Articles | Volume 11, issue 4
https://doi.org/10.5194/gmd-11-1229-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-1229-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
03 Apr 2018
Model evaluation paper |
| 03 Apr 2018
A 4.5 km resolution Arctic Ocean simulation with the global multi-resolution model FESOM 1.4
Alfred Wegener Institute Helmholtz Center for Polar and Marine
Research (AWI), Bremerhaven, Germany
Claudia Wekerle
Alfred Wegener Institute Helmholtz Center for Polar and Marine
Research (AWI), Bremerhaven, Germany
Sergey Danilov
Alfred Wegener Institute Helmholtz Center for Polar and Marine
Research (AWI), Bremerhaven, Germany
Jacobs University Bremen, Department of Mathematics & Logistics, Bremen, Germany
Xuezhu Wang
Hohai University, College of Oceanography,
Nanjing, China
Alfred Wegener Institute Helmholtz Center for Polar and Marine
Research (AWI), Bremerhaven, Germany
Thomas Jung
Alfred Wegener Institute Helmholtz Center for Polar and Marine
Research (AWI), Bremerhaven, Germany
University of Bremen, Department of Physics and Electrical Engineering, Bremen, Germany
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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
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Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-37, https://doi.org/10.5194/gmd-2023-37, 2023
Preprint under review for GMD
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Felix Pithan, Marylou Athanase, Sandro Dahlke, Antonio Sánchez-Benítez, Matthew D. Shupe, Anne Sledd, Jan Streffing, Gunilla Svensson, and Thomas Jung
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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
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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.
Sara Pasqualetto, Luisa Cristini, and Thomas Jung
Geosci. Commun., 5, 87–100, https://doi.org/10.5194/gc-5-87-2022, https://doi.org/10.5194/gc-5-87-2022, 2022
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Many projects in their reporting phase are required to provide a clear plan for evaluating the results of those efforts aimed at translating scientific results to a broader audience. This paper illustrates methodologies and strategies used in the framework of a European research project to assess the impact of knowledge transfer activities, both quantitatively and qualitatively, and provides recommendations and hints for developing a useful impact plan for scientific projects.
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
The Cryosphere, 15, 4703–4725, https://doi.org/10.5194/tc-15-4703-2021, https://doi.org/10.5194/tc-15-4703-2021, 2021
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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.
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
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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.
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
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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.
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.
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.
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.
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.
Doug M. Smith, James A. Screen, Clara Deser, Judah Cohen, John C. Fyfe, Javier García-Serrano, Thomas Jung, Vladimir Kattsov, Daniela Matei, Rym Msadek, Yannick Peings, Michael Sigmond, Jinro Ukita, Jin-Ho Yoon, and Xiangdong Zhang
Geosci. Model Dev., 12, 1139–1164, https://doi.org/10.5194/gmd-12-1139-2019, https://doi.org/10.5194/gmd-12-1139-2019, 2019
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The Polar Amplification Model Intercomparison Project (PAMIP) is an endorsed contribution to the sixth Coupled Model Intercomparison Project (CMIP6). It will investigate the causes and global consequences of polar amplification through coordinated multi-model numerical experiments. This paper documents the experimental protocol.
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.
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.
Qinghua Yang, Martin Losch, Svetlana N. Losa, Thomas Jung, Lars Nerger, and Thomas Lavergne
The Cryosphere, 10, 761–774, https://doi.org/10.5194/tc-10-761-2016, https://doi.org/10.5194/tc-10-761-2016, 2016
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We assimilate the summer SICCI sea ice concentration data with an ensemble-based Kalman Filter. Comparing with the approach using a constant data uncertainty, the sea ice concentration estimates are further improved when the SICCI-provided uncertainty are taken into account, but the sea ice thickness cannot be improved. We find the data assimilation system cannot give a reasonable ensemble spread of sea ice concentration and thickness if the provided uncertainty are directly used.
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
Related subject area
Oceanography
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
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
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)
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
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 I): Evolution of ecosystem composition under limited light and nutrient conditions
Evaluation of the CMCC global eddying ocean model for the Ocean Model Intercomparison Project (OMIP2)
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
A flexible z-coordinate approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)
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
Wind work at the air-sea interface: a modeling study in anticipation of future space missions
Improved upper-ocean thermodynamical structure modeling with combined effects of surface waves and M2 internal tides on vertical mixing: a case study for the Indian Ocean
The bulk parameterizations of turbulent air–sea fluxes in NEMO4: the origin of sea surface temperature differences in a global model study
NeverWorld2: an idealized model hierarchy to investigate ocean mesoscale eddies across resolutions
Observing system simulation experiments reveal that subsurface temperature observations improve estimates of circulation and heat content in a dynamic western boundary current
Parallel implementation of the SHYFEM (System of HydrodYnamic Finite Element Modules) model
Block-structured, equal-workload, multi-grid-nesting interface for the Boussinesq wave model FUNWAVE-TVD (Total Variation Diminishing)
Evaluation of an emergent feature of sub-shelf melt oscillations from an idealized coupled ice sheet–ocean model using FISOC (v1.1) – ROMSIceShelf (v1.0) – Elmer/Ice (v9.0)
GNOM v1.0: an optimized steady-state model of the modern marine neodymium cycle
Implementation and evaluation of open boundary conditions for sea ice in a regional coupled ocean (ROMS) and sea ice (CICE) modeling system
ROMSPath v1.0: offline particle tracking for the Regional Ocean Modeling System (ROMS)
DINCAE 2.0: multivariate convolutional neural network with error estimates to reconstruct sea surface temperature satellite and altimetry observations
RADIv1: a non-steady-state early diagenetic model for ocean sediments in Julia and MATLAB/GNU Octave
IBI-CCS: a regional high-resolution model to simulate sea level in western Europe
Empirical Lagrangian parametrization for wind-driven mixing of buoyant particles at the ocean surface
Improving ocean modeling software NEMO 4.0 benchmarking and communication efficiency
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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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.
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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, France Van Wambeke, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-33, https://doi.org/10.5194/gmd-2023-33, 2023
Revised manuscript accepted for GMD
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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.
Doroteaciro Iovino, Pier Giuseppe Fogli, and Simona Masina
EGUsphere, https://doi.org/10.5194/egusphere-2023-469, https://doi.org/10.5194/egusphere-2023-469, 2023
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The 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 OMIP-2 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.
