Articles | Volume 16, issue 5
https://doi.org/10.5194/os-16-1225-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-16-1225-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Oct 2020
Research article |
| 23 Oct 2020
| 23 Oct 2020
Properties and dynamics of mesoscale eddies in Fram Strait from a comparison between two high-resolution ocean–sea ice models
Claudia Wekerle
CORRESPONDING AUTHOR
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
Tore Hattermann
Norwegian Polar Institute, Tromsø, Norway
Energy and Climate Group, Department of Physics and Technology, The Arctic University of Tromsø, Tromsø, Norway
Qiang Wang
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
Laura Crews
School of Oceanography, University of Washington, Seattle, USA
Applied Physics Laboratory, University of Washington, Seattle, USA
Wilken-Jon von Appen
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
Sergey Danilov
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
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Xiaoxu Shi, Alexandre Cauquoin, Gerrit Lohmann, Lukas Jonkers, Qiang Wang, Hu Yang, Yuchen Sun, and Martin Werner
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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
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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.
Chen Zhao, Rupert Gladstone, Benjamin Keith Galton-Fenzi, David Gwyther, and Tore Hattermann
Geosci. Model Dev., 15, 5421–5439, https://doi.org/10.5194/gmd-15-5421-2022, https://doi.org/10.5194/gmd-15-5421-2022, 2022
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We use a coupled ice–ocean model to explore an oscillation feature found in several contributing models to MISOMIP1. The oscillation is closely related to the discretized grounding line retreat and likely strengthened by the buoyancy–melt feedback and/or melt–geometry feedback near the grounding line, and frequent ice–ocean coupling. Our model choices have a non-trivial impact on mean melt and ocean circulation strength, which might be interesting for the coupled ice–ocean community.
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
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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.
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
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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
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Coen Hofstede, Sebastian Beyer, Hugh Corr, Olaf Eisen, Tore Hattermann, Veit Helm, Niklas Neckel, Emma C. Smith, Daniel Steinhage, Ole Zeising, and Angelika Humbert
The Cryosphere, 15, 1517–1535, https://doi.org/10.5194/tc-15-1517-2021, https://doi.org/10.5194/tc-15-1517-2021, 2021
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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
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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.
Rupert Gladstone, Benjamin Galton-Fenzi, David Gwyther, Qin Zhou, Tore Hattermann, Chen Zhao, Lenneke Jong, Yuwei Xia, Xiaoran Guo, Konstantinos Petrakopoulos, Thomas Zwinger, Daniel Shapero, and John Moore
Geosci. Model Dev., 14, 889–905, https://doi.org/10.5194/gmd-14-889-2021, https://doi.org/10.5194/gmd-14-889-2021, 2021
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Retreat of the Antarctic ice sheet, and hence its contribution to sea level rise, is highly sensitive to melting of its floating ice shelves. This melt is caused by warm ocean currents coming into contact with the ice. Computer models used for future ice sheet projections are not able to realistically evolve these melt rates. We describe a new coupling framework to enable ice sheet and ocean computer models to interact, allowing projection of the evolution of melt and its impact on sea level.
Eric P. Chassignet, Stephen G. Yeager, Baylor Fox-Kemper, Alexandra Bozec, Frederic Castruccio, Gokhan Danabasoglu, Christopher Horvat, Who M. Kim, Nikolay Koldunov, Yiwen Li, Pengfei Lin, Hailong Liu, Dmitry V. Sein, Dmitry Sidorenko, Qiang Wang, and Xiaobiao Xu
Geosci. Model Dev., 13, 4595–4637, https://doi.org/10.5194/gmd-13-4595-2020, https://doi.org/10.5194/gmd-13-4595-2020, 2020
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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.
Nicolas C. Jourdain, Xylar Asay-Davis, Tore Hattermann, Fiammetta Straneo, Hélène Seroussi, Christopher M. Little, and Sophie Nowicki
The Cryosphere, 14, 3111–3134, https://doi.org/10.5194/tc-14-3111-2020, https://doi.org/10.5194/tc-14-3111-2020, 2020
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To predict the future Antarctic contribution to sea level rise, we need to use ice sheet models. The Ice Sheet Model Intercomparison Project for AR6 (ISMIP6) builds an ensemble of ice sheet projections constrained by atmosphere and ocean projections from the 6th Coupled Model Intercomparison Project (CMIP6). In this work, we present and assess a method to derive ice shelf basal melting in ISMIP6 from the CMIP6 ocean outputs, and we give examples of projected melt rates.
