https://doi.org/10.1029/2020GL087965,
2020.
Sidorenko, D., Koldunov, N. V., Wang, Q., Danilov, S., Goessling, H. F.,
Gurses, O., Scholz, P., Sein, D. V., Volodin, E., Wekerle, C., and Jung, T.:
Influence of a salt plume parameterization in a coupled climate model, J.
Adv. Model. Earth Sy., 10, 2357–2373, https://doi.org/10.1029/2018MS001291, 2018.
Sidorenko, D., Rackow, T., Jung, T., Semmler, T., Barbi, D., Danilov, S.,
Dethloff, K., Dorn, W., Fieg, K., Goessling, H. F., Handorf, D., Harig, S.,
Hiller, W., Juricke, S., Losch, M., Schröter, J., Sein, D. V., and Wang,
Q.: Towards multi-resolution global climate modeling with ECHAM6–FESOM.
Part I: model formulation and mean climate, Clim. Dynam., 44, 757–780,
https://doi.org/10.1007/s00382-014-2290-6, 2015.
Smagorinsky, J.: General circulation experiments with the primitive
equations, Mon. Weather Rev., 91, 99–164,
https://doi.org/10.1175/1520-0493(1963)091<0099:gcewtp>2.3.co;2,
1963.
Small, R. J., Bacmeister, J., Bailey, D., Baker, A., Bishop, S., Bryan,
F., Caron, J., Dennis, J., Gent, P., Hsu, H., Jochum, M., Lawrence, D.,
Muñoz, E., DiNezio, P., Scheitlin, T., Tomas, R., Tribbia, J., Tseng, Y.,
and Vertenstein, M.: A new synoptic scale resolving global climate
simulation using the Community Earth System Model, J. Adv. Model. Earth
Sy., 6, 1065–1094, https://doi.org/10.1002/2014MS000363, 2014.
Small, R. J., Curchitser, E., Hedstrom, K., Kauffman, B., and Large, W. G.:
The Benguela upwelling system: Quantifying the sensitivity to resolution and
coastal wind representation in a global climate model, J. Climate, 28,
9409–9432, https://doi.org/10.1175/JCLI-D-15-0192.1, 2015.
Smeed, D. A., Josey, S. A., Beaulieu, C., Johns, W. E., Moat, B. I.,
Frajka-Williams, E., Rayner, D., Meinen, C. S., Baringer, M. O., Bryden, H.
L., and McCarthy, G. D.: The North Atlantic Ocean is in a state of reduced
overturning, Geophys. Res. Lett., 45, 1527–1533,
https://doi.org/10.1002/2017GL076350, 2018.
Smith, R., Jones, P., Briegleb, B., Bryan, F., Danabasoglu, G., Dennis, J., Dukowicz, J., Eden, C., Fox-Kemper, B., Gent, P., Hecht, M., Jayne, S., Jochum, K. L. M., Large, W., Maltrud, M., Norton, N., Peacock, S., Vertenstein, M., and Yeager, S.: The parallel
ocean program (POP) reference manual: ocean component of the community
climate system model (CCSM) and community earth system model (CESM), Rep.
LAUR-01853, 141, 1–140, 2010.
Sprintall, J., Wijffels, S. E., Molcard, R., and Jaya, I.: Direct estimates
of the Indonesian Throughflow entering the Indian Ocean: 2004–2006, J.
Geophys. Res., 114, C07001, https://doi.org/10.1029/2008JC005257, 2009.
St. Laurent, L. C., Simmons, H. L., and Jayne, S. R.: Estimating tidally
driven mixing in the deep ocean, Geophys. Res. Lett., 29, 2106,
https://doi.org/10.1029/2002gl015633, 2002.
Steele, M., Morley, R., and Ermold, W.: PHC: A Global Ocean Hydrography with
a High-Quality Arctic Ocean, J. Climate, 14, 2079–2087,
https://doi.org/10.1175/1520-0442(2001)014<2079:PAGOHW>2.0.CO;2,
2001.
Stewart, K. D., Hogg, A. McC., Griffies, S. M., Heerdegen, A. P., Ward, M.
L., Spence, P., and England, M. H.: Vertical resolution of baroclinic modes
in global ocean models, Ocean Model., 113, 50–65,
https://doi.org/10.1016/j.ocemod.2017.03.012, 2017
Stroeve, J. and Meier, W. N.: Sea ice trends and climatologies from SMMR and SSM/I-SSMIS, Version 2, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/EYICLBOAAJOU, 2017.