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
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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
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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
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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
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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.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-13, https://doi.org/10.5194/gmd-2023-13, 2023
Revised manuscript accepted for GMD
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We propose a z-coordinate vertical algorithm for coastal ocean models which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation, independently of the vertical resolution, in a stable and accurate fashion. With simple analysis and realistic numerical experiments we show that it can be used to simulate effectively coastal flows with wetting and drying.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Hector S. Torres, Patrice Klein, Jinbo Wang, Alexander Wineteer, Bo Qiu, Andrew F. Thompson, Lionel Renault, Ernesto Rodriguez, Dimitris Menemenlis, Andrea Molod, Christopher N. Hill, Ehud Strobach, Hong Zhang, Mar Flexas, and Dragana Perkovic-Martin
Geosci. Model Dev., 15, 8041–8058, https://doi.org/10.5194/gmd-15-8041-2022, https://doi.org/10.5194/gmd-15-8041-2022, 2022
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Wind work at the air-sea interface is the scalar product of winds and currents and is the transfer of kinetic energy between the ocean and the atmosphere. Using a new global coupled ocean-atmosphere simulation performed at kilometer resolution, we show that all scales of winds and currents impact the ocean dynamics at spatial and temporal scales. The consequential interplay of surface winds and currents in the numerical simulation motivates the need for a winds and currents satellite mission.
Zhanpeng Zhuang, Quanan Zheng, Yongzeng Yang, Zhenya Song, Yeli Yuan, Chaojie Zhou, Xinhua Zhao, Ting Zhang, and Jing Xie
Geosci. Model Dev., 15, 7221–7241, https://doi.org/10.5194/gmd-15-7221-2022, https://doi.org/10.5194/gmd-15-7221-2022, 2022
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We evaluate the impacts of surface waves and internal tides on the upper-ocean mixing in the Indian Ocean. The surface-wave-generated turbulent mixing is dominant if depth is < 30 m, while the internal-tide-induced mixing is larger than surface waves in the ocean interior from 40
to 130 m. The simulated thermal structure, mixed layer depth and surface current are all improved when the mixing schemes are jointly incorporated into the ocean model because of the strengthened vertical mixing.
Giulia Bonino, Doroteaciro Iovino, Laurent Brodeau, and Simona Masina
Geosci. Model Dev., 15, 6873–6889, https://doi.org/10.5194/gmd-15-6873-2022, https://doi.org/10.5194/gmd-15-6873-2022, 2022
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The sea surface temperature (SST) is highly influenced by the transfer of energy driven by turbulent air–sea fluxes (TASFs). In the NEMO ocean general circulation model, TASFs are computed by means of bulk formulas. Bulk formulas require the choice of a given bulk parameterization, which influences the magnitudes of the TASFs. Our results show that parameterization-related SST differences are primarily sensitive to the wind stress differences across parameterizations.
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
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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.
David E. Gwyther, Colette Kerry, Moninya Roughan, and Shane R. Keating
Geosci. Model Dev., 15, 6541–6565, https://doi.org/10.5194/gmd-15-6541-2022, https://doi.org/10.5194/gmd-15-6541-2022, 2022
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The ocean current flowing along the southeastern coast of Australia is called the East Australian Current (EAC). Using computer simulations, we tested how surface and subsurface observations might improve models of the EAC. Subsurface observations are particularly important for improving simulations, and if made in the correct location and time, can have impact 600 km upstream. The stability of the current affects model estimates could be capitalized upon in future observing strategies.
Giorgio Micaletto, Ivano Barletta, Silvia Mocavero, Ivan Federico, Italo Epicoco, Giorgia Verri, Giovanni Coppini, Pasquale Schiano, Giovanni Aloisio, and Nadia Pinardi
Geosci. Model Dev., 15, 6025–6046, https://doi.org/10.5194/gmd-15-6025-2022, https://doi.org/10.5194/gmd-15-6025-2022, 2022
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The full exploitation of supercomputing architectures requires a deep revision of the current climate models. This paper presents the parallelization of the three-dimensional hydrodynamic model SHYFEM (System of HydrodYnamic Finite Element Modules). Optimized numerical libraries were used to partition the model domain and solve the sparse linear system of equations in parallel. The performance assessment demonstrates a good level of scalability with a realistic configuration used as a benchmark.
Young-Kwang Choi, Fengyan Shi, Matt Malej, Jane M. Smith, James T. Kirby, and Stephan T. Grilli
Geosci. Model Dev., 15, 5441–5459, https://doi.org/10.5194/gmd-15-5441-2022, https://doi.org/10.5194/gmd-15-5441-2022, 2022
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The multi-grid-nesting technique is an important methodology used for modeling transoceanic tsunamis and coastal effects. In this study, we developed a two-way nesting interface in a multi-grid-nesting system for the Boussinesq wave model FUNWAVE-TVD. The interface acts as a
backboneof the nesting framework, handling data input, output, time sequencing, and internal interactions between grids at different scales.
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.
Benoît Pasquier, Sophia K. V. Hines, Hengdi Liang, Yingzhe Wu, Steven L. Goldstein, and Seth G. John
Geosci. Model Dev., 15, 4625–4656, https://doi.org/10.5194/gmd-15-4625-2022, https://doi.org/10.5194/gmd-15-4625-2022, 2022
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Neodymium isotopes in seawater have the potential to provide key information about ocean circulation, both today and in the past. This can shed light on the underlying drivers of global climate, which will improve our ability to predict future climate change, but uncertainties in our understanding of neodymium cycling have limited use of this tracer. We present a new model of neodymium in the modern ocean that runs extremely fast, matches observations, and is freely available for development.
Pedro Duarte, Jostein Brændshøi, Dmitry Shcherbin, Pauline Barras, Jon Albretsen, Yvonne Gusdal, Nicholas Szapiro, Andreas Martinsen, Annette Samuelsen, Keguang Wang, and Jens Boldingh Debernard
Geosci. Model Dev., 15, 4373–4392, https://doi.org/10.5194/gmd-15-4373-2022, https://doi.org/10.5194/gmd-15-4373-2022, 2022
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Sea ice models are often implemented for very large domains beyond the regions of sea ice formation, such as the whole Arctic or all of Antarctica. In this study, we implement changes in the Los Alamos Sea Ice Model, allowing it to be implemented for relatively small regions within the Arctic or Antarctica and yet considering the presence and influence of sea ice outside the represented areas. Such regional implementations are important when spatially detailed results are required.