Hélène Seroussi, Sophie Nowicki, Antony J. Payne, Heiko Goelzer, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Torsten Albrecht, Xylar Asay-Davis, Alice Barthel, Reinhard Calov, Richard Cullather, Christophe Dumas, Benjamin K. Galton-Fenzi, Rupert Gladstone, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Nicolas C. Jourdain, Thomas Kleiner, Eric Larour, Gunter R. Leguy, Daniel P. Lowry, Chistopher M. Little, Mathieu Morlighem, Frank Pattyn, Tyler Pelle, Stephen F. Price, Aurélien Quiquet, Ronja Reese, Nicole-Jeanne Schlegel, Andrew Shepherd, Erika Simon, Robin S. Smith, Fiammetta Straneo, Sainan Sun, Luke D. Trusel, Jonas Van Breedam, Roderik S. W. van de Wal, Ricarda Winkelmann, Chen Zhao, Tong Zhang, and Thomas Zwinger
The Cryosphere, 14, 3033–3070, https://doi.org/10.5194/tc-14-3033-2020, https://doi.org/10.5194/tc-14-3033-2020, 2020
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The Antarctic ice sheet has been losing mass over at least the past 3 decades in response to changes in atmospheric and oceanic conditions. This study presents an ensemble of model simulations of the Antarctic evolution over the 2015–2100 period based on various ice sheet models, climate forcings and emission scenarios. Results suggest that the West Antarctic ice sheet will continue losing a large amount of ice, while the East Antarctic ice sheet could experience increased snow accumulation.
Hiroyuki Tsujino, L. Shogo Urakawa, Stephen M. Griffies, Gokhan Danabasoglu, Alistair J. Adcroft, Arthur E. Amaral, Thomas Arsouze, Mats Bentsen, Raffaele Bernardello, Claus W. Böning, Alexandra Bozec, Eric P. Chassignet, Sergey Danilov, Raphael Dussin, Eleftheria Exarchou, Pier Giuseppe Fogli, Baylor Fox-Kemper, Chuncheng Guo, Mehmet Ilicak, Doroteaciro Iovino, Who M. Kim, Nikolay Koldunov, Vladimir Lapin, Yiwen Li, Pengfei Lin, Keith Lindsay, Hailong Liu, Matthew C. Long, Yoshiki Komuro, Simon J. Marsland, Simona Masina, Aleksi Nummelin, Jan Klaus Rieck, Yohan Ruprich-Robert, Markus Scheinert, Valentina Sicardi, Dmitry Sidorenko, Tatsuo Suzuki, Hiroaki Tatebe, Qiang Wang, Stephen G. Yeager, and Zipeng Yu
Geosci. Model Dev., 13, 3643–3708, https://doi.org/10.5194/gmd-13-3643-2020, https://doi.org/10.5194/gmd-13-3643-2020, 2020
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The OMIP-2 framework for global ocean–sea-ice model simulations is assessed by comparing multi-model means from 11 CMIP6-class global ocean–sea-ice models calculated separately for the OMIP-1 and OMIP-2 simulations. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet key improvements in transitioning from OMIP-1 to OMIP-2 are also identified. Thus, the present assessment justifies that future ocean–sea-ice model development and analysis studies use the OMIP-2 framework.
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
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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.
Wilken-Jon von Appen, Volker H. Strass, Astrid Bracher, Hongyan Xi, Cora Hörstmann, Morten H. Iversen, and Anya M. Waite
Ocean Sci., 16, 253–270, https://doi.org/10.5194/os-16-253-2020, https://doi.org/10.5194/os-16-253-2020, 2020
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Nutrient-rich water is moved to the surface near continental margins. Then it forms rich but difficult to observe spatial structures of physical and biological/biogeochemical properties. Here we present a high resolution (2.5 km) section through such features obtained in May 2018 with a vehicle towed behind a ship. Considering that such interactions of physics and biology are common in the ocean, they likely strongly influence the productivity of such systems and their role in CO2 uptake.