Stroeve, J. C., Kattsov, V., Barrett, A., Serreze, M., Pavlova, T., Holland,
M., and Meier, W. N.: Trends in Arctic sea ice extent from CMIP5, CMIP3 and
observations, Geophys. Res. Lett., 39, L16502, https://doi.org/10.1029/2012GL052676,
2012.
Sun, Q., Whitney, M. M., Bryan, F. O., and Tseng, Y.: Assessing the skill of
the improved treatment of riverine freshwater in the Community Earth System
Model (CESM) relative to a new salinity climatology, J. Adv. Model. Earth
Sy., 11, 1189–1206, https://doi.org/10.1029/2018MS001349, 2019.
Suzuki, T., Yamazaki, D., Tsujino, H., Komuro, Y., Nakano, H., and Urakawa,
S.: A dataset of continental river discharge based on JRA-55 for use in a
global ocean circulation model, J. Oceanogr., 74, 421–429,
https://doi.org/10.1007/s10872-017-0458-5, 2018.
Talley, L.: Closure of the global overturning circulation through the Indian, Pacific, and Southern Oceans:
Schematics and transports, 26, 80–97, https://doi.org/10.5670/oceanog.2013.07, 2013.
Teague, W. J., Carron, M. J., and Hogan, P. J.: A comparison between the
Generalized Digital Environmental Model and Levitus climatologies, J.
Geophys. Res., 95, 7167–7183, https://doi.org/10.1029/jc095ic05p07167, 1990.
Thoppil, P. G., Richman, J. G., and Hogan, P. J.: Energetics of a global
ocean circulation model compared to observations, Geophys. Res. Lett.,
38, L15607, https://doi.org/10.1029/2011GL048347, 2011.
Trenberth, K. E., Zhang, Y., Fasullo, J. T., and Cheng, L.: Observation-based
estimates of global and basin ocean meridional heat transport time series,
J. Climate, 32, 4567–4583, https://doi.org/10.1175/JCLI-D-18-0872.1, 2019.
Tseng, Y., Lin, H., Chen, H. ching, Thompson, K., Bentsen, M., Böning,
C. W., Bozec, A., Cassou, C., Chassignet, E., Chow, C. H., Danabasoglu, G.,
Danilov, S., Farneti, R., Fogli, P. G., Fujii, Y., Griffies, S. M., Ilicak,
M., Jung, T., Masina, S., Navarra, A., Patara, L., Samuels, B. L.,
Scheinert, M., Sidorenko, D., Sui, C. H., Tsujino, H., Valcke, S., Voldoire,
A., Wang, Q., and Yeager, S. G.: North and equatorial Pacific Ocean
circulation in the CORE-II hindcast simulations, Ocean Model., 104,
143–170, https://doi.org/10.1016/j.ocemod.2016.06.003, 2016.
Tsujino, H., Urakawa, L. S., Griffies, S. M., Danabasoglu, G., Adcroft, A. J., Amaral, A. E., Arsouze, T., Bentsen, M., Bernardello, R., Böning, C. W., Bozec, A., Chassignet, E. P., Danilov, S., Dussin, R., Exarchou, E., Fogli, P. G., Fox-Kemper, B., Guo, C., Ilicak, M., Iovino, D., Kim, W. M., Koldunov, N., Lapin, V., Li, Y., Lin, P., Lindsay, K., Liu, H., Long, M. C., Komuro, Y., Marsland, S. J., Masina, S., Nummelin, A., Rieck, J. K., Ruprich-Robert, Y., Scheinert, M., Sicardi, V., Sidorenko, D., Suzuki, T., Tatebe, H., Wang, Q., Yeager, S. G., and Yu, Z.: Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2), Geosci. Model Dev., 13, 3643–3708, https://doi.org/10.5194/gmd-13-3643-2020, 2020.
Tsujino, H., Urakawa, S., Nakano, H., Small, R. J., Kim, W. M., Yeager, S.
G., Danabasoglu, G., Suzuki, T., Bamber, J. L., Bentsen, M., Böning, C.
W., Bozec, A., Chassignet, E. P., Curchitser, E., Boeira Dias, F., Durack,
P. J., Griffies, S. M., Harada, Y., Ilicak, M., Josey, S. A., Kobayashi, C.,
Kobayashi, S., Komuro, Y., Large, W. G., Le Sommer, J., Marsland, S. J.,
Masina, S., Scheinert, M., Tomita, H., Valdivieso, M., and Yamazaki, D.:
JRA-55 based surface dataset for driving ocean–sea-ice models (JRA55-do),
Ocean Model., 130, 79–139, https://doi.org/10.1016/j.ocemod.2018.07.002, 2018.