Elias J. Hunter, Heidi L. Fuchs, John L. Wilkin, Gregory P. Gerbi, Robert J. Chant, and Jessica C. Garwood
Geosci. Model Dev., 15, 4297–4311, https://doi.org/10.5194/gmd-15-4297-2022, https://doi.org/10.5194/gmd-15-4297-2022, 2022
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ROMSPath is an offline particle tracking model tailored for use with output from Regional Ocean Modeling System (ROMS) simulations. It is an update to an established system, the Lagrangian TRANSport (LTRANS) model, including a number of improvements. These include a modification of the model coordinate system which improved accuracy and numerical efficiency, and added functionality for nested grids and Stokes drift.
Alexander Barth, Aida Alvera-Azcárate, Charles Troupin, and Jean-Marie Beckers
Geosci. Model Dev., 15, 2183–2196, https://doi.org/10.5194/gmd-15-2183-2022, https://doi.org/10.5194/gmd-15-2183-2022, 2022
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Earth-observing satellites provide routine measurement of several ocean parameters. However, these datasets have a significant amount of missing data due to the presence of clouds or other limitations of the employed sensors. This paper describes a method to infer the value of the missing satellite data based on a convolutional autoencoder (a specific type of neural network architecture). The technique also provides a reliable error estimate of the interpolated value.
Olivier Sulpis, Matthew P. Humphreys, Monica M. Wilhelmus, Dustin Carroll, William M. Berelson, Dimitris Menemenlis, Jack J. Middelburg, and Jess F. Adkins
Geosci. Model Dev., 15, 2105–2131, https://doi.org/10.5194/gmd-15-2105-2022, https://doi.org/10.5194/gmd-15-2105-2022, 2022
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A quarter of the surface of the Earth is covered by marine sediments rich in calcium carbonates, and their dissolution acts as a giant antacid tablet protecting the ocean against human-made acidification caused by massive CO2 emissions. Here, we present a new model of sediment chemistry that incorporates the latest experimental findings on calcium carbonate dissolution kinetics. This model can be used to predict how marine sediments evolve through time in response to environmental perturbations.
Alisée A. Chaigneau, Guillaume Reffray, Aurore Voldoire, and Angélique Melet
Geosci. Model Dev., 15, 2035–2062, https://doi.org/10.5194/gmd-15-2035-2022, https://doi.org/10.5194/gmd-15-2035-2022, 2022
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Climate-change-induced sea level rise is a major threat for coastal and low-lying regions. Projections of coastal sea level changes are thus of great interest for coastal risk assessment and have significantly developed in recent years. In this paper, the objective is to provide high-resolution (6 km) projections of sea level changes in the northeastern Atlantic region bordering western Europe. For that purpose, a regional model is used to refine existing coarse global projections.
Victor Onink, Erik van Sebille, and Charlotte Laufkötter
Geosci. Model Dev., 15, 1995–2012, https://doi.org/10.5194/gmd-15-1995-2022, https://doi.org/10.5194/gmd-15-1995-2022, 2022
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Turbulent mixing is a vital process in 3D modeling of particle transport in the ocean. However, since turbulence occurs on very short spatial scales and timescales, large-scale ocean models generally have highly simplified turbulence representations. We have developed parametrizations for the vertical turbulent transport of buoyant particles that can be easily applied in a large-scale particle tracking model. The predicted vertical concentration profiles match microplastic observations well.
Gaston Irrmann, Sébastien Masson, Éric Maisonnave, David Guibert, and Erwan Raffin
Geosci. Model Dev., 15, 1567–1582, https://doi.org/10.5194/gmd-15-1567-2022, https://doi.org/10.5194/gmd-15-1567-2022, 2022
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To be efficient on supercomputers, software must be high-performance at computing many concurrent tasks. Communications between tasks is often necessary but time consuming, and ocean modelling software NEMO 4.0 is no exception.
In this work we describe approaches enabling fewer communications, an optimization to share the workload more equally between tasks and a new flexible configuration to assess NEMO's performance easily.
Cited articles
Aagaard, K., and Carmack, E. C.: The role of sea ice and other fresh-water in the Arctic circulation, J. Geophys. Res., 94, 14485–14498, 1989.
Aagaard, K., Swift, J. H., and Carmack, E.: Thermohaline circulation in the Arctic mediterranean seas, J. Geophys. Res.-Oceans, 90, 4833–4846, 1985.
Aksenov, Y., Ivanov, V. V., Nurser, A. J. G., Bacon, S., Polyakov, I. V., Coward, A. C., Naveira-Garabato, A. C., and Beszczynska-Moeller, A.: The Arctic Circumpolar Boundary Current, J. Geophys. Res.-Oceans, 116, C09017, https://doi.org/10.1029/2003GL018080, 2011.
Aksenov, Y., Karcher, M., A. Proshutinsky, R. Gerdes, B. de Cuevas, E. Golubeva, F. Kauker, A. T. Nguyen, G. A. Platov, M. Wadley, E. Watanabe, A. C. Coward, and A. J. G. Nurser: Arctic pathways of Pacific Water: Arctic Ocean model intercomparison experiments, J. Geophys. Res.-Oceans, 121, 27–59, 2016.
Arrigo, K. R. and van Dijken, G. L.: Continued increases in Arctic Ocean primary production, Prog. Oceanogr., 136, 60–70, 2015.
Arzel, O., Fichefet, T., Goosse, H., and Dufresne, J.-L.: Causes and impacts of changes in the Arctic freshwater budget during the 20th and 21st centuries in an AOGCM, Clim. Dynam., 30, 37–58, 2008.
Beszczynska-Moeller, 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. Science, 69, 852–863, 2012.
Biastoch, A., Sein, D., Durgadoo, J. V., Wang, Q., and Danilov, S.: Simulating the Agulhas system in global ocean models – nesting vs. multi-resolution unstructured meshes, Ocean Model., 121, 117–131, https://doi.org/10.1016/j.ocemod.2017.12.002, 2018.
Carmack, E. C., Yamamoto-Kawai, M., Haine, T. W. N., Bacon, S., Bluhm, B. A., Lique, C., Melling, H., Polyakov, I. V., Straneo, F., Timmermans, M.-L., and Williams, W. J.: Freshwater and its role in the Arctic Marine System: Sources, disposition, storage, export, and physical and biogeochemical consequences in the Arctic and global oceans, J. Geophys. Res.-Biogeo., 121, 675–717, 2016.