Felix L. Müller, Denise Dettmering, Claudia Wekerle, Christian Schwatke, Marcello Passaro, Wolfgang Bosch, and Florian Seitz
Earth Syst. Sci. Data, 11, 1765–1781, https://doi.org/10.5194/essd-11-1765-2019, https://doi.org/10.5194/essd-11-1765-2019, 2019
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Polar regions by satellite-altimetry-derived geostrophic currents (GCs) suffer from irregular and sparse data coverage. Therefore, a new dataset is presented, combining along-track derived dynamic ocean topography (DOT) heights with simulated differential water heights. For this purpose, a combination method, based on principal component analysis, is used. The results are combined with spatio-temporally consistent DOT and derived GC representations on unstructured, triangular formulated grids.
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
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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.
Ivan Kuznetsov, Alexey Androsov, Vera Fofonova, Sergey Danilov, Natalja Rakowsky, Sven Harig, and Karen Helen Wiltshire
Ocean Sci. Discuss., https://doi.org/10.5194/os-2019-103, https://doi.org/10.5194/os-2019-103, 2019
Revised manuscript not accepted
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Coastal regions play a significant role in global processes. Numerical models are one of the major instruments in understanding ocean dynamics. The main objective of this article is to demonstrate the representativeness of the simulations with the new FESOM-C model by comparing the results with observational data for the southeastern part of the North Sea. An equally important objective is to present the application of convergence analysis of solutions for grids of different spatial resolutions.
Katrin Lindbäck, Geir Moholdt, Keith W. Nicholls, Tore Hattermann, Bhanu Pratap, Meloth Thamban, and Kenichi Matsuoka
The Cryosphere, 13, 2579–2595, https://doi.org/10.5194/tc-13-2579-2019, https://doi.org/10.5194/tc-13-2579-2019, 2019
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In this study, we used a ground-penetrating radar technique to measure melting at high precision under Nivlisen, an ice shelf in central Dronning Maud Land, East Antarctica. We found that summer-warmed ocean surface waters can increase melting close to the ice shelf front. Our study shows the use of and need for measurements in the field to monitor Antarctica's coastal margins; these detailed variations in basal melting are not captured in satellite data but are vital to predict future changes.
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
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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
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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
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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.
Alexey Androsov, Vera Fofonova, Ivan Kuznetsov, Sergey Danilov, Natalja Rakowsky, Sven Harig, Holger Brix, and Karen Helen Wiltshire
Geosci. Model Dev., 12, 1009–1028, https://doi.org/10.5194/gmd-12-1009-2019, https://doi.org/10.5194/gmd-12-1009-2019, 2019
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We present a description of a coastal ocean circulation model designed to work on variable-resolution meshes made of triangular and quadrilateral cells. This hybrid mesh functionality allows for higher numerical performance and less dissipative solutions.
Felix L. Müller, Claudia Wekerle, Denise Dettmering, Marcello Passaro, Wolfgang Bosch, and Florian Seitz
The Cryosphere, 13, 611–626, https://doi.org/10.5194/tc-13-611-2019, https://doi.org/10.5194/tc-13-611-2019, 2019
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Knowledge of the dynamic ocean topography (DOT) enables studying changes of ocean surface currents. The DOT can be derived by satellite altimetry measurements or by models. However, in polar regions, altimetry-derived sea surface heights are affected by sea ice. Model representations are consistent but impacted by the underlying functional backgrounds and forcing models. The present study compares results from both data sources in order to investigate the potential for a combination of the two.
Maren Elisabeth Richter, Wilken-Jon von Appen, and Claudia Wekerle
Ocean Sci., 14, 1147–1165, https://doi.org/10.5194/os-14-1147-2018, https://doi.org/10.5194/os-14-1147-2018, 2018
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In the Fram Strait, Arctic Ocean outflow is joined by Atlantic Water (AW) that has not flowed through the Arctic Ocean. The confluence creates a density gradient which steepens and draws closer to the east Greenland shelf break from N to S. This brings the warm AW closer to the shelf break. South of 79° N, AW has reached the shelf break and the East Greenland Current has formed. When AW reaches the Greenland shelf it may propagate through troughs to glacier termini and contribute to glacier melt.
