Articles | Volume 16, issue 13
https://doi.org/10.5194/gmd-16-3849-2023
© Author(s) 2023. 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-16-3849-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
12 Jul 2023
Model evaluation paper |
| 12 Jul 2023
| 12 Jul 2023
The mixed-layer depth in the Ocean Model Intercomparison Project (OMIP): impact of resolving mesoscale eddies
Anne Marie Treguier
CORRESPONDING AUTHOR
Laboratoire d'Océanographie Physique et Spatiale (LOPS), Univ. Brest, CNRS, IRD, Ifremer, IUEM, Brest, France
Clement de Boyer Montégut
Laboratoire d'Océanographie Physique et Spatiale (LOPS), Univ. Brest, CNRS, IRD, Ifremer, IUEM, Brest, France
Alexandra Bozec
Center for Ocean–Atmospheric Prediction Studies, Florida State University, Tallahassee, FL, USA
Eric P. Chassignet
Center for Ocean–Atmospheric Prediction Studies, Florida State University, Tallahassee, FL, USA
Baylor Fox-Kemper
Department of Earth, Environmental, and Planetary Sciences, Brown University, Providence, RI, USA
Andy McC. Hogg
Research School of Earth Sciences, Australian National University, Canberra, Australia
ARC Centre of Excellence for Climate Extremes, Australian National University, Canberra, Australia
Doroteaciro Iovino
Ocean Modeling and Data Assimilation Division, Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), Bologna, Italy
Andrew E. Kiss
Research School of Earth Sciences, Australian National University, Canberra, Australia
ARC Centre of Excellence for Climate Extremes, Australian National University, Canberra, Australia
Julien Le Sommer
CNRS, IRD, Grenoble INP, INRAE, IGE, Université Grenoble Alpes, Grenoble, France
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Pengfei Lin
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Camille Lique
Laboratoire d'Océanographie Physique et Spatiale (LOPS), Univ. Brest, CNRS, IRD, Ifremer, IUEM, Brest, France
Hailong Liu
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Guillaume Serazin
Laboratoire d'Océanographie Physique et Spatiale (LOPS), Univ. Brest, CNRS, IRD, Ifremer, IUEM, Brest, France
Dmitry Sidorenko
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
Qiang Wang
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), Bremerhaven, Germany
Xiaobio Xu
Center for Ocean–Atmospheric Prediction Studies, Florida State University, Tallahassee, FL, USA
Steve Yeager
National Center for Atmospheric Research, Boulder, CO, USA
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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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Guillaume Boutin, Einar Ólason, Pierre Rampal, Heather Regan, Camille Lique, Claude Talandier, Laurent Brodeau, and Robert Ricker
The Cryosphere, 17, 617–638, https://doi.org/10.5194/tc-17-617-2023, https://doi.org/10.5194/tc-17-617-2023, 2023
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Sea ice cover in the Arctic is full of cracks, which we call leads. We suspect that these leads play a role for atmosphere–ocean interactions in polar regions, but their importance remains challenging to estimate. We use a new ocean–sea ice model with an original way of representing sea ice dynamics to estimate their impact on winter sea ice production. This model successfully represents sea ice evolution from 2000 to 2018, and we find that about 30 % of ice production takes place in leads.
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.
Stephanie Leroux, Jean-Michel Brankart, Aurélie Albert, Laurent Brodeau, Jean-Marc Molines, Quentin Jamet, Julien Le Sommer, Thierry Penduff, and Pierre Brasseur
Ocean Sci., 18, 1619–1644, https://doi.org/10.5194/os-18-1619-2022, https://doi.org/10.5194/os-18-1619-2022, 2022
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The goal of the study is to evaluate the predictability of the ocean circulation
at a kilometric scale, in order to anticipate the requirements of the future operational forecasting systems. For that purpose, ensemble experiments have been performed with a regional model for the Western Mediterranean (at 1/60° horizontal resolution). From these ensemble experiments, we show that it is possible to compute targeted predictability scores, which depend on initial and model uncertainties.
Sergey Kravtsov, Ilijana Mastilovic, Andrew McC. Hogg, William K. Dewar, and Jeffrey R. Blundell
Geosci. Model Dev., 15, 7449–7469, https://doi.org/10.5194/gmd-15-7449-2022, https://doi.org/10.5194/gmd-15-7449-2022, 2022
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Climate is a complex system whose behavior is shaped by multitudes of processes operating on widely different spatial scales and timescales. In hierarchical modeling, one goes back and forth between highly idealized process models and state-of-the-art models coupling the entire range of climate subsystems to identify specific phenomena and understand their dynamics. The present contribution highlights an intermediate climate model focussing on midlatitude ocean–atmosphere interactions.
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.
Stephen G. Yeager, Nan Rosenbloom, Anne A. Glanville, Xian Wu, Isla Simpson, Hui Li, Maria J. Molina, Kristen Krumhardt, Samuel Mogen, Keith Lindsay, Danica Lombardozzi, Will Wieder, Who M. Kim, Jadwiga H. Richter, Matthew Long, Gokhan Danabasoglu, David Bailey, Marika Holland, Nicole Lovenduski, Warren G. Strand, and Teagan King
Geosci. Model Dev., 15, 6451–6493, https://doi.org/10.5194/gmd-15-6451-2022, https://doi.org/10.5194/gmd-15-6451-2022, 2022
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The Earth system changes over a range of time and space scales, and some of these changes are predictable in advance. Short-term weather forecasts are most familiar, but recent work has shown that it is possible to generate useful predictions several seasons or even a decade in advance. This study focuses on predictions over intermediate timescales (up to 24 months in advance) and shows that there is promising potential to forecast a variety of changes in the natural environment.
Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, https://doi.org/10.5194/gmd-15-6399-2022, 2022
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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.
Etienne Pauthenet, Loïc Bachelot, Kevin Balem, Guillaume Maze, Anne-Marie Tréguier, Fabien Roquet, Ronan Fablet, and Pierre Tandeo
Ocean Sci., 18, 1221–1244, https://doi.org/10.5194/os-18-1221-2022, https://doi.org/10.5194/os-18-1221-2022, 2022
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Temperature and salinity profiles are essential for studying the ocean’s stratification, but there are not enough of these data. Satellites are able to measure daily maps of the surface ocean. We train a machine to learn the link between the satellite data and the profiles in the Gulf Stream region. We can then use this link to predict profiles at the high resolution of the satellite maps. Our prediction is fast to compute and allows us to get profiles at any locations only from surface data.
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.
Xiaoxu Shi, Martin Werner, Carolin Krug, Chris M. Brierley, Anni Zhao, Endurance Igbinosa, Pascale Braconnot, Esther Brady, Jian Cao, Roberta D'Agostino, Johann Jungclaus, Xingxing Liu, Bette Otto-Bliesner, Dmitry Sidorenko, Robert Tomas, Evgeny M. Volodin, Hu Yang, Qiong Zhang, Weipeng Zheng, and Gerrit Lohmann
Clim. Past, 18, 1047–1070, https://doi.org/10.5194/cp-18-1047-2022, https://doi.org/10.5194/cp-18-1047-2022, 2022
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Since the orbital parameters of the past are different from today, applying the modern calendar to the past climate can lead to an artificial bias in seasonal cycles. With the use of multiple model outputs, we found that such a bias is non-ignorable and should be corrected to ensure an accurate comparison between modeled results and observational records, as well as between simulated past and modern climates, especially for the Last Interglacial.
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.
Keith B. Rodgers, Sun-Seon Lee, Nan Rosenbloom, Axel Timmermann, Gokhan Danabasoglu, Clara Deser, Jim Edwards, Ji-Eun Kim, Isla R. Simpson, Karl Stein, Malte F. Stuecker, Ryohei Yamaguchi, Tamás Bódai, Eui-Seok Chung, Lei Huang, Who M. Kim, Jean-François Lamarque, Danica L. Lombardozzi, William R. Wieder, and Stephen G. Yeager
Earth Syst. Dynam., 12, 1393–1411, https://doi.org/10.5194/esd-12-1393-2021, https://doi.org/10.5194/esd-12-1393-2021, 2021
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A large ensemble of simulations with 100 members has been conducted with the state-of-the-art CESM2 Earth system model, using historical and SSP3-7.0 forcing. Our main finding is that there are significant changes in the variance of the Earth system in response to anthropogenic forcing, with these changes spanning a broad range of variables important to impacts for human populations and ecosystems.
Vera Fofonova, Tuomas Kärnä, Knut Klingbeil, Alexey Androsov, Ivan Kuznetsov, Dmitry Sidorenko, Sergey Danilov, Hans Burchard, and Karen Helen Wiltshire
Geosci. Model Dev., 14, 6945–6975, https://doi.org/10.5194/gmd-14-6945-2021, https://doi.org/10.5194/gmd-14-6945-2021, 2021
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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.
Hakase Hayashida, Meibing Jin, Nadja S. Steiner, Neil C. Swart, Eiji Watanabe, Russell Fiedler, Andrew McC. Hogg, Andrew E. Kiss, Richard J. Matear, and Peter G. Strutton
Geosci. Model Dev., 14, 6847–6861, https://doi.org/10.5194/gmd-14-6847-2021, https://doi.org/10.5194/gmd-14-6847-2021, 2021
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Ice algae are tiny plants like phytoplankton but they grow within sea ice. In polar regions, both phytoplankton and ice algae are the foundation of marine ecosystems and play an important role in taking up carbon dioxide in the atmosphere. However, state-of-the-art climate models typically do not include ice algae, and therefore their role in the climate system remains unclear. This project aims to address this knowledge gap by coordinating a set of experiments using sea-ice–ocean models.
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.