Cavalieri, D. J. and Parkinson, C. L.: Arctic sea ice variability and trends, 1979–2010, The Cryosphere, 6, 881–889, https://doi.org/10.5194/tc-6-881-2012, 2012.
Chassignet, E. P., Hurlburt, H. E., Metzger, E. J., Smedstad, O. M., Cummings, J. A., Halliwell, G. R., Bleck, R., Baraille, R., Wallcraft, A. J., Lozano, C., Tolman, H. L., Srinivasan, A., Hankin, S., Cornillon, P., Weisberg, R., Barth, A., He, R., Werner, F., and Wilkin, J.: U.S. GODAE: Global Ocean Prediction with the HYbrid Coordinate Ocean Model (HYCOM), Oceanography, 22, 64–75, 2009.
Comiso, J. C.: Large decadal decline in the Arctic multiyear ice cover, J. Clim., 25, 1176–1193, 2012.
Curry, B., Lee, C. M., Petrie, B., Moritz, R. E., and Kwok, R.: Multiyear volume, liquid freshwater, and sea ice transports through Davis Strait, 2004–2010, J. Phys. Oceanogr., 44, 1244–1266, 2014.
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, 2009.
Danabasoglu, G., Yeager, S. G., Bailey, D., et al.: North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase {II} (CORE-II) – part i: Mean states, Ocean Model., 73, 76–107, 2014.
Danilov, S., Kivman, G., and Schroeter, J.: A finite-element ocean model: principles and evaluation, Ocean Model., 6, 125–150, 2004.
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.
de Steur, L., Hansen, E., Mauritzen, C., Beszczynska-Möller, A., and Fahrbach, E.: Impact of recirculation on the East Greenland Current in Fram Strait: Results from moored current meter measurements between 1997 and 2009, Deep-Sea Res. Pt. I, 92, 26–40, 2014.
Dickson, R., Rudels, B., Dye, S., Karcher, M., Meincke, J., and Yashayaev, I.: Current estimates of freshwater flux through Arctic and subarctic seas, Prog. Oceanogr., 73, 210–230, 2007.
Dmitrenko, I. A., Polyakov, I. V., Kirillov, S. A., Timokhov, L. A., Frolov, I. E., Sokolov, V. T., Simmons, H. L., Ivanov, V. V., and Walsh, D.: Toward a warmer arctic ocean: Spreading of the early 21st century Atlantic Water warm anomaly along the Eurasian Basin margins, J. Geophys. Res.-Oceans, 113, C05023, https://doi.org/10.1029/2003GL018080, 2008.
Dmitrenko, I. A., Ivanov, V. V., Kirillov, S. A., Vinogradova, E. L., Torres-Valdes, S., and Bauch, D.: Properties of the Atlantic derived halocline waters over the Laptev Sea continental margin: Evidence from 2002 to 2009, J. Geophys. Res.-Oceans, 116, C10024, https://doi.org/10.1029/2011JC007269, 2011.
Dmitrenko, I. A., Rudels, B., Kirillov, S. A., Aksenov, Y. O., Lien, V. S., Ivanov, V. V., Schauer, U., Polyakov, I. V., Coward, A., and Barber, D. G.: Atlantic water flow into the Arctic Ocean through the St. Anna Trough in the northern Kara Sea, J. Geophys. Res.-Oceans, 120, 5158–5178, 2015.
Duffy, P. B., Eby, M., and Weaver, A. J.: Effects of sinking of salt rejected during formation of sea ice on results of an ocean-atmosphere-sea ice climate model, Geophys. Res. Lett., 26, 1739–1742, 1999.
Dupont, F., Higginson, S., Bourdallé-Badie, R., Lu, Y., Roy, F., Smith, G. C., Lemieux, J.-F., Garric, G., and Davidson, F.: A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans, Geosci. Model Dev., 8, 1577–1594, https://doi.org/10.5194/gmd-8-1577-2015, 2015.
Fetterer, F., K. Knowles, W. Meier, and M. Savoie: Sea Ice Index, Boulder, Colorado USA: National Snow and Ice Data Center, Digital media, updated daily, available at: https://nsidc.org/, 2016.
Fieg, K., Gerdes, R., Fahrbach, E., Beszczynska-Möller, A., and Schauer, U.: Simulation of oceanic volume transports through Fram Strait 1995–2005, Ocean Dynam., 60, 491–502, 2010.
Gascard, J.-C., Kergomard, C., Jeannin, P.-F., and Fily, M.: Diagnostic study of the Fram Strait marginal ice zone during summer from 1983 and 1984 Marginal Ice Zone Experiment Lagrangian observations, J. Geophys. Res.-Oceans, 93, 3613–3641, 1988.
Gent, P. R. and McWilliams, J. C.: Isopycnal mixing in ocean circulation models, J. Phys. Oceanogr., 20, 150–155, 1990.
Gerdes, R., Karcher, M. J., Kauker, F., and Schauer, U.: Causes and development of repeated Arctic Ocean warming events, Geophys. Res. Lett., 30, 1980, https://doi.org/10.1029/2003GL018080, 2003.
Giles, K. A., Laxon, S. W., Ridout, A. L., Wingham, D. J., and Bacon, S.: Western Arctic Ocean freshwater storage increased by wind-driven spin-up of the Beaufort Gyre, Nat. Geosci., 5, 194–197, 2012.
Goosse, H., Fichefet, T., and Campin, J. M.: The effects of the water flow through the Canadian Archipelago in a global ice-ocean model, Geophys. Res. Lett., 24, 1507–1510, 1997.
Griffies, S., Winton, M., Samuels, B., Danabasoglu, G., Yeager, S., Marlsand, S., Drange, H., and Bentsen, M.: Datasets and protocol for the CLIVAR WGOMD Coordinated Ocean-sea ice Reference Experiments (COREs), Tech. Rep. 21, WCRP Report, 2012.
Griffies, S. M.: The Gent-Mcwilliams skew flux, J. Phys. Oceanogr., 28, 831–841, 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. S., 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, 2009.
Griffies, S. M., Yin, J., Durack, P. J., et al.: 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, 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., and Zhang, R.: Impacts on Ocean Heat from Transient Mesoscale Eddies in a Hierarchy of Climate Models, J. Climate, 28, 952–977, 2015.
Haarsma, R. J., Roberts, M. J., Vidale, P. L., Senior, C. A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fuckar, 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.