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
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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.
Amelie Driemel, Eberhard Fahrbach, Gerd Rohardt, Agnieszka Beszczynska-Möller, Antje Boetius, Gereon Budéus, Boris Cisewski, Ralph Engbrodt, Steffen Gauger, Walter Geibert, Patrizia Geprägs, Dieter Gerdes, Rainer Gersonde, Arnold L. Gordon, Hannes Grobe, Hartmut H. Hellmer, Enrique Isla, Stanley S. Jacobs, Markus Janout, Wilfried Jokat, Michael Klages, Gerhard Kuhn, Jens Meincke, Sven Ober, Svein Østerhus, Ray G. Peterson, Benjamin Rabe, Bert Rudels, Ursula Schauer, Michael Schröder, Stefanie Schumacher, Rainer Sieger, Jüri Sildam, Thomas Soltwedel, Elena Stangeew, Manfred Stein, Volker H Strass, Jörn Thiede, Sandra Tippenhauer, Cornelis Veth, Wilken-Jon von Appen, Marie-France Weirig, Andreas Wisotzki, Dieter A. Wolf-Gladrow, and Torsten Kanzow
Earth Syst. Sci. Data, 9, 211–220, https://doi.org/10.5194/essd-9-211-2017, https://doi.org/10.5194/essd-9-211-2017, 2017
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Our oceans are always in motion – huge water masses are circulated by winds and by global seawater density gradients resulting from different water temperatures and salinities. Measuring temperature and salinity of the world's oceans is crucial e.g. to understand our climate. Since 1983, the research icebreaker Polarstern has been the basis of numerous water profile measurements in the Arctic and the Antarctic. We report on a unique collection of 33 years of polar salinity and temperature data.
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
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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.
Stephen M. Griffies, Gokhan Danabasoglu, Paul J. Durack, Alistair J. Adcroft, V. Balaji, Claus W. Böning, Eric P. Chassignet, Enrique Curchitser, Julie Deshayes, Helge Drange, Baylor Fox-Kemper, Peter J. Gleckler, Jonathan M. Gregory, Helmuth Haak, Robert W. Hallberg, Patrick Heimbach, Helene T. Hewitt, David M. Holland, Tatiana Ilyina, Johann H. Jungclaus, Yoshiki Komuro, John P. Krasting, William G. Large, Simon J. Marsland, Simona Masina, Trevor J. McDougall, A. J. George Nurser, James C. Orr, Anna Pirani, Fangli Qiao, Ronald J. Stouffer, Karl E. Taylor, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Maria Valdivieso, Qiang Wang, Michael Winton, and Stephen G. Yeager
Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, https://doi.org/10.5194/gmd-9-3231-2016, 2016
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The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This document defines OMIP and details a protocol both for simulating global ocean/sea-ice models and for analysing their output.
Tim Stöven, Toste Tanhua, Mario Hoppema, and Wilken-Jon von Appen
Ocean Sci., 12, 319–333, https://doi.org/10.5194/os-12-319-2016, https://doi.org/10.5194/os-12-319-2016, 2016
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The article describes transient tracer distributions of CFC-12 and SF6 in the Fram Strait in 2012. The SF6 excess and the anthropogenic carbon content in this area was estimated assuming a standard parameterization of the inverse-Gaussian–transit-time distribution. Hydrographic data were obtained along a mooring array at 78°50’N and a mean velocity field was used for flux estimates.
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
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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.
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
N. Rakowsky, A. Androsov, A. Fuchs, S. Harig, A. Immerz, S. Danilov, W. Hiller, and J. Schröter
Nat. Hazards Earth Syst. Sci., 13, 1629–1642, https://doi.org/10.5194/nhess-13-1629-2013, https://doi.org/10.5194/nhess-13-1629-2013, 2013
Cited articles
Adcock, S. T. and Marshall, D. P.: Interactions between Geostrophic Eddies and
the Mean Circulation over Large-Scale Bottom Topography, J. Phys.