Amy Solomon, Céline Heuzé, Benjamin Rabe, Sheldon Bacon, Laurent Bertino, Patrick Heimbach, Jun Inoue, Doroteaciro Iovino, Ruth Mottram, Xiangdong Zhang, Yevgeny Aksenov, Ronan McAdam, An Nguyen, Roshin P. Raj, and Han Tang
Ocean Sci., 17, 1081–1102, https://doi.org/10.5194/os-17-1081-2021, https://doi.org/10.5194/os-17-1081-2021, 2021
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Freshwater in the Arctic Ocean plays a critical role in the global climate system by impacting ocean circulations, stratification, mixing, and emergent regimes. In this review paper we assess how Arctic Ocean freshwater changed in the 2010s relative to the 2000s. Estimates from observations and reanalyses show a qualitative stabilization in the 2010s due to a compensation between a freshening of the Beaufort Gyre and a reduction in freshwater in the Amerasian and Eurasian basins.
Pengfei Wang, Jinrong Jiang, Pengfei Lin, Mengrong Ding, Junlin Wei, Feng Zhang, Lian Zhao, Yiwen Li, Zipeng Yu, Weipeng Zheng, Yongqiang Yu, Xuebin Chi, and Hailong Liu
Geosci. Model Dev., 14, 2781–2799, https://doi.org/10.5194/gmd-14-2781-2021, https://doi.org/10.5194/gmd-14-2781-2021, 2021
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Global ocean general circulation models are a fundamental tool for oceanography research, ocean forecast, and climate change research. The increasing resolution will greatly improve simulations of the models, but it also demands much more computing resources. In this study, we have ported an ocean general circulation model to a heterogeneous computing system and have developed a 3–5 km model version. A 14-year integration has been conducted and the preliminary results have been evaluated.
Pablo Ortega, Jon I. Robson, Matthew Menary, Rowan T. Sutton, Adam Blaker, Agathe Germe, Jöel J.-M. Hirschi, Bablu Sinha, Leon Hermanson, and Stephen Yeager
Earth Syst. Dynam., 12, 419–438, https://doi.org/10.5194/esd-12-419-2021, https://doi.org/10.5194/esd-12-419-2021, 2021
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Deep Labrador Sea densities are receiving increasing attention because of their link to many of the processes that govern decadal climate oscillations in the North Atlantic and their potential use as a precursor of those changes. This article explores those links and how they are represented in global climate models, documenting the main differences across models. Models are finally compared with observational products to identify the ones that reproduce the links more realistically.
Giulia Bonino, Elisa Lovecchio, Nicolas Gruber, Matthias Münnich, Simona Masina, and Doroteaciro Iovino
Biogeosciences, 18, 2429–2448, https://doi.org/10.5194/bg-18-2429-2021, https://doi.org/10.5194/bg-18-2429-2021, 2021
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Seasonal variations of processes such as upwelling and biological production that happen along the northwestern African coast can modulate the temporal variability of the biological activity of the adjacent open North Atlantic hundreds of kilometers away from the coast thanks to the lateral transport of coastal organic carbon. This happens with a temporal delay, which is smaller than a season up to roughly 500 km from the coast due to the intense transport by small-scale filaments.
Sophie Cravatte, Guillaume Serazin, Thierry Penduff, and Christophe Menkes
Ocean Sci., 17, 487–507, https://doi.org/10.5194/os-17-487-2021, https://doi.org/10.5194/os-17-487-2021, 2021
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The various currents in the southwestern Pacific Ocean contribute to the redistribution of waters from the subtropical gyre equatorward and poleward. The drivers of their interannual variability are not completely understood but are usually thought to be related to well-known climate modes of variability. Here, we suggest that oceanic chaotic variability alone, which is by definition unpredictable, explains the majority of this interannual variability south of 20° S.
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.
Guillaume Boutin, Timothy Williams, Pierre Rampal, Einar Olason, and Camille Lique
The Cryosphere, 15, 431–457, https://doi.org/10.5194/tc-15-431-2021, https://doi.org/10.5194/tc-15-431-2021, 2021
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In this study, we investigate the interactions of surface ocean waves with sea ice. We focus on the evolution of sea ice after it has been fragmented by the waves. Fragmented sea ice is expected to experience less resistance to deformation. We reproduce this evolution using a new coupling framework between a wave model and the recently developed sea ice model neXtSIM. We find that waves can significantly increase the mobility of compact sea ice over wide areas in the wake of storm events.
Cameron M. O'Neill, Andrew McC. Hogg, Michael J. Ellwood, Bradley N. Opdyke, and Stephen M. Eggins
Clim. Past, 17, 171–201, https://doi.org/10.5194/cp-17-171-2021, https://doi.org/10.5194/cp-17-171-2021, 2021
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We undertake a model–data study of the last glacial–interglacial cycle of atmospheric CO2, spanning 0–130 ka. We apply a carbon cycle box model, constrained with glacial–interglacial observations, and solve for optimal model parameter values against atmospheric and ocean proxy data. The results indicate that the last glacial drawdown in atmospheric CO2 was delivered mainly by slowing ocean circulation, lower sea surface temperatures and also increased Southern Ocean biological productivity.
Clément Bricaud, Julien Le Sommer, Gurvan Madec, Christophe Calone, Julie Deshayes, Christian Ethe, Jérôme Chanut, and Marina Levy
Geosci. Model Dev., 13, 5465–5483, https://doi.org/10.5194/gmd-13-5465-2020, https://doi.org/10.5194/gmd-13-5465-2020, 2020
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In order to reduce the cost of ocean biogeochemical models, a multi-grid approach where ocean dynamics and tracer transport are computed with different spatial resolution has been developed in the NEMO v3.6 OGCM. Different experiments confirm that the spatial resolution of hydrodynamical fields can be coarsened without significantly affecting the resolved passive tracer fields. This approach leads to a factor of 7 reduction of the overhead associated with running a full biogeochemical model.
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.
Shaoqing Zhang, Haohuan Fu, Lixin Wu, Yuxuan Li, Hong Wang, Yunhui Zeng, Xiaohui Duan, Wubing Wan, Li Wang, Yuan Zhuang, Hongsong Meng, Kai Xu, Ping Xu, Lin Gan, Zhao Liu, Sihai Wu, Yuhu Chen, Haining Yu, Shupeng Shi, Lanning Wang, Shiming Xu, Wei Xue, Weiguo Liu, Qiang Guo, Jie Zhang, Guanghui Zhu, Yang Tu, Jim Edwards, Allison Baker, Jianlin Yong, Man Yuan, Yangyang Yu, Qiuying Zhang, Zedong Liu, Mingkui Li, Dongning Jia, Guangwen Yang, Zhiqiang Wei, Jingshan Pan, Ping Chang, Gokhan Danabasoglu, Stephen Yeager, Nan Rosenbloom, and Ying Guo
Geosci. Model Dev., 13, 4809–4829, https://doi.org/10.5194/gmd-13-4809-2020, https://doi.org/10.5194/gmd-13-4809-2020, 2020
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Science advancement and societal needs require Earth system modelling with higher resolutions that demand tremendous computing power. We successfully scale the 10 km ocean and 25 km atmosphere high-resolution Earth system model to a new leading-edge heterogeneous supercomputer using state-of-the-art optimizing methods, promising the solution of high spatial resolution and time-varying frequency. Corresponding technical breakthroughs are of significance in modelling and HPC design communities.
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.
Pedro Colombo, Bernard Barnier, Thierry Penduff, Jérôme Chanut, Julie Deshayes, Jean-Marc Molines, Julien Le Sommer, Polina Verezemskaya, Sergey Gulev, and Anne-Marie Treguier
Geosci. Model Dev., 13, 3347–3371, https://doi.org/10.5194/gmd-13-3347-2020, https://doi.org/10.5194/gmd-13-3347-2020, 2020
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In the ocean circulation model NEMO, the representation of the overflow of dense Arctic waters through the Denmark Strait is investigated. In this
z-coordinate context, sensitivity tests show that the mixing parameterizations preferably act along the model grid slope. Thus, the representation of the overflow is more sensitive to resolution than to parameterization and is best when the numerical grid matches the local topographic slope.
Guillaume Sérazin, Frédéric Marin, Lionel Gourdeau, Sophie Cravatte, Rosemary Morrow, and Mei-Ling Dabat
Ocean Sci., 16, 907–925, https://doi.org/10.5194/os-16-907-2020, https://doi.org/10.5194/os-16-907-2020, 2020
Hailun He, Yuan Wang, Xiqiu Han, Yanzhou Wei, Pengfei Lin, Zhongyan Qiu, and Yejian Wang
Ocean Sci., 16, 895–906, https://doi.org/10.5194/os-16-895-2020, https://doi.org/10.5194/os-16-895-2020, 2020
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Ocean profiling observation in the Indian Ocean is not sufficient. We conducted a hydrographic survey on the Carlsberg Ridge, which is a mid-ocean ridge in the northwest Indian Ocean, to obtain snapshots of sectional temperature, salinity, and density fields by combining the ARGO data. The results show mesoscale eddies located along the specific ridge and the existence of a west-propagating planetary wave. The results provide references in the regional ocean circulation.
Dmitry Sidorenko, Sergey Danilov, Nikolay Koldunov, Patrick Scholz, and Qiang Wang
Geosci. Model Dev., 13, 3337–3345, https://doi.org/10.5194/gmd-13-3337-2020, https://doi.org/10.5194/gmd-13-3337-2020, 2020
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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.
Yurui Zhang, Thierry Huck, Camille Lique, Yannick Donnadieu, Jean-Baptiste Ladant, Marina Rabineau, and Daniel Aslanian
Clim. Past, 16, 1263–1283, https://doi.org/10.5194/cp-16-1263-2020, https://doi.org/10.5194/cp-16-1263-2020, 2020
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The early Eocene (~ 55 Ma) was an extreme warm period accompanied by a high atmospheric CO2 level. We explore the relationships between ocean dynamics and this warm climate with the aid of the IPSL climate model. Our results show that the Eocene was characterized by a strong overturning circulation associated with deepwater formation in the Southern Ocean, which is analogous to the present-day North Atlantic. Consequently, poleward ocean heat transport was strongly enhanced.