Haid, V. and Timmermann, R.: Simulated heat flux and sea ice production at coastal polynyas in the southwestern Weddell Sea, J. Geophys. Res.-Oceans, 118, 2640–2652, 2013.
Haine, T., Curry, B., Gerdes, R., Hansen, E., Karcher, M., Lee, C., Rudels, B., Spreen, G., de Steur, L., Stewart, K., and Woodgate, R.: Arctic freshwater export: Status, mechanisms, and prospects, Global Planet. Change, 125, 13–35, 2015.
Hakkinen, S.: A simulation of thermohaline effects of a great salinity anomaly, J. Climate, 12, 1781–1795, 1999.
Hattermann, T., Isachsen, P. E., von Appen, W.-J., Albretsen, J., and Sundfjord, A.: Eddy-driven recirculation of Atlantic Water in Fram Strait, Geophys. Res. Lett., 43, 3406–3414, 2016.
Holland, M. M., Cecilia, M. B., Eby, M., and Weavr, A. J.: The role of ice–ocean interactions in the variability of the North Atlantic thermohaline circulation, J. Climate, 14, 656–675, 2001.
Holloway, G., Dupont, F., Golubeva, E., Haekkinen, S., Hunke, E., Jin, M., Karcher, M., Kauker, F., Maltrud, M., Maqueda, M. A. M., Maslowski, W., Platov, G., Stark, D., Steele, M., Suzuki, T., Wang, J., and Zhang, J.: Water properties and circulation in Arctic Ocean models, J. Geophys. Res.-Oceans, 112, C04S03, https://doi.org/10.1029/2006JC003642, 2007.
Hunke, E. and Dukowicz, J.: An elastic-viscous-plastic model for sea ice dynamics, J. Phys. Oceanogr., 27, 1849–1867, 1997.
Ilicak, M., Drange, H., Wang, Q., et al.: An assessment of the Arctic Ocean in a suite of interannual CORE-II simulations – Part III: Hydrography and fluxes, Ocean Model., 100, 141–161, 2016.
Iovino, D., Masina, S., Storto, A., Cipollone, A., and Stepanov, V. N.: A 1∕16° eddying simulation of the global NEMO sea-ice-socean system, Geosci. Model Dev., 9, 2665–2684, https://doi.org/10.5194/gmd-9-2665-2016, 2016.
Jahn, A. and Holland, M. M.: Implications of arctic sea ice changes for North Atlantic deep convection and the meridional overturning circulation in CCSM4-CMIP5 simulations, Geophys. Res. Lett., 40, 1206–1211, 2013.
Jahn, A., Aksenov, Y., de Cuevas, B. A., de Steur, L., Hakkinen, S., Hansen, E., Herbaut, C., Houssais, M. N., Karcher, M., Kauker, F., Lique, C., Nguyen, A., Pemberton, P., Worthen, D., and Zhang, J.: Arctic Ocean freshwater: How robust are model simulations?, J. Geophys. Res.-Oceans, 117, C00D16, https://doi.org/10.1029/2012JC007907, 2012.
Jakobsson, M., Macnab, R., Mayer, L., Anderson, R., Edwards, M., Hatzky, J., Schenke, H. W., and Johnson, P.: An improved bathymetric portrayal of the Arctic Ocean: Implications for ocean modeling and geological, geophysical and oceanographic analyses, Geophys. Res. Lett., 35, L07602, https://doi.org/10.1029/2008GL033520, 2008.
Johnson, M., Proshutinsky, A., Aksenov, Y., Nguyen, A. T., Lindsay, R., Haas, C., Zhang, J., Diansky, N., Kwok, R., Maslowski, W., Haekkinen, S., Ashik, I., and de Cuevas, B.: Evaluation of Arctic sea ice thickness simulated by Arctic Ocean Model Intercomparison Project models, J. Geophys. Res.-Oceans, 117, C00D13, https://doi.org/10.1029/2011JC007257, 2012.
Jungclaus, J. H., Haak, H., Latif, M., and Mikolajewicz, U.: Arctic-North Atlantic interactions and multidecadal variability of the meridional overturning circulation, J. Climate, 18, 4013–4031, 2005.
Karcher, M., Kauker, F., Gerdes, R., Hunke, E., and Zhang, J.: On the dynamics of Atlantic Water circulation in the Arctic Ocean, J. Geophys. Res.-Oceans, 112, C04S02, https://doi.org/10.1029/2006JC003630, 2007.
Karcher, M., Beszczynska-Moeller, A., Kauker, F., Gerdes, R., Heyen, S., Rudels, B., and Schauer, U.: Arctic Ocean warming and its consequences for the Denmark Strait overflow, J. Geophys. Res.-Oceans, 116, C02037, https://doi.org/10.1029/2010JC006265, 2011.
Karcher, M. J. and Oberhuber, J. M.: Pathways and modification of the upper and intermediate waters of the Arctic Ocean, J. Geophys. Res.-Oceans, 107, 3049, https://doi.org/10.1029/2000JC000530, 2002.
Karcher, M. J., Gerdes, R., Kauker, F., and Koberle, C.: Arctic warming: Evolution and spreading of the 1990s warm event in the Nordic seas and the Arctic Ocean, J. Geophys. Res.-Oceans, 108, 3034, https://doi.org/10.1029/2001JC001265, 2003.
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, 2015.
Koldunov, N. V., Serra, N., Köhl, A., Stammer, D., Henry, O., Cazenave, A., Prandi, P., Knudsen, P., Andersen, O. B., Gao, Y., and Johannessen, J.: Multimodel simulations of Arctic Ocean sea surface height variability in the period 1970–2009, J. Geophys. Res.-Oceans, 119, 8936–8954, 2014.
Kwok, R., Cunningham, G. F., Wensnahan, M., Rigor, I., Zwally, H. J., and Yi, D.: Thinning and volume loss of the Arctic Ocean sea ice cover: 2003–2008, J. Geophys. Res.-Oceans, 114, C07005, https://doi.org/10.1029/2009JC005312, 2009.
Large, W. G. and Yeager, S. G.: The global climatology of an interannually varying air-sea flux data set, Clim. Dynam., 33, 341–364, 2009.
Large, W. G., McWilliams, J. C., and S. C. Doney: Oceanic vertical mixing – a review and a model with a nonlocal boundary-layer parameterization, Rev. Geophys., 32, 363–403, 1994.