Oceanogr., 30, 3223–3238,
https://doi.org/10.1175/1520-0485(2000)030<3223:IBGEAT>2.0.CO;2, 2000. a
Albretsen, J., Hattermann, T., and Sundfjord, A.: Ocean and sea ice circulation model results from Svalbard area (ROMS) [Data set], Norwegian Polar Institute, https://doi.org/10.21334/npolar.2017.2f52acd2, 2017. a
Bashmachnikov, I. L., Kozlov, I. E., Petrenko, L. A., Glok, N. I., and Wekerle,
C.: Eddies in the North Greenland Sea and Fram Strait From Satellite
Altimetry, SAR and High-Resolution Model Data, J. Geophys.
Res.-Oceans, 125, e2019JC015832, https://doi.org/10.1029/2019JC015832, 2020. a, b, c
Beszczynska-Möller, A., Fahrbach, E., Schauer, U., and Hansen, E.:
Variability in Atlantic water temperature and transport at the entrance to
the Arctic Ocean, 1997–2010, ICES J. Mar. Sci., 69, 852–863,
https://doi.org/10.1093/icesjms/fss056, 2012. a, b
Budgell, W. P.: Numerical simulation of ice-ocean variability in the Barents
Sea region, Ocean Dynam., 55, 370–387, https://doi.org/10.1007/s10236-005-0008-3,
2005. a, b
Chelton, D. B., Schlax, M. G., and Samelson, R. M.: Global observations of
nonlinear mesoscale eddies, Prog. Oceanogr., 91, 167–216,
https://doi.org/10.1016/j.pocean.2011.01.002, 2011. a, b
Cherian, D. A. and Brink, K. H.: Shelf Flows Forced by Deep-Ocean Anticyclonic
Eddies at the Shelf Break, J. Phys. Oceanogr., 48, 1117–1138,
https://doi.org/10.1175/JPO-D-17-0237.1, 2018. a
Crews, L., Sundfjord, A., Albretsen, J., and Hattermann, T.: Mesoscale Eddy
Activity and Transport in the Atlantic Water Inflow Region North of
Svalbard, J. Geophys. Res.-Oceans, 123, 201–215,
https://doi.org/10.1002/2017JC013198, 2018. a
Crews, L., Sundfjord, A., and Hattermann, T.: How the Yermak Pass Branch
Regulates Atlantic Water Inflow to the Arctic Ocean, J. Geophys.
Res.-Oceans, 124, 267–280, https://doi.org/10.1029/2018JC014476, 2019. a, b
Dai, A., Qian, T., Trenberth, K. E., and Milliman, J. D.: Changes in
Continental Freshwater Discharge from 1948 to 2004, J. Climate, 22,
2773–2792, https://doi.org/10.1175/2008JCLI2592.1, 2009. a
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. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.,
Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M.,
Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park,
B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and
Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the
data assimilation system, Q. J. Roy. Meteor.
Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
de Steur, L., Hansen, E., Gerdes, R., Karcher, M., Fahrbach, E., and Holfort,
J.: Freshwater fluxes in the East Greenland Current: A decade of
observations, Geophys. Res. Lett., 36, L23611, https://doi.org/10.1029/2009GL041278, 2009. a
Egbert, G. D. and Erofeeva, S. Y.: Efficient Inverse Modeling of Barotropic
Ocean Tides, J. Atmos. Ocean. Tech., 19, 183–204,
https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2, 2002. a
Eldevik, T., Nilsen, J. E. Ø., Iovino, D., Olsson, K. A., Sandø, A. B.,
and Drange, H.: Observed sources and variability of Nordic Seas overflow,
Nat. Geosci., 2, 406–410, https://doi.org/10.1038/NGEO518, 2009. a
Fer, I., Müller, M., and Peterson, A. K.: Tidal forcing, energetics, and mixing near the Yermak Plateau, Ocean Sci., 11, 287–304, https://doi.org/10.5194/os-11-287-2015, 2015 a
Fer, I., Bosse, A., and Dugstad, J.: Norwegian Atlantic Slope Current along
the Lofoten Escarpment, Ocean Science, 16, 685–701,
https://doi.org/10.5194/os-16-685-2020, 2020. a, b
Gent, P. and McWilliams, J.: Isopycnal Mixing in Ocean Circulation Models, J.