Taylor A. Shropshire, Steven L. Morey, Eric P. Chassignet, Alexandra Bozec, Victoria J. Coles, Michael R. Landry, Rasmus Swalethorp, Glenn Zapfe, and Michael R. Stukel
Biogeosciences, 17, 3385–3407, https://doi.org/10.5194/bg-17-3385-2020, https://doi.org/10.5194/bg-17-3385-2020, 2020
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Zooplankton are the smallest animals in the ocean and important food for fish. Despite their importance, zooplankton have been relatively undersampled. To better understand the zooplankton community in the Gulf of Mexico (GoM), we developed a model to simulate their dynamics. We found that heterotrophic protists are important for supporting mesozooplankton, which are the primary prey of larval fish. The model developed in this study has the potential to improve fisheries management in the GoM.
Torben Koenigk, Ramon Fuentes-Franco, Virna Meccia, Oliver Gutjahr, Laura C. Jackson, Adrian L. New, Pablo Ortega, Christopher Roberts, Malcolm Roberts, Thomas Arsouze, Doroteaciro Iovino, Marie-Pierre Moine, and Dmitry V. Sein
Ocean Sci. Discuss., https://doi.org/10.5194/os-2020-41, https://doi.org/10.5194/os-2020-41, 2020
Revised manuscript not accepted
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The mixing of water masses into the deep ocean in the North Atlantic is important for the entire global ocean circulation. We use seven global climate models to investigate the effect of increasing the model resolution on this deep ocean mixing. The main result is that increased model resolution leads to a deeper mixing of water masses in the Labrador Sea but has less effect in the Greenland Sea. However, most of the models overestimate the deep ocean mixing compared to observations.
Mathieu Le Corre, Jonathan Gula, and Anne-Marie Tréguier
Ocean Sci., 16, 451–468, https://doi.org/10.5194/os-16-451-2020, https://doi.org/10.5194/os-16-451-2020, 2020
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The ocean circulation is crucial for the climate, and the North Atlantic subpolar gyre is a key component of the meridional heat transport. In this study we use a high-resolution simulation with bottom-following coordinates to investigate the gyre dynamics. We show that nonlinear processes, underestimated in most climate models, control the circulation in the gyre interior. This result contrasts with the classical theory putting forward wind effects on the large-scale circulation.
Valentin Resseguier, Wei Pan, and Baylor Fox-Kemper
Nonlin. Processes Geophys., 27, 209–234, https://doi.org/10.5194/npg-27-209-2020, https://doi.org/10.5194/npg-27-209-2020, 2020
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Geophysical flows span a broader range of temporal and spatial scales than can be resolved numerically. One way to alleviate the ensuing numerical errors is to combine simulations with measurements, taking account of the accuracies of these two sources of information. Here we quantify the distribution of numerical simulation errors without relying on high-resolution numerical simulations. Specifically, small-scale random vortices are added to simulations while conserving energy or circulation.
Guillaume Boutin, Camille Lique, Fabrice Ardhuin, Clément Rousset, Claude Talandier, Mickael Accensi, and Fanny Girard-Ardhuin
The Cryosphere, 14, 709–735, https://doi.org/10.5194/tc-14-709-2020, https://doi.org/10.5194/tc-14-709-2020, 2020
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We investigate the interactions of surface ocean waves with sea ice taking place at the interface between the compact sea ice cover and the open ocean. We use a newly developed coupling framework between a wave and an ocean–sea ice numerical model. Our results show how the push on sea ice exerted by waves changes the amount and the location of sea ice melting, with a strong impact on the ocean surface properties close to the ice edge.
Andrew E. Kiss, Andrew McC. Hogg, Nicholas Hannah, Fabio Boeira Dias, Gary B. Brassington, Matthew A. Chamberlain, Christopher Chapman, Peter Dobrohotoff, Catia M. Domingues, Earl R. Duran, Matthew H. England, Russell Fiedler, Stephen M. Griffies, Aidan Heerdegen, Petra Heil, Ryan M. Holmes, Andreas Klocker, Simon J. Marsland, Adele K. Morrison, James Munroe, Maxim Nikurashin, Peter R. Oke, Gabriela S. Pilo, Océane Richet, Abhishek Savita, Paul Spence, Kial D. Stewart, Marshall L. Ward, Fanghua Wu, and Xihan Zhang
Geosci. Model Dev., 13, 401–442, https://doi.org/10.5194/gmd-13-401-2020, https://doi.org/10.5194/gmd-13-401-2020, 2020
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We describe new computer model configurations which simulate the global ocean and sea ice at three resolutions. The coarsest resolution is suitable for multi-century climate projection experiments, whereas the finest resolution is designed for more detailed studies over time spans of decades. The paper provides technical details of the model configurations and an assessment of their performance relative to observations.
Anson Cheung, Baylor Fox-Kemper, and Timothy Herbert
Clim. Past, 15, 1985–1998, https://doi.org/10.5194/cp-15-1985-2019, https://doi.org/10.5194/cp-15-1985-2019, 2019
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We test two assumptions that are often made in paleoclimate studies by using observations and ask whether temperature and productivity proxy records in the Southern California Current can be used to reconstruct Ekman upwelling. By examining the covariation between alongshore wind stress, temperature, and productivity, we found that the dominant covarying pattern does not reflect Ekman upwelling. Other upwelling patterns found are timescale dependent. Multiple proxies can improve reconstruction.
Patrick Scholz, Dmitry Sidorenko, Ozgur Gurses, Sergey Danilov, Nikolay Koldunov, Qiang Wang, Dmitry Sein, Margarita Smolentseva, Natalja Rakowsky, and Thomas Jung
Geosci. Model Dev., 12, 4875–4899, https://doi.org/10.5194/gmd-12-4875-2019, https://doi.org/10.5194/gmd-12-4875-2019, 2019
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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.
Christopher Horvat, Lettie A. Roach, Rachel Tilling, Cecilia M. Bitz, Baylor Fox-Kemper, Colin Guider, Kaitlin Hill, Andy Ridout, and Andrew Shepherd
The Cryosphere, 13, 2869–2885, https://doi.org/10.5194/tc-13-2869-2019, https://doi.org/10.5194/tc-13-2869-2019, 2019
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Changes in the floe size distribution (FSD) are important for sea ice evolution but to date largely unobserved and unknown. Climate models, forecast centres, ship captains, and logistic specialists cannot currently obtain statistical information about sea ice floe size on demand. We develop a new method to observe the FSD at global scales and high temporal and spatial resolution. With refinement, this method can provide crucial information for polar ship routing and real-time forecasting.
Nikolay V. Koldunov, Vadym Aizinger, Natalja Rakowsky, Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, and Thomas Jung
Geosci. Model Dev., 12, 3991–4012, https://doi.org/10.5194/gmd-12-3991-2019, https://doi.org/10.5194/gmd-12-3991-2019, 2019
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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.
Cameron M. O'Neill, Andrew McC. Hogg, Michael J. Ellwood, Stephen M. Eggins, and Bradley N. Opdyke
Geosci. Model Dev., 12, 1541–1572, https://doi.org/10.5194/gmd-12-1541-2019, https://doi.org/10.5194/gmd-12-1541-2019, 2019
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The [simple carbon project] model v1.0 (SCP-M) was constructed for simulations of the paleo and modern carbon cycle. In this paper we show its application to the carbon cycle transition from the Last Glacial Maximum to the Holocene period. Our model–data experiment uses SCP-M's fast run time to cover a large range of possible inputs. The results highlight the role of varying the strength of ocean circulation to account for large fluctuations in atmospheric CO2 across the two periods.
Nicole S. Lovenduski, Stephen G. Yeager, Keith Lindsay, and Matthew C. Long
Earth Syst. Dynam., 10, 45–57, https://doi.org/10.5194/esd-10-45-2019, https://doi.org/10.5194/esd-10-45-2019, 2019
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This paper shows that the absorption of carbon dioxide by the ocean is predictable several years in advance. This is important because fossil-fuel-derived carbon dioxide is largely responsible for anthropogenic global warming and because carbon dioxide emission management and global carbon cycle budgeting exercises can benefit from foreknowledge of ocean carbon absorption. The promising results from this new forecast system justify the need for additional oceanic observations.
Robert Ricker, Fanny Girard-Ardhuin, Thomas Krumpen, and Camille Lique
The Cryosphere, 12, 3017–3032, https://doi.org/10.5194/tc-12-3017-2018, https://doi.org/10.5194/tc-12-3017-2018, 2018
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We present ice volume flux estimates through the Fram Strait using CryoSat-2 ice thickness data. This study presents a detailed analysis of temporal and spatial variability of ice volume export through the Fram Strait and shows the impact of ice volume export on Arctic ice mass balance.
Qiang Wang, Claudia Wekerle, Sergey Danilov, Xuezhu Wang, and Thomas Jung
Geosci. Model Dev., 11, 1229–1255, https://doi.org/10.5194/gmd-11-1229-2018, https://doi.org/10.5194/gmd-11-1229-2018, 2018
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For developing a system for Arctic research, we evaluate the Arctic Ocean simulated by FESOM. We use two global meshes differing in the horizontal resolution only in the Arctic Ocean (24 vs. 4.5 km). The high resolution significantly improves the model's representation of the Arctic Ocean. The most pronounced improvement is in the Arctic intermediate layer. The high resolution also improves the ocean surface circulation, mainly through a better representation of the Canadian Arctic Archipelago.