Turner, A. K. and Hunke, E. C.: Impacts of a mushy-layer thermodynamic
approach in global sea-ice simulations using the CICE sea-ice model, J.
Geophys. Res.-Oceans, 120, 1253–1275, https://doi.org/10.1002/2014JC010358, 2015.
von Storch, J.-S., Haak, H., Hertwig, E., and Fast, I.: Vertical heat and
salt fluxes due to resolved and parameterised meso-scale eddies, Ocean
Model., 108, 1–19, https://doi.org/10.1016/j.ocemod.2016.10.001, 2016.
Wang, Q., Danilov, S., and Schröter, J.: Finite element ocean circulation
model based on triangular prismatic elements, with application in studying
the effect of topography representation, J. Geophys. Res., 113, C05015,
https://doi.org/10.1029/2007JC004482, 2008.
Wang, Q., Danilov, S., Sidorenko, D., Timmermann, R., Wekerle, C., Wang, X., Jung, T., and Schröter, J.: The Finite Element Sea Ice-Ocean Model (FESOM) v.1.4: formulation of an ocean general circulation model, Geosci. Model Dev., 7, 663–693, https://doi.org/10.5194/gmd-7-663-2014, 2014.
Wang, Q., Ilicak, M., Gerdes, R., Drange, H., Aksenov, Y., Bailey, D. A.,
Bentsen, M., Biastoch, A., Bozec, A., Böning, C., Cassou, C.,
Chassignet, E., Coward, A. C., Curry, B., Danabasoglu, G., Danilov, S.,
Fernandez, E., Fogli, P. G., Fujii, Y., Griffies, S. M., Iovino, D., Jahn,
A., Jung, T., Large, W. G., Lee, C., Lique, C., Lu, J., Masina, S., Nurser,
A. J. G., Rabe, B., Roth, C., Salas y Mélia, D., Samuels, B. L., Spence,
P., Tsujino, H., Valcke, S., Voldoire, A., Wang, X., and Yeager, S. G.: An
assessment of the Arctic Ocean in a suite of interannual CORE-II
simulations. Part I: Sea ice and solid freshwater, Ocean Model., 99,
110–132, https://doi.org/10.1016/j.ocemod.2015.12.008, 2016a.
Wang, Q., Ilicak, M., Gerdes, R., Drange, H., Aksenov, Y., Bailey, D. A.,
Bentsen, M., Biastoch, A., Bozec, A., Böning, C., Cassou, C.,
Chassignet, E., Coward, A. C., Curry, B., Danabasoglu, G., Danilov, S.,
Fernandez, E., Fogli, P. G., Fujii, Y., Griffies, S. M., Iovino, D., Jahn,
A., Jung, T., Large, W. G., Lee, C., Lique, C., Lu, J., Masina, S., Nurser,
A. J. G., Rabe, B., Roth, C., Salas y Mélia, D., Samuels, B. L., Spence,
P., Tsujino, H., Valcke, S., Voldoire, A., Wang, X., and Yeager, S. G.: An
assessment of the Arctic Ocean in a suite of interannual CORE-II
simulations. Part II: Liquid freshwater, Ocean Model., 99, 86–109,
https://doi.org/10.1016/j.ocemod.2015.12.009, 2016b.
Wang, Q., Danilov, S., Jung, T., Kaleschke, L., and Wernecke, A.: Sea ice
leads in the Arctic Ocean: Model assessment, interannual variability and
trends, Geophys. Res. Lett., 43, 7019–7027, https://doi.org/10.1002/2016GL068696,
2016c.
Whitworth, T.: Monitoring the transport of the Antarctic Circumpolar Current
at Drake Passage, J. Phys. Oceanogr., 13, 2045–2057,
https://doi.org/10.1175/1520-0485(1983)013<2045:mttota>2.0.co;2,
1983.
Whitworth, T. and Peterson, R. G.: Volume transport of the Antarctic
Circumpolar Current from Bottom pressure measurements, J. Phys. Oceanogr.,
15, 810–816, https://doi.org/10.1175/1520-0485(1985)015<0810:vtotac>2.0.co;2, 1985.