Phys. Oceanogr., 20, 150–155, 1990. a
Griffies, S.: 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. a
Gula, J., Molemaker, M. J., and McWilliams, J. C.: Gulf Stream Dynamics along
the Southeastern U.S. Seaboard, J. Phys. Oceanogr., 45, 690–715,
https://doi.org/10.1175/JPO-D-14-0154.1, 2015. a
Haidvogel, D., Arango, H., Budgell, W., Cornuelle, B., Curchitser, E., Lorenzo,
E. D., Fennel, K., Geyer, W., Hermann, A., Lanerolle, L., Levin, J.,
McWilliams, J., Miller, A., Moore, A., Powell, T., Shchepetkin, A., Sherwood,
C., Signell, R., Warner, J., and Wilkin, J.: Ocean forecasting in
terrain-following coordinates: Formulation and skill assessment of the
Regional Ocean Modeling System, J. Comput. Phys., 227, 3595–3624, https://doi.org/10.1016/j.jcp.2007.06.016, 2008. a
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. a
Isern-Fontanet, J., Garcia-Ladona, E., and Font, J.: Vortices of the
Mediterranean Sea: An Altimetric Perspective, J. Phys.
Oceanogr., 36, 87–103, https://doi.org/10.1175/JPO2826.1, 2006. a
Jansen, M. F., Held, I. M., Adcroft, A., and Hallberg, R.: Energy budget-based
backscatter in an eddy permitting primitive equation model, Ocean Model.,
94, 15–26, https://doi.org/10.1016/j.ocemod.2015.07.015, 2015. a
Johannessen, O. M., Johannessen, J. A., Svendsen, E., Shuchman, R. A.,
Campbell, W. J., and Josberger, E.: Ice-Edge Eddies in the Fram Strait
Marginal Ice Zone, Science, 236, 427–429,
https://doi.org/10.1126/science.236.4800.427, 1987. a, b
Juricke, S., Danilov, S., Kutsenko, A., and Oliver, M.: Ocean kinetic energy
backscatter parametrizations on unstructured grids: Impact on mesoscale
turbulence in a channel, Ocean Model., 138, 51–67,
https://doi.org/10.1016/j.ocemod.2019.03.009, 2019. a
Juricke, S., Danilov, S., Koldunov, N., Oliver, M., and Sidorenko, D.: Ocean
Kinetic Energy Backscatter Parametrization on Unstructured Grids: Impact on
Global Eddy-Permitting Simulations, J. Adv. Model. Earth
Sy., 12, e2019MS001855, https://doi.org/10.1029/2019MS001855, 2020. a
Kang, D. and Curchitser, E. N.: Gulf Stream eddy characteristics in a
high-resolution ocean model, J. Geophys. Res.-Oceans, 118,
4474–4487, https://doi.org/10.1002/jgrc.20318, 2013. a
Kawasaki, T. and Hasumi, H.: The inflow of Atlantic water at the Fram Strait
and its interannual variability, J. Geophys. Res.-Oceans, 121, 502–519,
https://doi.org/10.1002/2015JC011375, 2016. a
Large, W. and Yeager, S.: 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, 2008. a
Lüschow, V., Storch, J.-S. v., and Marotzke, J.: Diagnosing the Influence
of Mesoscale Eddy Fluxes on the Deep Western Boundary Current in the
1∕10∘ STORM/NCEP Simulation, J. Phys. Oceanogr., 49,
751–764, https://doi.org/10.1175/JPO-D-18-0103.1, 2019. a
Mahadevan, A.: The Impact of Submesoscale Physics on Primary Productivity of
Plankton, Annu. Rev. Mar. Sci., 8, 161–184,
https://doi.org/10.1146/annurev-marine-010814-015912, 2016. a
Manucharyan, G. E. and Thompson, A. F.: Submesoscale Sea Ice-Ocean
Interactions in Marginal Ice Zones, J. Geophys. Res.-Oceans,
122, 9455–9475, https://doi.org/10.1002/2017JC012895, 2017. a
Martínez-Moreno, J., Hogg, A. M., Kiss, A. E., Constantinou, N. C., and
Morrison, A. K.: Kinetic Energy of Eddy-Like Features From Sea Surface
Altimetry, J. Adv. Modeling Earth Sy., 11, 3090–3105,
https://doi.org/10.1029/2019MS001769, 2019. a
Morrow, R., Birol, F., Griffin, D., and Sudre, J.: Divergent pathways of
cyclonic and anti-cyclonic ocean eddies, Geophys. Res. Lett., 31, L24311,
https://doi.org/10.1029/2004GL020974, 2004. a
Nencioli, F., Dong, C., Dickey, T., Washburn, L., and McWilliams, J. C.: A
Vector Geometry-Based Eddy Detection Algorithm and Its Application to a
High-Resolution Numerical Model Product and High-Frequency Radar Surface
Velocities in the Southern California Bight, J. Atmos.