Seonmin Ahn, Baylor Fox-Kemper, Timothy Herbert, and Charles Lawrence
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-1, https://doi.org/10.5194/cp-2018-1, 2018
Revised manuscript not accepted
Verena Haid, Doroteaciro Iovino, and Simona Masina
The Cryosphere, 11, 1387–1402, https://doi.org/10.5194/tc-11-1387-2017, https://doi.org/10.5194/tc-11-1387-2017, 2017
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Since the Antarctic sea ice extent shows a recent increase, we investigate the sea ice response to changed amount and distribution of surface freshwater addition in the Southern Ocean with the ocean–sea ice model NEMO/LIM2. We find that freshwater addition within the range of current estimates increases the ice extent, but higher amounts could have an opposing effect. The freshwater distribution is of great influence on the ice dynamics and the ice thickness is strongly influenced by it.
Laurent Bessières, Stéphanie Leroux, Jean-Michel Brankart, Jean-Marc Molines, Marie-Pierre Moine, Pierre-Antoine Bouttier, Thierry Penduff, Laurent Terray, Bernard Barnier, and Guillaume Sérazin
Geosci. Model Dev., 10, 1091–1106, https://doi.org/10.5194/gmd-10-1091-2017, https://doi.org/10.5194/gmd-10-1091-2017, 2017
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A new, probabilistic version of an ocean modelling system has been implemented in order to simulate the chaotic and the atmospherically forced contributions to the ocean variability. For that purpose, a large ensemble of global hindcasts has been performed. Results illustrate the importance of the oceanic chaos on climate-related oceanic indices, and the relevance of such probabilistic ocean modelling approaches to anticipating the behaviour of the next generation of coupled climate models.
Petteri Uotila, Doroteaciro Iovino, Martin Vancoppenolle, Mikko Lensu, and Clement Rousset
Geosci. Model Dev., 10, 1009–1031, https://doi.org/10.5194/gmd-10-1009-2017, https://doi.org/10.5194/gmd-10-1009-2017, 2017
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We performed ocean model simulations with new and old sea-ice components. Sea ice improved in the new model compared to the earlier one due to better model physics. In the ocean, the largest differences are confined close to the surface within and near the sea-ice zone. The global ocean circulation slowly deviates between the simulations due to dissimilar sea ice in the deep water formation regions, such as the North Atlantic and Antarctic.
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.
Arin D. Nelson, Jeffrey B. Weiss, Baylor Fox-Kemper, Royce K. P. Zia, and Fabienne Gaillard
Ocean Sci. Discuss., https://doi.org/10.5194/os-2016-105, https://doi.org/10.5194/os-2016-105, 2017
Revised manuscript has not been submitted
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We quantify the skill in observing the variability of global upper ocean heat content (OHC) by applying the ISAS13 observing strategy to a CCSM simulation. We find that variability is unreliably observed before 2005, while observed annual running means for 2005–2013 correlate well with model "truth" to a median of 95 %. When scaled to the real ocean, we find signal-to-noise ratios of 1.9 for pre-Argo times (1990–2005) and 14.7 after Argo is introduced (2005–2013). The global warming is robust.
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.
Doroteaciro Iovino, Simona Masina, Andrea Storto, Andrea Cipollone, and Vladimir N. Stepanov
Geosci. Model Dev., 9, 2665–2684, https://doi.org/10.5194/gmd-9-2665-2016, https://doi.org/10.5194/gmd-9-2665-2016, 2016
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An 11-year simulation of a global eddying ocean (1/16) configuration is presented. Model performance is evaluated against observations and a twin 1/4 configuration. The model realistically represents the variability at upper and intermediate depths, the position and strength of the surface circulation, and exchanges of mass through key passages. Sea ice properties are close to satellite observations. This simulation constitutes the groundwork for future applications to short range ocean forecasting.
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.
V. Schourup-Kristensen, D. Sidorenko, D. A. Wolf-Gladrow, and C. Völker
Geosci. Model Dev., 7, 2769–2802, https://doi.org/10.5194/gmd-7-2769-2014, https://doi.org/10.5194/gmd-7-2769-2014, 2014
P. Lin, Y. Song, Y. Yu, and H. Liu
Clim. Past Discuss., https://doi.org/10.5194/cpd-10-2519-2014, https://doi.org/10.5194/cpd-10-2519-2014, 2014
Revised manuscript not accepted
Q. Wang, S. Danilov, D. Sidorenko, R. Timmermann, C. Wekerle, X. Wang, T. Jung, and J. Schröter
Geosci. Model Dev., 7, 663–693, https://doi.org/10.5194/gmd-7-663-2014, https://doi.org/10.5194/gmd-7-663-2014, 2014
A. M. Treguier, J. Deshayes, J. Le Sommer, C. Lique, G. Madec, T. Penduff, J.-M. Molines, B. Barnier, R. Bourdalle-Badie, and C. Talandier
Ocean Sci., 10, 243–255, https://doi.org/10.5194/os-10-243-2014, https://doi.org/10.5194/os-10-243-2014, 2014
Related subject area
Climate and Earth system modeling
CARIB12: a regional Community Earth System Model/Modular Ocean Model 6 configuration of the Caribbean Sea
Architectural insights into and training methodology optimization of Pangu-Weather
Evaluation of global fire simulations in CMIP6 Earth system models
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections
ISOM 1.0: a fully mesoscale-resolving idealized Southern Ocean model and the diversity of multiscale eddy interactions
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature
The need for carbon-emissions-driven climate projections in CMIP7
Robust handling of extremes in quantile mapping – “Murder your darlings”
A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates
Methane dynamics in the Baltic Sea: investigating concentration, flux, and isotopic composition patterns using the coupled physical–biogeochemical model BALTSEM-CH4 v1.0
CropSuite – A comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – The ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Split-explicit external mode solver in the finite volume sea ice–ocean model FESOM2
Applying double cropping and interactive irrigation in the North China Plain using WRF4.5
The sea ice component of GC5: coupling SI3 to HadGEM3 using conductive fluxes
CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5
HyPhAICC v1.0: a hybrid physics–AI approach for probability fields advection shown through an application to cloud cover nowcasting
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
A non-intrusive, multi-scale, and flexible coupling interface in WRF
Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)
Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model
Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic
HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
A 3D-Var assimilation scheme for vertical velocity with CMA-MESO v5.0
Updating the radiation infrastructure in MESSy (based on MESSy version 2.55)
An urban module coupled with the Variable Infiltration Capacity model to improve hydrothermal simulations in urban systems
Bayesian hierarchical model for bias-correcting climate models
Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4
Reduced floating-point precision in regional climate simulations: an ensemble-based statistical verification
TorchClim v1.0: a deep-learning plugin for climate model physics
The very-high resolution configuration of the EC-Earth global model for HighResMIP
ZEMBA v1.0: An energy and moisture balance climate model to investigate Quaternary climate
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
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Hector V3.2.0: functionality and performance of a reduced-complexity climate model
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Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
EGUsphere, https://doi.org/10.5194/egusphere-2024-2526, https://doi.org/10.5194/egusphere-2024-2526, 2024
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CropSuite is a fuzzy-logic based high resolution open-source crop suitability model considering the impact of climate variability. We apply CropSuite for 48 important staple and cash crops at 1 km spatial resolution for Africa. We find that climate variability significantly impacts on suitable areas, but also affects optimal sowing dates, and multiple cropping potentials. The results provide information that can be used for climate impact assessments, adaptation and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-135, https://doi.org/10.5194/gmd-2024-135, 2024
Revised manuscript accepted for GMD
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The Icosahedral Nonhydrostatic (ICON) Model Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++ and Python) and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-140, https://doi.org/10.5194/gmd-2024-140, 2024
Revised manuscript accepted for GMD
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This article details a new feature we implemented in the most popular regional atmospheric model (WRF). This feature allows data to be exchanged between WRF and any other model (e.g. an ocean model) using the coupling library Ocean-Atmosphere-Sea-Ice-Soil – Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
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We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-119, https://doi.org/10.5194/gmd-2024-119, 2024
Revised manuscript accepted for GMD
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10-15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100-km and a 25-km grid. The three models are compared with observations to study the improvements thanks to the increased in the resolution.
Daniel Francis James Gunning, Kerim Hestnes Nisancioglu, Emilie Capron, and Roderik van de Wal
EGUsphere, https://doi.org/10.5194/egusphere-2024-1384, https://doi.org/10.5194/egusphere-2024-1384, 2024
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This work documents the first results from ZEMBA: an energy balance model of the climate system. The model is a computationally efficient tool designed to study the response of climate to changes in the Earth’s orbit. We demonstrate ZEMBA reproduces many features of the Earth’s climate for both the pre-industrial period and the Earth’s most recent cold extreme- the Last Glacial Maximum. We intend to develop ZEMBA further and investigate the glacial cycles of the last 2.5 million years.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
K. Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
EGUsphere, https://doi.org/10.5194/egusphere-2024-1431, https://doi.org/10.5194/egusphere-2024-1431, 2024
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The study aimed to improve the representation of spring wheat and rice in the CLM5. The modified CLM5 model performed significantly better than the default model in simulating crop phenology, yield, carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific parameters for accurately simulating vegetation processes and land surface processes.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Cited articles
Alexander, M. A., Scott, J. D., Friedland, K. D., Mills, K. E., Nye, J. A., Pershing, A. J., and Thomas, A. C.:
Projected sea surface temperatures over the 21st century: Changes in the mean, variability and extremes for large marine ecosystem regions of Northern Oceans, Elem. Sci. Anthr., 6, 9, https://doi.org/10.1525/elementa.191, 2018.
Beckmann, A. and Döscher, R.:
A Method for Improved Representation of Dense Water Spreading over Topography in Geopotential-Coordinate Models, J. Phys. Oceanogr., 27, 581–591, https://doi.org/10.1175/1520-0485(1997)027<0581:AMFIRO>2.0.CO;2, 1997.