Laxon, S. W., Giles, K. A., Ridout, A. L., Wingham, D. J., Willatt, R., Cullen, R., Kwok, R., Schweiger, A., Zhang, J., Haas, C., Hendricks, S., Krishfield, R., Kurtz, N., Farrell, S., and Davidson, M.: CryoSat-2 estimates of Arctic sea ice thickness and volume, Geophys. Res. Lett., 40, 732–737, 2013.
Li, Z., Saad, Y., and Sosonkina, M.: pARMS: a parallel version of the algebraic recursive multilevel solver, Numer. Linear Algebr., 10, 485–509, 2003.
Lique, C. and Steele, M.: Where can we find a seasonal cycle of the Atlantic water temperature within the Arctic Basin?, J. Geophys. Res.-Oceans, 117, C03026, https://doi.org/10.1029/2011JC007612, 2012.
Lique, C. and Steele, M.: Seasonal to decadal variability of Arctic Ocean heat content: A model-based analysis and implications for autonomous observing systems, J. Geophys. Res.-Oceans, 118, 1673–1695, 2013.
Löhner, R., Morgan, K., Peraire, J., and Vahdati, M.: Finite-element flux-corrected transport (FEM-FCT) for the Euler and Navier-Stokes equations, Int. J. Numer. Methods Fluids, 7, 1093–1109, 1987.
Luneva, M. V., Aksenov, Y., Harle, J. D., and Holt, J. T.: The effects of tides on the water mass mixing and sea ice in the Arctic Ocean, J. Geophys. Res.-Oceans, 120, 6669–6699, 2015.
Manucharyan, G. E., Spall, M. A., and Thompson, A. F.: A theory of the wind-driven Beaufort Gyre variability, J. Phys. Oceanogr., 46, 3263–3278, 2016.
Marnela, M., Rudels, B., Houssais, M.-N., Beszczynska-Möller, A., and Eriksson, P. B.: Recirculation in the Fram Strait and transports of water in and north of the Fram Strait derived from CTD data, Ocean Sci., 9, 499–519, https://doi.org/10.5194/os-9-499-2013, 2013.
Maslowski, W., Marble, D., Walczowski, W., Schauer, U., Clement, J. L., and Semtner, A. J.: On climatological mass, heat, and salt transports through the Barents sea and Fram strait from a pan-Arctic coupled ice-ocean model simulation, J. Geophys. Res.-Oceans, 109, C03032, https://doi.org/10.1029/2001JC001039, 2004.
McPhee, M. G., Proshutinsky, A., Morison, J. H., Steele, M., and Alkire, M. B.: Rapid change in freshwater content of the Arctic Ocean, Geophys. Res. Lett., 36, L10602, https://doi.org/10.1029/2009GL037525, 2009.
Melling, H.: Exchanges of freshwater through the shallow straits of the North American Arctic, in: The Freshwater Budget of the Arctic Ocean, edited by: Lewis, E. L., Jones, E. P., Lemke, P., Prowse, T. D., and Wadhams, P., Springer, New York, 479–502, 2000.
Metzger, E. J., Smedstad, O. M., Thoppil, P. G., Hurlburt, H. E., Cummings, J. A., Wallcraft, A. J., Zamudio, L., Franklin, D. S., Posey, P. G., Phelps, M. W., Hogan, P. J., Bub, F. L., and DeHaan, C. J.: US Navy operational global ocean and Arctic ice prediction systems, Oceanography, 27, 32–43, 2014.
Morison, J., Kwok, R., Peralta-Ferriz, C., Alkire, M., Rigor, I., Andersen, R., and Steele, M.: Changing Arctic Ocean freshwater pathways, Nature, 481, 66–70, 2012.
Nguyen, A. T., Menemenlis, D., and Kwok, R.: Improved modeling of the Arctic halocline with a subgrid-scale brine rejection parameterization, J. Geophys. Res.-Oceans, 114, C11014, https://doi.org/10.1029/2008JC005121, 2009.
Nurser, A. J. G. and Bacon, S.: The Rossby radius in the Arctic Ocean, Ocean Sci., 10, 967–975, https://doi.org/10.5194/os-10-967-2014, 2014.
Oke, P. R., Griffin, D. A., Schiller, A., Matear, R. J., Fiedler, R., Mansbridge, J., Lenton, A., Cahill, M., Chamberlain, M. A., and Ridgway, K.: Evaluation of a near-global eddy-resolving ocean model, Geosci. Model Dev., 6, 591–615, https://doi.org/10.5194/gmd-6-591-2013, 2013.
Orvik, K. A. and Niiler, P.: Major pathways of Atlantic water in the northern North Atlantic and Nordic Seas toward Arctic, Geophys. Res. Lett., 29, 1896, https://doi.org/10.1029/2002GL015002, 2002.
Parkinson, C. and Washington, W.: A large-scale numerical model of sea ice, J. Geophys. Res.-Oceans, 84, 311–337, 1979.
Polyakov, I., Timokhov, L., Alexeev, V., Bacon, S., Dmitrenko, I., Fortier, L., Frolov, I., Gascard, J., Hansen, E., Ivanov, V., Laxon, S., Mauritzen C., Perovich, D., Shimada, K., Simmons, H., Sokolov, V., Steele, M., and Toole, J.: Arctic ocean warming contributes to reduced polar ice cap, J. Phys. Oceanogr., 40, 2743–2756, 2010.
Polyakov, I. V., Pnyushkov, A. V., and Timokhov, L. A.: Warming of the intermediate Atlantic Water of the Arctic Ocean in the 2000s, J. Climate, 25, 8362–8370, 2012.
Polyakov, I. V., Pnyushkov, A. V., Rember, R., Padman, L., Carmack, E. C., and Jackson, J. M.: Winter convection transports Atlantic Water heat to the surface layer in the eastern Arctic Ocean, J. Phys. Oceanogr., 43, 2142–2155, 2013a.
Polyakov, I. V., Bhatt, U. S., Walsh, J. E., Abrahamsen, E. P., Pnyushkov, A. V., and Wassmann, P. F.: Recent oceanic changes in the Arctic in the context of long-term observations, Ecol. Appl., 23, 1745–1764, 2013b.
Proshutinsky, A. and Kowalik, Z.: Preface to special section on Arctic Ocean Model Intercomparison Project (AOMIP) studies and results, J. Geophys. Res.-Oceans, 112, C04S01, https://doi.org/10.1029/2006JC004017, 2007.