Ocean. Tech., 27, 564–579, https://doi.org/10.1175/2009JTECHO725.1, 2010. a, b, c, d, e
Okubo, A.: Horizontal dispersion of floatable particles in the vicinity of
velocity singularities such as convergences, Deep Sea Research and
Oceanographic Abstracts, 17, 445–454, https://doi.org/10.1016/0011-7471(70)90059-8,
1970. a
Olbers, D., Willebrand, J., and Eden, C.: Ocean Dynamics, Springer-Verlag,
Berlin Heidelberg, https://doi.org/10.1007/978-3-642-23450-7, 2012. a
Olson, D. B.: Rings in the ocean, Annu. Rev. Earth Pl.
Sc., 19, 283–311, 1991. a
Polyakov, I. V., Pnyushkov, A. V., and Timokhov, L.: Warming of the
Intermediate Atlantic Water of the Arctic Ocean in the 2000s, J. Climate,
25, 8362–8370, https://doi.org/10.1175/JCLI-D-12-00266.1, 2012. a
Raj, R. P., Johannessen, J. A., Eldevik, T., Nilsen, J. E. A., and Halo, I.:
Quantifying mesoscale eddies in the Lofoten Basin, J. Geophys.
Res.-Oceans, 121, 4503–4521, https://doi.org/10.1002/2016JC011637, 2016. a
Richter, M. E., von Appen, W.-J., and Wekerle, C.: Does the East Greenland Current exist in the northern Fram Strait?, Ocean Sci., 14, 1147–1165, https://doi.org/10.5194/os-14-1147-2018, 2018. a
Rudels, B.: The thermohaline circulation of the Arctic Ocean and the Greenland
Sea, Philos. T. Roy. Soc. Lond. A, 352, 287–299,
https://doi.org/10.1098/rsta.1995.0071, 1995. a
Schaffer, J., von Appen, W.-J., Dodd, P. A., Hofstede, C., Mayer, C., de Steur,
L., and Kanzow, T.: Warm water pathways toward Nioghalvfjerdsfjorden
Glacier, Northeast Greenland, J. Geophys. Res.-Oceans, 122,
4004–4020, https://doi.org/10.1002/2016JC012462, 2017. a
Schauer, U., Fahrbach, E., Østerhus, S., and Rohardt, G.: Arctic warming
through the Fram Strait: Oceanic heat transport from 3 years of
measurements, J. Geophys. Res., 109, C06026, https://doi.org/10.1029/2003JC001823, 2004. a
Shchepetkin, A. F. and McWilliams, J. C.: The regional oceanic modeling system
(ROMS): a split-explicit, free-surface, topography-following-coordinate
oceanic model, Ocean Model., 9, 347–404,
https://doi.org/10.1016/j.ocemod.2004.08.002, 2005. a, b
Shchepetkin, A. F. and McWilliams, J. C.: Correction and commentary for “Ocean forecasting in terrain-following coordinates: Formulation and skill
assessment of the regional ocean modeling system” by Haidvogel et al., J.