Beech, N., Rackow, T., Semmler, T., Danilov, S., Wang, Q., and Jung, T.:
Long-term evolution of ocean eddy activity in a warming world, Nat. Clim. Change, 12, 910–917, https://doi.org/10.1038/s41558-022-01478-3, 2022.
Belcher, S. E., Grant, A. L. M., Hanley, K. E., Fox-Kemper, B., Van Roekel, L., Sullivan, P. P., Large, W. G., Brown, A., Hines, A., Calvert, D., Rutgersson, A., Pettersson, H., Bidlot, J.-R., Janssen, P. A. E. M., and Polton, J. A.:
A global perspective on Langmuir turbulence in the ocean surface boundary layer, Geophys. Res. Lett., 39, L18605, https://doi.org/10.1029/2012GL052932, 2012.
Bi, D., Dix, M., Marsland, S., O'Farrell, S., Sullivan, A., Bodman, R., Law, R., Harman, I., Srbinovsky, J., Rashid, H. A., Dobrohotoff, P., Mackallah, C., Yan, H., Hirst, A., Savita, A., Dias, F. B., Woodhouse, M., Fiedler, R., and Heerdegen, A.:
Configuration and spin-up of ACCESS-CM2, the new generation Australian Community Climate and Earth System Simulator Coupled Model, J. South. Hemisphere Earth Syst. Sci., 70, 225–251, https://doi.org/10.1071/es19040, 2020.
Blanke, B. and Delecluse, P.:
Variability of the Tropical Atlantic Ocean Simulated by a General Circulation Model with Two Different Mixed-Layer Physics, J. Phys. Oceanogr., 23, 1363–1388, https://doi.org/10.1175/1520-0485(1993)023<1363:VOTTAO>2.0.CO;2, 1993.
Bouillon, S., Morales Maqueda, M. Á., Legat, V., and Fichefet, T.:
An elastic–viscous–plastic sea ice model formulated on Arakawa B and C grids, Ocean Model., 27, 174–184, https://doi.org/10.1016/j.ocemod.2009.01.004, 2009.
Brainerd, K. E. and Gregg, M. C.:
Surface mixed and mixing layer depths, Deep-Sea Res. Pt. I, 42, 1521–1543, https://doi.org/10.1016/0967-0637(95)00068-H, 1995.
Campin, J.-M. and Goosse, H.:
Parameterization of density-driven downsloping flow for a coarse-resolution ocean model in z-coordinate, Tellus A, 51, 412–430, https://doi.org/10.1034/j.1600-0870.1999.t01-3-00006.x, 1999.
Canuto, V. M., Howard, A., Cheng, Y., and Dubovikov, M. S.:
Ocean Turbulence. Part I: One-Point Closure Model—Momentum and Heat Vertical Diffusivities, J. Phys. Oceanogr., 31, 1413–1426, https://doi.org/10.1175/1520-0485(2001)031<1413:OTPIOP>2.0.CO;2, 2001.
Canuto, V. M., Howard, A., Cheng, Y., and Dubovikov, M. S.:
Ocean Turbulence. Part II: Vertical Diffusivities of Momentum, Heat, Salt, Mass, and Passive Scalars, J. Phys. Oceanogr., 32, 240–264, https://doi.org/10.1175/1520-0485(2002)032<0240:OTPIVD>2.0.CO;2, 2002.
Chang, P., Zhang, S., Danabasoglu, G., Yeager, S. G., Fu, H., Wang, H., Castruccio, F. S., Chen, Y., Edwards, J., Fu, D., Jia, Y., Laurindo, L. C., Liu, X., Rosenbloom, N., Small, R. J., Xu, G., Zeng, Y., Zhang, Q., Bacmeister, J., Bailey, D. A., Duan, X., DuVivier, A. K., Li, D., Li, Y., Neale, R., Stössel, A., Wang, L., Zhuang, Y., Baker, A., Bates, S., Dennis, J., Diao, X., Gan, B., Gopal, A., Jia, D., Jing, Z., Ma, X., Saravanan, R., Strand, W. G., Tao, J., Yang, H., Wang, X., Wei, Z., and Wu, L.:
An Unprecedented Set of High-Resolution Earth System Simulations for Understanding Multiscale Interactions in Climate Variability and Change, J. Adv. Model. Earth Sy., 12, e2020MS002298, https://doi.org/10.1029/2020MS002298, 2020.
Chassignet, E. P., Smith, L. T., Halliwell, G. R., and Bleck, R.:
North Atlantic Simulations with the Hybrid Coordinate Ocean Model (HYCOM): Impact of the Vertical Coordinate Choice, Reference Pressure, and Thermobaricity, J. Phys. Oceanogr., 33, 2504–2526, https://doi.org/10.1175/1520-0485(2003)033<2504:NASWTH>2.0.CO;2, 2003.
Chassignet, E. P., Yeager, S. G., Fox-Kemper, B., Bozec, A., Castruccio, F., Danabasoglu, G., Horvat, C., Kim, W. M., Koldunov, N., Li, Y., Lin, P., Liu, H., Sein, D. V., Sidorenko, D., Wang, Q., and Xu, X.:
Impact of horizontal resolution on global ocean–sea ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2), Geosci. Model Dev., 13, 4595–4637, https://doi.org/10.5194/gmd-13-4595-2020, 2020.
Cherchi, A., Fogli, P. G., Lovato, T., Peano, D., Iovino, D., Gualdi, S., Masina, S., Scoccimarro, E., Materia, S., Bellucci, A., and Navarra, A.:
Global Mean Climate and Main Patterns of Variability in the CMCC-CM2 Coupled Model, J. Adv. Model. Earth Sy., 11, 185–209, https://doi.org/10.1029/2018MS001369, 2019.
Courtois, P., Hu, X., Pennelly, C., Spence, P., and Myers, P. G.:
Mixed layer depth calculation in deep convection regions in ocean numerical models, Ocean Model., 120, 60–78, https://doi.org/10.1016/j.ocemod.2017.10.007, 2017.
Danabasoglu, G.:
NCAR CESM2 model output prepared for CMIP6 OMIP omip1, WCRP [data set], https://doi.org/10.22033/ESGF/CMIP6.7678, 2019.
Danabasoglu, G., Ferrari, R., and McWilliams, J. C.:
Sensitivity of an Ocean General Circulation Model to a Parameterization of Near-Surface Eddy Fluxes, J. Climate, 21, 1192–1208, https://doi.org/10.1175/2007JCLI1508.1, 2008.
Danabasoglu, G., Yeager, S. G., Bailey, D., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Canuto, V. M., Cassou, C., Chassignet, E., Coward, A. C., Danilov, S., Diansky, N., Drange, H., Farneti, R., Fernandez, E., Fogli, P. G., Forget, G., Fujii, Y., Griffies, S. M., Gusev, A., Heimbach, P., Howard, A., Jung, T., Kelley, M., Large, W. G., Leboissetier, A., Lu, J., Madec, G., Marsland, S. J., Masina, S., Navarra, A., Nurser, A. J. G., Pirani, A., Mélia, D. S. Y., Samuels, B. L., Scheinert, M., Sidorenko, D., Treguier, A.-M., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., and Wang, Q.:
North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part I: Mean states, Ocean Model., 73, 76–107, https://doi.org/10.1016/j.ocemod.2013.10.005, 2014.
Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D. A., DuVivier, A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A., Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M., Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R., Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S., van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C., Fischer, C., Fox-Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J., Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L., Rasch, P. J., and Strand, W. G.:
The Community Earth System Model Version 2 (CESM2), J. Adv. Model. Earth Sy., 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020.
D'Asaro, E. A.:
Turbulence in the Upper-Ocean Mixed Layer, Annu. Rev. Mar. Sci., 6, 101–115, https://doi.org/10.1146/annurev-marine-010213-135138, 2014.
de Boyer Montégut, C.:
Mixed layer depth climatology computed with a density threshold criterion of 0.03 kg/m3 from 10 m depth value, SEANOE [data set], https://doi.org/10.17882/91774, 2022.
de Boyer Montégut, C., Madec, G., Fisher, A. S., Lazar, A., and Iudicone, D.:
Mixed layer depth over the global ocean: An examination of profile data and a profile-based climatology, J. Geophys. Res., 109, C12003, https://doi.org/10.1029/2004JC002378, 2004.
de Boyer Montégut, C., Vialard, J., Shenoi, S. S. C., Shankar, D., Durand, F., Ethé, C., and Madec, G.:
Simulated Seasonal and Interannual Variability of the Mixed Layer Heat Budget in the Northern Indian Ocean, J. Climate, 20, 3249–3268, https://doi.org/10.1175/JCLI4148.1, 2007.
Dong, S., Sprintall, J., Gille, S. T., and Talley, L.:
Southern Ocean mixed-layer depth from Argo float profiles, J. Geophys. Res.-Oceans, 113, C06013, https://doi.org/10.1029/2006JC004051, 2008.
Döscher, R. and Beckmann, A.:
Effects of a Bottom Boundary Layer Parameterization in a Coarse-Resolution Model of the North Atlantic Ocean, J. Atmos. Ocean. Tech., 17, 698–707, https://doi.org/10.1175/1520-0426(2000)017<0698:EOABBL>2.0.CO;2, 2000.
Downes, S. M., Farneti, R., Uotila, P., Griffies, S. M., Marsland, S. J., Bailey, D., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Canuto, V. M., Chassignet, E., Danabasoglu, G., Danilov, S., Diansky, N., Drange, H., Fogli, P. G., Gusev, A., Howard, A., Ilicak, M., Jung, T., Kelley, M., Large, W. G., Leboissetier, A., Long, M., Lu, J., Masina, S., Mishra, A., Navarra, A., Nurser, A. J. G., Patara, L., Samuels, B. L., Sidorenko, D., Spence, P., Tsujino, H., Wang, Q., and Yeager, S. G.:
An assessment of Southern Ocean water masses and sea ice during 1988–2007 in a suite of interannual CORE-II simulations, Ocean Model., 94, 67–94, https://doi.org/10.1016/j.ocemod.2015.07.022, 2015.