Proshutinsky, A., Bourke, R. H., and McLaughlin, F. A.: The role of the Beaufort Gyre in Arctic climate variability: Seasonal to decadal climate scales, Geophys. Res. Lett., 29, 2100, https://doi.org/10.1029/2002GL015847, 2002.
Proshutinsky, A., Krishfield, R., Timmermans, M.-L., Toole, J., Carmack, E., McLaughlin, F., Williams, W. J., Zimmermann, S., Itoh, M., and Shimada, K.: Beaufort Gyre freshwater reservoir: State and variability from observations, J. Geophys. Res.-Oceans, 114, C00A10, https://doi.org/10.1029/2008JC005104, 2009.
Proshutinsky, A., Aksenov, Y., Kinney, J. C., Gerdes, R., Golubeva, E., Holland, D., Holloway, G., Jahn, A., Johnson, M., Popova, E., Steele, M., and Watanabe, E.: Recent Advances in Arctic Ocean Studies Employing Models from the Arctic Ocean Model Intercomparison Project, Oceanography, 24, 102–113, 2011.
Quadfasel, D., Gascard, J.-C., and Koltermann, K.-P.: Large-scale oceanography in Fram Strait during the 1984 Marginal Ice Zone Experiment, J. Geophys. Res.-Oceans, 92, 6719–6728, 1987.
Rabe, B., Karcher, M., Schauer, U., Toole, J. M., Krishfield, R. A., Pisarev, S., Kauker, F., Gerdes, R., and Kikuchi, T.: Assessment of Arctic Ocean freshwater content changes from the 1990s to the 2006-2008 period, Deep-Sea Res. Pt. I, 58, 173–185, 2011.
Rabe, B., Karcher, M., Kauker, F., Schauer, U., Toole, J. M., Krishfield, R. A., Pisarev, S., Kikuchi, T., and Su, J.: Arctic ocean basin liquid freshwater storage trend 1992–2012, Geophys. Res. Lett., 41, 961–968, 2014.
Redi, M. H.: Oceanic isopycnal mixing by coordinate rotation, J. Phys. Oceanogr., 12, 1154–1158, 1982.
Rippeth, T. P., Lincoln, B. J., Lenn, Y.-D., Green, J. A. M., Sundfjord, A., and Bacon, S.: Tide-mediated warming of Arctic halocline by Atlantic heat fluxes over rough topography, Nat. Geosci., 8, 191–194, 2015.
Roach, A. T., Aagaard, K., Pease, C., Salo, S. A., Weingartner, T., Pavlov, V., and Kulakov, M.: Direct measurements of transport and water properties through the Bering Strait, J. Geophys. Res.-Oceans, 100, 18443–18457, 1995.
Rudels, B.: Arctic Ocean circulation, processes and water masses: A description of observations and ideas with focus on the period prior to the International Polar Year 2007–2009, Prog. Oceanogr., 132, 22–67, 2015.
Rudels, B. and Friedrich, H.: The transformation of the Atlantic Water in the Arctic Ocean and their significance for the freshwaer budget, in: The Freshater Budget of the Arctic Ocean, edited by: Lewis, E. L., Jones, E. P., Lemke, P., Prowse, T. D., and Wadhams, P., Kluwer, 503–532, 2000.
Rudels, B., Jones, E. P., Anderson, L. G., and Kattner, G.: On the intermediate depth waters of the Arctic Ocean, in: The Polar Oceans and Their Role in Shaping the Global Environment, edited by: Johannessen, O. M., Muench, R. D., and Overland, J. E., American Geophysical Union, 33–46,, 1994.
Rudels, B., Anderson, L. G., and Jones E. P.: Formation and evolution of the surface mixed layer and halocline of the Arctic Ocean, J. Geophys. Res.-Oceans, 101, 8807–8821, 1996.
Saloranta, T. M. and Haugan, P. M.: Interannual variability in the hydrography of Atlantic water northwest of Svalbard, J. Geophys. Res.-Oceans, 106, 13931–13943, 2001.
Schauer, U., Rudels, B., Jones, E. P., Anderson, L. G., Muench, R. D., Björk, G., Swift, J. H., Ivanov, V., and Larsson, A.-M.: Confluence and redistribution of Atlantic water in the Nansen, Amundsen and Makarov basins, Ann. Geophys., 20, 257–273, https://doi.org/10.5194/angeo-20-257-2002, 2002.
Schauer, U., Beszczynska-Moeller, A., Walczowski, W., Fahrbach, E., Piechura, J., and Hansen, E.: Variation of measured heat flow through the Fram Strait between 1997 and 2006, in: Arctic-Subarctic Ocean Fluxes: Defining the Role of the Northern Seas in Climate, edited by: Dickson, R. R., Meincke, J., and Rhines, P., Springer, 65–85, 2008.
Scholz, P., Lohmann, G., Wang, Q., and Danilov, S.: Evaluation of a finite-element sea-ice ocean model (fesom) set-up to study the interannual to decadal variability in the deep-water formation rates, Ocean Dynam., 63, 347–370, 2013.
Schweiger, A., Lindsay, R., Zhang, J., Steele, M., Stern, H., and Kwok, R.: Uncertainty in modeled Arctic sea ice volume, J. Geophys. Res.-Oceans, 116, C00D06, https://doi.org/10.1029/2011JC007084, 2011.
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, 2016.
Sein, D.V., Koldunov, N. V., Danilov, S., Wang, Q., Sidorenko, D., Fast, I., Rackow, T., Cabos, W., and Jung, T.: Ocean modeling on a mesh with resolution following the local Rossby radius, J. Adv. Model. Earth Sy., 9, 2601–2614, 2017.
Serreze, M. C. and Barry, R. G.: Processes and impacts of Arctic amplification: A research synthesis, Global Planet. Change, 77, 85–96, 2011.
Serreze, M. C., Barrett, A. P., Slater, A. G., Woodgate, R. A., Aagaard, K., Lammers, R. B., Steele, M., Moritz, R., Meredith, M., and Lee, C. M.: The large-scale freshwater cycle of the Arctic, J. Geophys. Res.-Oceans, 111, C11010, https://doi.org/10.1029/2005JC003424, 2006.
Skagseth, Ø., Furevik, T., Ingvaldsen, R., Mork, H. L. K., Orvik, K., and Ozhigi, V.: Volume and heat transports to the Arctic Ocean via the Norwegian and Barents Seas, in: Arctic-Subarctic Ocean Fluxes: Defining the Role of the Northern Seas in Climate, edited by: Dickson, R. R., Meincke, J., and Rhines, P., Springer, 45–64, 2008.