Comp. Phys., 227, 3595–3624, J. Comput. Phys., 228, 8985–9000, https://doi.org/10.1016/j.jcp.2009.09.002, 2009. a
Smith, D. C., Morison, J. H., Johannessen, J. A., and Untersteiner, N.:
Topographic generation of an eddy at the edge of the East Greenland
Current, J. Geophys. Res.-Oceans, 89, 8205–8208,
https://doi.org/10.1029/JC089iC05p08205, 1984. a, b
Soufflet, Y., Marchesiello, P., Lemarié, F., Jouanno, J., Capet, X.,
Debreu, L., and Benshila, R.: On effective resolution in ocean models,
Ocean Model., 98, 36–50, https://doi.org/10.1016/j.ocemod.2015.12.004, 2016. a, b
Spall, M. A. and Pedlosky, J.: Lateral Coupling in Baroclinically Unstable
Flows, J. Phys. Oceanogr., 38, 1267–1277,
https://doi.org/10.1175/2007JPO3906.1, 2008. a
Storkey, D., Blockley, E. W., Furner, R., Guiavarc'h, C., Lea, D., Martin,
M. J., Barciela, R. M., Hines, A., Hyder, P., and Siddorn, J. R.:
Forecasting the ocean state using NEMO: The new FOAM system, J.
Oper. Oceanogr., 3, 3–15, https://doi.org/10.1080/1755876X.2010.11020109,
2010. a
Teigen, S. H., Nilsen, F., Skogseth, R., Gjevik, B., and Beszczynska-Möller,
A.: Baroclinic instability in the West Spitsbergen Current, J. Geophys.
Res.-Oceans, 116, C07012, https://doi.org/10.1029/2011JC006974, 2011. a, b
Tverberg, V. and Nøst, O. A.: Eddy overturning across a shelf edge front:
Kongsfjorden, west Spitsbergen, J. Geophys. Res.-Oceans,
114, C04024, https://doi.org/10.1029/2008JC005106, 2009. a, b, c
Volkov, D. L., Kubryakov, A. A., and Lumpkin, R.: Formation and variability of
the Lofoten basin vortex in a high-resolution ocean model, Deep-Sea Res.
Pt. I, 105, 142–157, https://doi.org/10.1016/j.dsr.2015.09.001, 2015. a
von Appen, W.-J., Wekerle, C., Hehemann, L., Schourup-Kristensen, V., Konrad,
C., and Iversen, M. H.: Observations of a Submesoscale Cyclonic Filament in
the Marginal Ice Zone, Geophys. Res. Lett., 45, 6141–6149,
https://doi.org/10.1029/2018GL077897, 2018. a, b
von Appen, W.-J., Beszczynska-Möller, A., Schauer, U., and
Fahrbach, E.: Physical oceanography and current meter data from moorings
F1–F14 and F15/F16 in the Fram Strait, 1997–2016, PANGAEA,
https://doi.org/10.1594/PANGAEA.900883, 2019. a, b, c, d
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. a
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. a, b
Wang, Q., Koldunov, N. V., Danilov, S., Sidorenko, D., Wekerle, C., Scholz, P.,
Bashmachnikov, I. L., and Jung, T.: Eddy Kinetic Energy in the Arctic Ocean
from a Global Simulation with a 1-km Arctic, Geophys. Res. Lett., 47, e2020GL088550,
https://doi.org/10.1029/2020GL088550, 2020. a
Weiss, J.: The dynamics of enstrophy transfer in two-dimensional
hydrodynamics, Physica D, 48, 273–294,
https://doi.org/10.1016/0167-2789(91)90088-Q, 1991. a
Wekerle, C., Wang, Q., von Appen, W.-J., Danilov, S., Schourup-Kristensen, V.,
and Jung, T.: Eddy-Resolving Simulation of the Atlantic Water Circulation in
the Fram Strait With Focus on the Seasonal Cycle, J. Geophys. Res.-Oceans, 122, 8385–8405,
https://doi.org/10.1002/2017JC012974, 2017a. a, b, c, d, e, f, g
Wekerle, C., Wang, Q., von Appen, W.-J., Danilov, S., Schourup-Kristensen, V., and Jung, T.: Eddy-permitting and eddy-resolving simulations of the Fram Strait ocean dynamics with the Finite-Element Sea-Ice Ocean Model (FESOM), links to NetCDF files, PANGAEA, https://doi.org/10.1594/PANGAEA.880569, 2017b. a
Wilson, N., Straneo, F., and Heimbach, P.: Satellite-derived submarine melt rates and mass balance (2011–2015) for Greenland's largest remaining ice tongues, The Cryosphere, 11, 2773–2782, https://doi.org/10.5194/tc-11-2773-2017, 2017.
a
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.
The high-resolution ocean models ROMS and FESOM configured for the Fram Strait reveal very...