DuVivier, A. K., Large, W. G., and Small, R. J.:
Argo Observations of the Deep Mixing Band in the Southern Ocean: A Salinity Modeling Challenge, J. Geophys. Res.-Oceans, 123, 7599–7617, https://doi.org/10.1029/2018JC014275, 2018.
Eyring, V., Gillet, N. P., Achuta Rao, K. M., Barimalala, R., Barreiro Parillo, M., Bellouin, N., Cassou, C., and Durack, P. J.:
Human Influence on the Climate System, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, 423–552, 2021.
Fogli, P. G., Iovino, D., and Lovato, T.:
CMCC CMCC-CM2-SR5 model output prepared for CMIP6 OMIP omip1, WCRP [data set], https://doi.org/10.22033/ESGF/CMIP6.13230, 2020.
Fox-Kemper, B., Ferrari, R., and Hallberg, R.:
Parameterization of Mixed Layer Eddies. Part I: Theory and Diagnosis, J. Phys. Oceanogr., 38, 1145–1165, https://doi.org/10.1175/2007JPO3792.1, 2008.
Fox-Kemper, B., Danabasoglu, G., Ferrari, R., Griffies, S. M., Hallberg, R. W., Holland, M. M., Maltrud, M. E., Peacock, S., and Samuels, B. L.:
Parameterization of mixed layer eddies. III: Implementation and impact in global ocean climate simulations, Model. Underst. Ocean Mesoscale Submesoscale, 39, 61–78, https://doi.org/10.1016/j.ocemod.2010.09.002, 2011.
Fox-Kemper, B., Hewitt, H. T., Xiao, C., Adalgeirsdottir, G., Drijfhout, S. S., Edwards, T. L., Golledge, N. R., Hemer, M., Kopp, R. E., Krinner, G., Mix, A., Notz, D., Nowicki, S., Nurhati, I. S., Ruiz, L., Sallee, J.-B., Slangen, A. B. A., and Yu, Y.:
Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, United Kingdom and New York, NY, USA, 1211–1362, https://doi.org/10.1017/9781009157896.011, 2021.
Gaillard, F., Reynaud, T., Thierry, V., Kolodziejczyk, N., and von Schuckmann, K.:
In Situ–Based Reanalysis of the Global Ocean Temperature and Salinity with ISAS: Variability of the Heat Content and Steric Height, J. Climate, 29, 1305–1323, https://doi.org/10.1175/JCLI-D-15-0028.1, 2016.
García-Ibáñez, M. I., Pardo, P. C., Carracedo, L. I., Mercier, H., Lherminier, P., Ríos, A. F., and Pérez, F. F.:
Structure, transports and transformations of the water masses in the Atlantic Subpolar Gyre, Prog. Oceanogr., 135, 18–36, https://doi.org/10.1016/j.pocean.2015.03.009, 2015.
Gaube, P., J. McGillicuddy Jr., D., and Moulin, A. J.:
Mesoscale Eddies Modulate Mixed Layer Depth Globally, Geophys. Res. Lett., 46, 1505–1512, https://doi.org/10.1029/2018GL080006, 2019.
Gelderloos, R., Katsman, C. A., and Drijfhout, S. S.:
Assessing the Roles of Three Eddy Types in Restratifying the Labrador Sea after Deep Convection, J. Phys. Oceanogr., 41, 2102–2119, https://doi.org/10.1175/JPO-D-11-054.1, 2011.
Griffies, S. M.:
Elements of the Modular Ocean Model (MOM) (2012 release with updates), NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, USA, 2012.
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, https://doi.org/10.1016/j.ocemod.2008.08.007, 2009.
Griffies, S. M., Danabasoglu, G., Durack, P. J., Adcroft, A. J., Balaji, V., Böning, C. W., Chassignet, E. P., Curchitser, E., Deshayes, J., Drange, H., Fox-Kemper, B., Gleckler, P. J., Gregory, J. M., Haak, H., Hallberg, R. W., Heimbach, P., Hewitt, H. T., Holland, D. M., Ilyina, T., Jungclaus, J. H., Komuro, Y., Krasting, J. P., Large, W. G., Marsland, S. J., Masina, S., McDougall, T. J., Nurser, A. J. G., Orr, J. C., Pirani, A., Qiao, F., Stouffer, R. J., Taylor, K. E., Treguier, A. M., Tsujino, H., Uotila, P., Valdivieso, M., Wang, Q., Winton, M., and Yeager, S. G.:
OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project, Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, 2016.
Grist, J. P., Josey, S. A., New, A. L., Roberts, M., Koenigk, T., and Iovino, D.:
Increasing Atlantic Ocean Heat Transport in the Latest Generation Coupled Ocean-Atmosphere Models: The Role of Air-Sea Interaction, J. Geophys. Res.-Oceans, 123, 8624–8637, https://doi.org/10.1029/2018JC014387, 2018.
Haarsma, R. J., Roberts, M. J., Vidale, P. L., Senior, C. A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N. S., Guemas, V., von Hardenberg, J., Hazeleger, W., Kodama, C., Koenigk, T., Leung, L. R., Lu, J., Luo, J.-J., Mao, J., Mizielinski, M. S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., Small, J., and von Storch, J.-S.:
High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6, Geosci. Model Dev., 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, 2016.
Haney, S., Bachman, S., Cooper, B., Kupper, S., McCaffrey, K., Van Roekel, L., Stevenson, S., Fox-Kemper, B., and Ferrari, R.:
Hurricane wake restratification rates of one-, two- and three-dimensional processes, J. Mar. Res., 70, https://elischolar.library.yale.edu/journal_of_marine_research/361 (last access: 1 July 2023), 2012.
Hausmann, U., McGillicuddy Jr., D. J., and Marshall, J.:
Observed mesoscale eddy signatures in Southern Ocean surface mixed-layer depth, J. Geophys. Res.-Oceans, 122, 617–635, https://doi.org/10.1002/2016JC012225, 2017.
Hayashida, H., Kiss, A., Hogg, A., Hannah, N., Dias, F. B., Brassington, G., Chamberlain, M., Chapman, C., Dobrohotoff, P., Domingues, C. M., Duran, E., England, M., Fiedler, R., Griffies, S. M., Heerdegen, A., Heil, P., Holmes, R., Klocker, A., Marsland, S., Morrison, A., Munroe, J., Nikurashin, M., Oke, P. R., Pilo, G. S., Richet, O., Savita, A., Spence, P., Stewart, K. D., Ward, M., Wu, F., Zhang, X., Mackallah, C., and Druken, K.:
CSIRO-COSIMA ACCESS-OM2 model output prepared for CMIP6 OMIP omip2, WCRP [data set], https://doi.org/10.22033/ESGF/CMIP6.14689, 2021.
Hecht, M. and Hasumi, H.:
Ocean Modelling in the Eddying regime, Wiley, Washington D.C., USA, ISBN 978-0-87590-442-9, 2008.
Helber, R. W., Kara, A. B., Richman, J. G., Carnes, M. R., Barron, C. N., Hurlburt, H. E., and Boyer, T.:
Temperature versus salinity gradients below the ocean mixed layer, J. Geophys. Res.-Oceans, 117, C05006, https://doi.org/10.1029/2011JC007382, 2012.
Heuzé, C.:
Antarctic Bottom Water and North Atlantic Deep Water in CMIP6 models, Ocean Sci., 17, 59–90, https://doi.org/10.5194/os-17-59-2021, 2021.
Holte, J. and Talley, L.:
A New Algorithm for Finding Mixed Layer Depths with Applications to Argo Data and Subantarctic Mode Water Formation, J. Atmos. Ocean. Tech., 26, 1920–1939, https://doi.org/10.1175/2009JTECHO543.1, 2009.
Holte, J., Talley, L. D., Gilson, J., and Roemmich, D.:
An Argo mixed layer climatology and database, Geophys. Res. Lett., 44, 5618–5626, https://doi.org/10.1002/2017GL073426, 2017.
Huang, C. J., Qiao, F., and Dai, D.:
Evaluating CMIP5 simulations of mixed layer depth during summer, J. Geophys. Res.-Oceans, 119, 2568–2582, https://doi.org/10.1002/2013JC009535, 2014.
Huang, P.-Q., Lu, Y.-Z., and Zhou, S.-Q.:
An Objective Method for Determining Ocean Mixed Layer Depth with Applications to WOCE Data, J. Atmos. Ocean. Tech., 35, 441–458, https://doi.org/10.1175/JTECH-D-17-0104.1, 2018.
Hunke, E. and Lipscomb, W. H.:
CICE: The Los Alamos Sea Ice Model Documentation and Software User's Manual Version 4.1, Los Alamos National Laboratory, Los Alamos, 2008.
Hunke, E., Lipscomb, W. H., Turner, A. K., Jeffery, N., and and Elliott, S.:
CICE: The Los Alamos Sea Ice Model Documentation and Software User's Manual Version 5.1, Los Alamos National Laboratory, Los Alamos, NM, USA, 2015.
Iovino, D., Masina, S., Storto, A., Cipollone, A., and Stepanov, V. N.:
A
Jochum, M.:
Impact of latitudinal variations in vertical diffusivity on climate simulations, J. Geophys. Res.-Oceans, 114, C01010, https://doi.org/10.1029/2008JC005030, 2009.
Johnson, G. C. and Lyman, J. M.:
GOSML: A Global Ocean Surface Mixed Layer Statistical Monthly Climatology: Means, Percentiles, Skewness, and Kurtosis, J. Geophys. Res.-Oceans, 127, e2021JC018219, https://doi.org/10.1029/2021JC018219, 2022.