Smagorinsky, J.: General circulation experiments with the primitive equations: I. the basic experiment, Mon. Weather Rev., 91, 99–164, 1963.
Smedsrud, L. H., Ingvaldsen, R., Nilsen, J. E. Ø., and Skagseth, Ø.: Heat in the Barents Sea: transport, storage, and surface fluxes, Ocean Sci., 6, 219–234, https://doi.org/10.5194/os-6-219-2010, 2010.
Smedsrud, L. H., Esau, I., Ingvaldsen, R. B., Eldevik, T., Haugan, P. M., Li, C., Lien, V. S., Olsen, A., Omar, A. M., Ottera, O. H.,, Risebrobakken, Sando, A. B., Semenov, V. A., and Sorokina, S. A.: The role of the Barents Sea in the Arctic climate system, Rev. Geophys., 51, 415–449, 2013.
Smedsrud, L. H., Halvorsen, M. H., Stroeve, J. C., Zhang, R., and Kloster, K.: Fram Strait sea ice export variability and September Arctic sea ice extent over the last 80 years, The Cryosphere, 11, 65–79, https://doi.org/10.5194/tc-11-65-2017, 2017.
Steele, M., Morley, R., and Ermold, W.: PHC: A global ocean hydrography with a high quality Arctic Ocean, J. Climate, 14, 2079–2087, 2001.
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.
Timmermann, R., Danilov, S., Schröter, J., Böning, C., Sidorenko, D. and Rollenhagen, K.: Ocean circulation and sea ice distribution in a finite element global sea ice-ocean model, Ocean Model., 27, 114–129, 2009.
Timmermann, R., Wang, Q., and Hellmer, H.: Ice-shelf basal melting in a global finite-element sea-ice/ice-shelf/ocean model, Ann. Glaciol., 53, 303–314, 2012.
Tremblay, J.-É., Anderson, L. G., Matrai, P., Coupel, P., Bélanger, S., Michel, C., and Reigstad, M.: Global and regional drivers of nutrient supply, primary production and CO2 drawdown in the changing Arctic Ocean, Prog. Oceanogr., 139, 171–196, 2015.
Tschudi, M. A., Curry, J. A., and Maslanik, J. A.: Characterization of springtime leads in the Beaufort/Chukchi Seas from airborne and satellite observations during FIRE/SHEBA, J. Geophys. Res.-Oceans, 107, 8034, https://doi.org/10.1029/2000JC000541, 2002.
Vihma, T.: Effects of Arctic sea ice decline on weather and climate: A review, Surv. Geophys., 35, 1175–1214, 2014.
von Appen, W.-J., Schauer, U., Hattermann, T., and Beszczynska-Möller, A.: Seasonal cycle of mesoscale instability of the West Spitsbergen Current, J. Phys. Oceanogr., 46, 1231–1254, 2016.
von Storch, J.-S., Eden, C., Fast, I., Haak, H., Hernández-Deckers, D., Maier-Reimer, E., Marotzke, J., and Stammer, D.: An Estimate of the Lorenz Energy Cycle for the World Ocean Based on the STORM/NCEP Simulation, J. Phys. Oceanogr., 42, 2185–2205, 2012.
Wadley, M. R. and Bigg, G. R.: Impact of flow through the Canadian Archipelago and Bering Strait on the north Atlantic and Arctic circulation: An ocean modelling study, Q. J. Roy. Meteor. Soc., 128, 2187–2203, 2002.
Wallace, J. M., Held, I. M., Thompson, D. W. J., Trenberth, K. E., and Walsh, J. E.: Global warming and winter weather, Science, 343, 729–730, 2014.
Wang, Q., Danilov, S., and Schröter, J.: Finite Element Ocean circulation Model based on triangular prismatic elements, with application in studying the effect of vertical discretization, J. Geophys. Res.-Oceans, 113, C05015, https://doi.org/10.1029/2007JC004482, 2008.
Wang, Q., Danilov, S., Fahrbach, E., Schröter, J., and Jung, T.: On the impact of wind forcing on the seasonal variability of Weddell Sea Bottom Water transport, Geophys. Res. Lett., 39, L06603, https://doi.org/10.1029/2012GL051198, 2012.
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., et al.: 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, 2016a.
Wang, Q., Ilicak, M., Gerdes, R., et al.: An assessment of the Arctic Ocean in a suite of interannual CORE-II simulations – Part II: Liquid freshwater, Ocean Model., 99, 65–90, 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, 2016c.
Wekerle, C., Wang, Q., Danilov, S., Jung, T., and Schröter, J.: The Canadian Arctic Archipelago throughflow in a multiresolution global model: Model assessment and the driving mechanism of interannual variability, J. Geophys. Res.-Oceans, 118, 4525–4541, 2013.
Wekerle, C., Wang, Q., Danilov, S., Schourup-Kristensen, V., von Appen, W.-J., and Jung, T.: Atlantic Water in the Nordic Seas: locally eddy-permitting ocean simulation in a global setup, J. Geophys. Res.-Oceans, 122, 914–940, 2017a.
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, 2017b.
Woodgate, R. A. and Aagaard, K.: Revising the Bering Strait freshwater flux into the Arctic Ocean, Geophys. Res. Lett., 32, L02602, https://doi.org/10.1029/2004GL021747, 2005.
Woodgate, R. A., Aagaard, K., Muench, R. D., Gunn, J., Björk, G., Rudels, B., Roach, A. T., and Schauer, U.: The Arctic Ocean boundary current along the Eurasian slope and the adjacent Lomonosov Ridge: Water mass properties, transports and transformations from moored instruments, Deep-Sea Res. Pt, I, 48, 1757–1792, 2001.
Yang, J., Proshutinsky, A., and Lin, X.: Dynamics of an idealized Beaufort Gyre: 1. the effect of a small beta and lack of western boundaries, J. Geophys. Res.-Oceans, 121, 1249–1261, 2016.
Zhang, J. and Steele, M.: Effect of vertical mixing on the Atlantic Water layer circulation in the Arctic Ocean, J. Geophys. Res.-Oceans, 112, C04S04, https://doi.org/10.1029/2006JC003732, 2007.
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.
For developing a system for Arctic research, we evaluate the Arctic Ocean simulated by FESOM. We...