Xu, X., Rhines, P. B., and Chassignet, E. P.: Temperature-salinity structure of the North Atlantic circulation and associated heat and freshwater transports, J. Climate, 29, 7723–7741, https://doi.org/10.1175/JCLI-D-15-0798.1, 2016.
Xu, X., Chassignet, E. P., Dong, S., and Baringer, M. O.: Transport structure
of the South Atlantic Ocean derived from a high-resolution numerical model
and observations, J. Geophys. Res., in review, 2020a.
Xu, X., Chassignet, E. P., Firing, Y. L., and Donohue, K.: Antarctic
Circumpolar Current transport through Drake Passage: What can we learn from
comparing high-resolution model results to observations?, J. Geophys. Res.-Oceans, 125, e2020JC016365, https://doi.org/10.1029/2020JC016365, 2020b.
Xu, X., Hurlburt, H. E., Schmitz, W. J., Zantopp, R., Fischer, J., and Hogan,
P. J.: On the currents and transports connected with the atlantic meridional
overturning circulation in the subpolar North Atlantic, J. Geophys. Res.-Oceans, 118, 502–516, https://doi.org/10.1002/jgrc.20065, 2013.
Xu, X., Chassignet, E. P., Johns, W. E., Schmitz, W. J., and Metzger, E. J.:
Intraseasonal to interannual variability of the Atlantic meridional
overturning circulation from eddy-resolving simulations and observations, J.
Geophys. Res.-Oceans, 119, 5140–5159, https://doi.org/10.1002/2014jc009994, 2014.
Xu, X., Chassignet, E. P., and Wang, F.: On the variability of the Atlantic
meridional overturning circulation transports in coupled CMIP5 simulations,
Clim. Dynam., 52, 6511–6531, https://doi.org/10.1007/s00382-018-4529-0, 2019.
Yashayaev, I.: Hydrographic changes in the Labrador Sea, 1960–2005, Prog.
Oceanogr., 73, 242–276, https://doi.org/10.1016/j.pocean.2007.04.015, 2007.
Yeager, S. G. and Large, W. G.: Late-winter generation of spiciness on subducted isopycnals, J. Phys. Oceanogr., 34, 1528–1547,
https://doi.org/10.1175/1520-0485(2004)034<1528:LGOSOS>2.0.CO;2,
2004.
Yi, D. and Zwally, H. J.: Arctic Sea Ice Freeboard and Thickness, Version 1, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/SXJVJ3A2XIZT, last update: 15 April 2014, 2020.
Yu, R. C.: A two-step shape-preserving advection scheme,
Adv. Atmos. Sci., 11, 479-−490, https://doi.org/10.1007/BF02658169, 1994.
Yu, Y. Q., Tang, S. L. , Liu, H. L., Lin, P. F., and Li, X. L.: Development and evaluation of the dynamic framework of
an ocean general circulation model with arbitrary orthogonal curvilinear coordinate, Chinese J. Atmos. Sci., 42, 877−-889, https://doi.org/10.3878/j.issn.1006-9895.1805.17284, 2018 (in Chinese with English abstract).
Yu, Z. P., Liu, H. L., and Lin, P. F.: A numerical study of the influence of
tidal mixing on Atlantic meridional overturning circulation (AMOC)
Simulation, Chinese J. Atmos. Sci., 41, 1087–1100,
https://doi.org/10.3878/j.issn.1006-9895.1702.16263, 2017 (in Chinese).
Zhang, X. H. and Liang, X. Z.: A numerical world ocean general circulation model, Adv. Atmos. Sci., 6, 44−-61,
https://doi.org/10.1007/BF02656917, 1989.
Zweng, M. M., Reagan, J. R., Antonov, J. I., Locarnini, R. A., Mishonov, A. V., Boyer, T. P., Garcia, H. E., Baranova, O. K., Johnson, D. R., Seidov, D., and Biddle, M. M.: World Ocean Atlas 2013, vol. 2, Salinity, edited by: Levitus, and Mishonov, A., NOAA Atlas NESDIS 74, 39 pp., 2013.
Short summary
This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations to assess the robustness of climate-relevant improvements in ocean simulations associated with moving from coarse (∼1°) to eddy-resolving (∼0.1°) horizontal resolutions. Despite significant improvements, greatly enhanced horizontal resolution does not deliver unambiguous bias reduction in all regions for all models.
This paper presents global comparisons of fundamental global climate variables from a suite of...
Special issue