Johnston, T. M. S. and Rudnick, D. L.:
Observations of the Transition Layer, J. Phys. Oceanogr., 39, 780–797, https://doi.org/10.1175/2008JPO3824.1, 2009.
Kiss, A. E., Hogg, A. McC., Hannah, N., Boeira Dias, F., Brassington, G. B., Chamberlain, M. A., Chapman, C., Dobrohotoff, P., Domingues, C. M., Duran, E. R., England, M. H., Fiedler, R., Griffies, S. M., Heerdegen, A., Heil, P., Holmes, R. M., Klocker, A., Marsland, S. J., Morrison, A. K., Munroe, J., Nikurashin, M., Oke, P. R., Pilo, G. S., Richet, O., Savita, A., Spence, P., Stewart, K. D., Ward, M. L., Wu, F., and Zhang, X.:
ACCESS-OM2 v1.0: a global ocean–sea ice model at three resolutions, Geosci. Model Dev., 13, 401–442, https://doi.org/10.5194/gmd-13-401-2020, 2020.
Kiss, A. E., Hogg, A. McC., Hannah, N., Boeira Dias, F., Brassington, G. B., Chamberlain, M. A., Chapman, C., Dobrohotoff, P., Domingues, C. M., Duran, E. R., England, M. H., Fiedler, R., Griffies, S. M., Heerdegen, A., Heil, P., Holmes, R. M., Klocker, A., Marsland, S. J., Morrison, A. K., Munroe, J., Nikurashin, M., Oke, P. R., Pilo, G. S., Richet, O., Savita, A., Spence, P., Stewart, K. D., Ward, M. L., Wu, F., and Zhang, X.: ACCESS-OM2 0.1 degree global model output (interannual forcing simulation), NCI Data Catalogue [data set], https://doi.org/10.25914/608097cb3433f, 2022.
Large, W. G. and Caron, J. M.:
Diurnal cycling of sea surface temperature, salinity, and current in the CESM coupled climate model, J. Geophys. Res.-Oceans, 120, 3711–3729, https://doi.org/10.1002/2014JC010691, 2015.
Large, W. G. and Yeager, S. G.: The global climatology of an interannually varying air-sea flux data set, Clim. Dynam., 33, 341–364, https://doi.org/10.1007/s00382-008-0441-3, 2009.
Large, W. G., McWilliams, J. C., and Doney, S. C.:
Oceanic vertical mixing: A review and a model with a nonlocal boundary layer parameterization, Rev. Geophys., 32, 363–403, https://doi.org/10.1029/94RG01872, 1994.
Large, W. G., Danabasoglu, G., Doney, S. C., and McWilliams, J. C.:
Sensitivity to Surface Forcing and Boundary Layer Mixing in a Global Ocean Model: Annual-Mean Climatology, J. Phys. Oceanogr., 27, 2418–2447, https://doi.org/10.1175/1520-0485(1997)027<2418:STSFAB>2.0.CO;2, 1997.
Lee, H.-C., Rosati, A., and Spelman, M. J.:
Barotropic tidal mixing effects in a coupled climate model: Oceanic conditions in the Northern Atlantic, Ocean Model., 11, 464–477, https://doi.org/10.1016/j.ocemod.2005.03.003, 2006.
Lherminier, P., Gascard, J.-C., and Quadfasel, D.:
The Greenland Sea in Water 1993 and 1994: preconditioning for deep convection, Deep Sea Res. Part II Top. Stud. Oceanogr., 46, 1199–1235, https://doi.org/10.1016/S0967-0645(99)00020-X, 1999.
Li, L., Yu, Y., Tang, Y., Lin, P., Xie, J., Song, M., Dong, L., Zhou, T., Liu, L., Wang, L., Pu, Y., Chen, X., Chen, L., Xie, Z., Liu, H., Zhang, L., Huang, X., Feng, T., Zheng, W., Xia, K., Liu, H., Liu, J., Wang, Y., Wang, L., Jia, B., Xie, F., Wang, B., Zhao, S., Yu, Z., Zhao, B., and Wei, J.:
The Flexible Global Ocean-Atmosphere-Land System Model Grid-Point Version 3 (FGOALS-g3): Description and Evaluation, J. Adv. Model. Earth Sy., 12, e2019MS002012, https://doi.org/10.1029/2019MS002012, 2020.
Li, Q. and Fox-Kemper, B.:
Anisotropy of Langmuir turbulence and the Langmuir-enhanced mixed layer entrainment, Phys Rev Fluids, 5, 013803, https://doi.org/10.1103/PhysRevFluids.5.013803, 2020.
Li, Q., Webb, A., Fox-Kemper, B., Craig, A., Danabasoglu, G., Large, W. G., and Vertenstein, M.:
Langmuir mixing effects on global climate: WAVEWATCH III in CESM, Waves Coast. Reg. Glob. Process., 103, 145–160, https://doi.org/10.1016/j.ocemod.2015.07.020, 2016.
Li, Q., Fox-Kemper, B., Breivik, Ø., and Webb, A.:
Statistical models of global Langmuir mixing, Ocean Model., 113, 95–114, https://doi.org/10.1016/j.ocemod.2017.03.016, 2017.
Li, Q., Reichl, B. G., Fox-Kemper, B., Adcroft, A. J., Belcher, S. E., Danabasoglu, G., Grant, A. L. M., Griffies, S. M., Hallberg, R., Hara, T., Harcourt, R. R., Kukulka, T., Large, W. G., McWilliams, J. C., Pearson, B., Sullivan, P. P., Van Roekel, L., Wang, P., and Zheng, Z.:
Comparing Ocean Surface Boundary Vertical Mixing Schemes Including Langmuir Turbulence, J. Adv. Model. Earth Sy., 11, 3545–3592, https://doi.org/10.1029/2019MS001810, 2019.
Lin, P.:
CAS FGOALS-f3-L model output prepared for CMIP6 OMIP omip1, WCRP [data set], https://doi.org/10.22033/ESGF/CMIP6.3413, 2019.
Lin, P.:
CAS FGOALS-f3-H model output prepared for CMIP6 OMIP omip2, WCRP [data set], https://doi.org/10.22033/ESGF/CMIP6.13283, 2020.
Lin, P., Yu, Z., Liu, H., Yu, Y., Li, Y., Jiang, J., Xue, W., Chen, K., Yang, Q., Zhao, B., Wei, J., Ding, M., Sun, Z., Wang, Y., Meng, Y., Zheng, W., and Ma, J.:
LICOM Model Datasets for the CMIP6 Ocean Model Intercomparison Project, Adv. Atmos. Sci., 37, 239–249, https://doi.org/10.1007/s00376-019-9208-5, 2020.
Llort, J., Lévy, M., Sallée, J. B., and Tagliabue, A.:
Nonmonotonic Response of Primary Production and Export to Changes in Mixed-Layer Depth in the Southern Ocean, Geophys. Res. Lett., 46, 3368–3377, https://doi.org/10.1029/2018GL081788, 2019.
Lorbacher, K., Dommenget, D., Niiler, P. P., and Köhl, A.:
Ocean mixed layer depth: A subsurface proxy of ocean-atmosphere variability, J. Geophys. Res., 111, C07010, https://doi.org/10.1029/2003JC002157, 2006.
MacKinnon, J. A., Nash, J. D., Alford, M. H., Lucas, A. J., Mickett, J. B., Shroyer, E. L., Waterhouse, A. F., Tandon, A., Sengupta, D., Mahadevan, A., Ravichandran, M., Pinkel, R., Rudnick, D. L., Whalen, C. B., Alberty, M. S., Lekha, J. S., Fine, E. C., Chaudhuri, D., and Wagner, G. L.:
A Tale of Two Spicy Seas, Oceanography, 29, 50–61, https://doi.org/10.5670/oceanog.2016.38, 2016.
Madec, G. and the NEMO team:
NEMO reference manual 3_6_STABLE, Institut Pierre-Simon Laplace (IPSL), Paris, France, France, 2016.
Mensa, J. A., Garraffo, Z., Griffa, A., Özgökmen, T. M., Haza, A., and Veneziani, M.:
Seasonality of the submesoscale dynamics in the Gulf Stream region, Ocean Dyn., 63, 923–941, https://doi.org/10.1007/s10236-013-0633-1, 2013.
Mignot, J., de Boyer Montégut, C., Lazar, A., and Cravatte, S.:
Control of salinity on the mixed layer depth in the world ocean: 2. Tropical areas, J. Geophys. Res.-Oceans, 112, C06011, https://doi.org/10.1029/2006JC003954, 2007.
Pan, R., Shu, Q., Wang, Q., Wang, S., Song, Z., He, Y., and Qiao, F.:
Future Arctic climate change in CMIP6 strikingly intensified by NEMO-family climate models, Geophys. Res. Lett., 50, e2022GL102077, https://doi.org/10.1029/2022GL102077, 2023.
Pellichero, V., Sallée, J.-B., Schmidtko, S., Roquet, F., and Charrassin, J.-B.:
The ocean mixed layer under Southern Ocean sea-ice: Seasonal cycle and forcing, J. Geophys. Res.-Oceans, 122, 1608–1633, https://doi.org/10.1002/2016JC011970, 2017.
Peralta-Ferriz, C. and Woodgate, R. A.:
Seasonal and interannual variability of pan-Arctic surface mixed layer properties from 1979 to 2012 from hydrographic data, and the dominance of stratification for multiyear mixed layer depth shoaling, Prog. Oceanogr., 134, 19–53, https://doi.org/10.1016/j.pocean.2014.12.005, 2015.
Reichl, B. G. and Hallberg, R.:
A simplified energetics based planetary boundary layer (ePBL) approach for ocean climate simulations, Ocean Model., 132, 112–129, https://doi.org/10.1016/j.ocemod.2018.10.004, 2018.
Reichl, B. G., Adcroft, A., Griffies, S. M., and Hallberg, R.:
A Potential Energy Analysis of Ocean Surface Mixed Layers, J. Geophys. Res.-Oceans, 127, e2021JC018140, https://doi.org/10.1029/2021JC018140, 2022.
Roberts, M. J., Vidale, P. L., Senior, C., Hewitt, H. T., Bates, C., Berthou, S., Chang, P., Christensen, H. M., Danilov, S., Demory, M.-E., Griffies, S. M., Haarsma, R., Jung, T., Martin, G., Minobe, S., Ringler, T., Satoh, M., Schiemann, R., Scoccimarro, E., Stephens, G., and Wehner, M. F.:
The benefits of global high-resolution for climate simulation: process-understanding and the enabling of stakeholder decisions at the regional scale, B. Am. Meteorol. Soc., 99, 2341–2359, https://doi.org/10.1175/BAMS-D-15-00320.1, 2018.
Roberts, M. J., Jackson, L. C., Roberts, C. D., Meccia, V., Docquier, D., Koenigk, T., Ortega, P., Moreno-Chamarro, E., Bellucci, A., Coward, A., Drijfhout, S., Exarchou, E., Gutjahr, O., Hewitt, H., Iovino, D., Lohmann, K., Putrasahan, D., Schiemann, R., Seddon, J., Terray, L., Xu, X., Zhang, Q., Chang, P., Yeager, S. G., Castruccio, F. S., Zhang, S., and Wu, L.:
Sensitivity of the Atlantic Meridional Overturning Circulation to Model Resolution in CMIP6 HighResMIP Simulations and Implications for Future Changes, J. Adv. Model. Earth Sy., 12, e2019MS002014, https://doi.org/10.1029/2019MS002014, 2020.
Rudzin, J. E., Shay, L. K., and Johns, W. E.:
The Influence of the Barrier Layer on SST Response during Tropical Cyclone Wind Forcing Using Idealized Experiments, J. Phys. Oceanogr., 48, 1471–1478, https://doi.org/10.1175/JPO-D-17-0279.1, 2018.
Sallée, J.-B., Shuckburgh, E., Bruneau, N., Meijers, A. J. S., Bracegirdle, T. J., and Wang, Z.:
Assessment of Southern Ocean mixed-layer depths in CMIP5 models: Historical bias and forcing response, J. Geophys. Res.-Oceans, 118, 1845–1862, https://doi.org/10.1002/jgrc.20157, 2013.
Sallée, J.-B., Pellichero, V., Akhoudas, C., Pauthenet, E., Vignes, L., Schmidtko, S., Garabato, A. N., Sutherland, P., and Kuusela, M.: Summertime increases in upper-ocean stratification and mixed-layer depth, Nature, 591, 592–598, https://doi.org/10.1038/s41586-021-03303-x, 2021.
Schulze, L. M., Pickart, R. S., and Moore, G. W. K.:
Atmospheric forcing during active convection in the Labrador Sea and its impact on mixed-layer depth, J. Geophys. Res.-Oceans, 121, 6978–6992, https://doi.org/10.1002/2015JC011607, 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, https://doi.org/10.1002/2017MS001099, 2017.
Semmler, T., Jungclaus, J., Danek, C., Goessling, H. F., Koldunov, N. V., Rackow, T., and Sidorenko, D.:
Ocean Model Formulation Influences Transient Climate Response, J. Geophys. Res.-Oceans, 126, e2021JC017633, https://doi.org/10.1029/2021JC017633, 2021.
Serazin, G., Treguier, A. M., and De Boyer Montégut, C.:
A seasonal climatology of the upper ocean pycnocline, Front. Mar. Sci., in press, 2023.
Shroyer, E. L., Gordon, A. L., Jaeger, G. S., Freilich, M., Waterhouse, A. F., Farrar, J. T., Sarma, V. V. S. S., Venkatesan, R., Weller, R. A., Moum, J. N., and Mahadevan, A.:
Upper layer thermohaline structure of the Bay of Bengal during the 2013 northeast monsoon, Deep-Sea Res. Pt. II, 172, 104630, https://doi.org/10.1016/j.dsr2.2019.07.018, 2020.
Simmons, H. L., Jayne, S. R., Laurent, L. C. St., and Weaver, A. J.:
Tidally driven mixing in a numerical model of the ocean general circulation, Ocean Model., 6, 245–263, https://doi.org/10.1016/S1463-5003(03)00011-8, 2004.
Small, R. J., DuVivier, A. K., Whitt, D. B., Long, M. C., Grooms, I., and Large, W. G.:
On the control of subantarctic stratification by the ocean circulation, Clim. Dynam., 56, 299–327, https://doi.org/10.1007/s00382-020-05473-2, 2021.
Smith, R., Jones, P. W., Briegleb, P. A., Bryan, O., Danabasoglu, G., Dennis, M. L., Dukowicz, J. K., Eden, C., Fox-Kemper, B., Gent, R. van, Hecht, M., Jayne, S. R., Jochum, M., Large, G., Lindsay, K., Maltrud, M. E., Norton, J., Peacock, L., Vertenstein, M., and Yeager, S. G.:
The Parallel Ocean Program (POP) reference manual: Ocean component of the Community Climate System Model (CCSM), UCAR/NCAR, Boulder, USA, 2010.
Solodoch, A., Stewart, A. L., Hogg, A. McC., Morrison, A. K., Kiss, A. E., Thompson, A. F., Purkey, S. G., and Cimoli, L.:
How Does Antarctic Bottom Water Cross the Southern Ocean?, Geophys. Res. Lett., 49, e2021GL097211, https://doi.org/10.1029/2021GL097211, 2022.
Stewart, K. D., Hogg, A. McC., Griffies, S. M., Heerdegen, A. P., Ward, M. L., Spence, P., and England, M. H.:
Vertical resolution of baroclinic modes in global ocean models, Ocean Model., 113, 50–65, https://doi.org/10.1016/j.ocemod.2017.03.012, 2017.
Toyoda, T., Fujii, Y., Kuragano, T., Kamachi, M., Ishikawa, Y., Masuda, S., Sato, K., Awaji, T., Hernandez, F., Ferry, N., Guinehut, S., Martin, M. J., Peterson, K. A., Good, S. A., Valdivieso, M., Haines, K., Storto, A., Masina, S., Köhl, A., Zuo, H., Balmaseda, M., Yin, Y., Shi, L., Alves, O., Smith, G., Chang, Y.-S., Vernieres, G., Wang, X., Forget, G., Heimbach, P., Wang, O., Fukumori, I., and Lee, T.:
Intercomparison and validation of the mixed layer depth fields of global ocean syntheses, Clim. Dynam., 49, 753–773, https://doi.org/10.1007/s00382-015-2637-7, 2017.
Treguier, A. M., Chassignet, E., Hogg, A. McC., Kiss, A. E., Li, Y., Lin, P., Liu, H., Iovino, D., Sidorenko, D., Wang, Q., and Yeager, S.: The Mixed Layer Depth in the Ocean Model Intercomparison Project (OMIP): Impact of Resolving Mesoscale Eddies: supporting data (1.0), Zenodo [data set], https://doi.org/10.5281/zenodo.7656425, 2023.
Tsujino, H., Urakawa, S., Nakano, H., Small, R. J., Kim, W. M., Yeager, S. G., Danabasoglu, G., Suzuki, T., Bamber, J. L., Bentsen, M., Böning, C. W., Bozec, A., Chassignet, E. P., Curchitser, E., Boeira Dias, F., Durack, P. J., Griffies, S. M., Harada, Y., Ilicak, M., Josey, S. A., Kobayashi, C., Kobayashi, S., Komuro, Y., Large, W. G., Le Sommer, J., Marsland, S. J., Masina, S., Scheinert, M., Tomita, H., Valdivieso, M., and Yamazaki, D.:
JRA-55 based surface dataset for driving ocean–sea-ice models (JRA55-do), Ocean Model., 130, 79–139, https://doi.org/10.1016/j.ocemod.2018.07.002, 2018.
Tsujino, H., Urakawa, L. S., Griffies, S. M., Danabasoglu, G., Adcroft, A. J., Amaral, A. E., Arsouze, T., Bentsen, M., Bernardello, R., Böning, C. W., Bozec, A., Chassignet, E. P., Danilov, S., Dussin, R., Exarchou, E., Fogli, P. G., Fox-Kemper, B., Guo, C., Ilicak, M., Iovino, D., Kim, W. M., Koldunov, N., Lapin, V., Li, Y., Lin, P., Lindsay, K., Liu, H., Long, M. C., Komuro, Y., Marsland, S. J., Masina, S., Nummelin, A., Rieck, J. K., Ruprich-Robert, Y., Scheinert, M., Sicardi, V., Sidorenko, D., Suzuki, T., Tatebe, H., Wang, Q., Yeager, S. G., and Yu, Z.:
Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2), Geosci. Model Dev., 13, 3643–3708, https://doi.org/10.5194/gmd-13-3643-2020, 2020.
Uchida, T., Balwada, D., P. Abernathey, R., A. McKinley, G., K. Smith, S., and Lévy, M.:
Vertical eddy iron fluxes support primary production in the open Southern Ocean, Nat. Commun., 11, 1125, https://doi.org/10.1038/s41467-020-14955-0, 2020.
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.
Whitt, D. B., Nicholson, S. A., and Carranza, M. M.:
Global Impacts of Subseasonal (< 60 Day) Wind Variability on Ocean Surface Stress, Buoyancy Flux, and Mixed Layer Depth, J. Geophys. Res.-Oceans, 124, 8798–8831, https://doi.org/10.1029/2019JC015166, 2019.
Short summary
The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a...
