Articles | Volume 14, issue 3
https://doi.org/10.5194/gmd-14-1801-2021
© Author(s) 2021. 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-14-1801-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
01 Apr 2021
Development and technical paper |
| 01 Apr 2021
| 01 Apr 2021
Improved representation of river runoff in Estimating the Circulation and Climate of the Ocean Version 4 (ECCOv4) simulations: implementation, evaluation, and impacts to coastal plume regions
State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology & Institution of South China Sea Ecology and Environmental Engineering, Chinese Academy of Science, Guangzhou, China
Southern Marine Science and Engineering Guangdong Laboratory, Guangzhou, China
Guangdong Key Laboratory of Ocean Remote Sensing, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
Dimitris Menemenlis
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Huijie Xue
State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology & Institution of South China Sea Ecology and Environmental Engineering, Chinese Academy of Science, Guangzhou, China
Southern Marine Science and Engineering Guangdong Laboratory, Guangzhou, China
Hong Zhang
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Dustin Carroll
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Moss Landing Marine Laboratories, San José State University, Moss Landing, California, USA
State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology & Institution of South China Sea Ecology and Environmental Engineering, Chinese Academy of Science, Guangzhou, China
Southern Marine Science and Engineering Guangdong Laboratory, Guangzhou, China
College of Marine Science, University of Chinese Academy of Sciences, Guangzhou, China
State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, China
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Clement Bertin, Vincent Le Fouest, Dustin Carroll, Stephanie Dutkiewicz, Dimitris Menemenlis, Atsushi Matsuoka, Manfredi Manizza, and Charles E. Miller
EGUsphere, https://doi.org/10.5194/egusphere-2025-973, https://doi.org/10.5194/egusphere-2025-973, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
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We adjusted a model of the Mackenzie River region to account for the riverine export of organic matter that affects light in the water. We show that such export causes a delay in the phytoplankton growth by two weeks and raises the water surface temperature by 1.7 °C. We found that temperature increase turns this coastal region from a sink of carbon dioxide to an emitter. Our findings suggest that rising exports of organic matter can significantly affect the carbon cycle in Arctic coastal areas.
Abdullah A. Fahad, Andrea Molod, Krzysztof Wargan, Dimitris Menemenlis, Patrick Heimbach, Atanas Trayanov, Ehud Strobach, and Lawrence Coy
EGUsphere, https://doi.org/10.21203/rs.3.rs-1892797/v2, https://doi.org/10.21203/rs.3.rs-1892797/v2, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study used a 1-degree GEOS-MITgcm coupled GCM to analyze the Northern Hemisphere (NH) stratospheric temperature response to external forcing. Results show the NH polar stratospheric temperature increased from 1992 to 2000, contrary to the expectation of stratospheric cooling with rising CO2. However, from 2000 to 2020, the temperature decreased. The study concluded that changes in CO2 and Ozone drive the meridional eddy transport of heat, dictating polar stratospheric temperature behavior.
Yoshihiro Nakayama, Alena Malyarenko, Hong Zhang, Ou Wang, Matthis Auger, Yafei Nie, Ian Fenty, Matthew Mazloff, Armin Köhl, and Dimitris Menemenlis
Geosci. Model Dev., 17, 8613–8638, https://doi.org/10.5194/gmd-17-8613-2024, https://doi.org/10.5194/gmd-17-8613-2024, 2024
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Global- and basin-scale ocean reanalyses are becoming easily accessible. However, such ocean reanalyses are optimized for their entire model domains and their ability to simulate the Southern Ocean requires evaluation. We conduct intercomparison analyses of Massachusetts Institute of Technology General Circulation Model (MITgcm)-based ocean reanalyses. They generally perform well for the open ocean, but open-ocean temporal variability and Antarctic continental shelves require improvements.
Katharina Gallmeier, J. Xavier Prochaska, Peter Cornillon, Dimitris Menemenlis, and Madolyn Kelm
Geosci. Model Dev., 16, 7143–7170, https://doi.org/10.5194/gmd-16-7143-2023, https://doi.org/10.5194/gmd-16-7143-2023, 2023
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This paper introduces an approach to evaluate numerical models of ocean circulation. We compare the structure of satellite-derived sea surface temperature anomaly (SSTa) instances determined by a machine learning algorithm at 10–80 km scales to those output by a high-resolution MITgcm run. The simulation over much of the ocean reproduces the observed distribution of SSTa patterns well. This general agreement, alongside a few notable exceptions, highlights the potential of this approach.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Hector S. Torres, Patrice Klein, Jinbo Wang, Alexander Wineteer, Bo Qiu, Andrew F. Thompson, Lionel Renault, Ernesto Rodriguez, Dimitris Menemenlis, Andrea Molod, Christopher N. Hill, Ehud Strobach, Hong Zhang, Mar Flexas, and Dragana Perkovic-Martin
Geosci. Model Dev., 15, 8041–8058, https://doi.org/10.5194/gmd-15-8041-2022, https://doi.org/10.5194/gmd-15-8041-2022, 2022
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Wind work at the air-sea interface is the scalar product of winds and currents and is the transfer of kinetic energy between the ocean and the atmosphere. Using a new global coupled ocean-atmosphere simulation performed at kilometer resolution, we show that all scales of winds and currents impact the ocean dynamics at spatial and temporal scales. The consequential interplay of surface winds and currents in the numerical simulation motivates the need for a winds and currents satellite mission.
Olivier Sulpis, Matthew P. Humphreys, Monica M. Wilhelmus, Dustin Carroll, William M. Berelson, Dimitris Menemenlis, Jack J. Middelburg, and Jess F. Adkins
Geosci. Model Dev., 15, 2105–2131, https://doi.org/10.5194/gmd-15-2105-2022, https://doi.org/10.5194/gmd-15-2105-2022, 2022
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A quarter of the surface of the Earth is covered by marine sediments rich in calcium carbonates, and their dissolution acts as a giant antacid tablet protecting the ocean against human-made acidification caused by massive CO2 emissions. Here, we present a new model of sediment chemistry that incorporates the latest experimental findings on calcium carbonate dissolution kinetics. This model can be used to predict how marine sediments evolve through time in response to environmental perturbations.
Marion Kersalé, Denis L. Volkov, Kandaga Pujiana, and Hong Zhang
Ocean Sci., 18, 193–212, https://doi.org/10.5194/os-18-193-2022, https://doi.org/10.5194/os-18-193-2022, 2022
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The southern Indian Ocean is one of the major basins for regional heat accumulation and sea level rise. The year-to-year changes of regional sea level are influenced by water exchange with the Pacific Ocean via the Indonesian Throughflow. Using a general circulation model, we show that the spatiotemporal pattern of these changes is primarily set by local wind forcing modulated by El Niño–Southern Oscillation, while oceanic signals originating in the Pacific can amplify locally forced signals.
Shuangling Chen, Mark L. Wells, Rui Xin Huang, Huijie Xue, Jingyuan Xi, and Fei Chai
Biogeosciences, 18, 5539–5554, https://doi.org/10.5194/bg-18-5539-2021, https://doi.org/10.5194/bg-18-5539-2021, 2021
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Subduction transports surface waters to the oceanic interior, which can supply significant amounts of carbon and oxygen to the twilight zone. Using a novel BGC-Argo dataset covering the western North Pacific, we successfully identified the imprints of episodic shallow subduction patches. These subduction patches were observed mainly in spring and summer (70.6 %), and roughly half of them extended below ~ 450 m, injecting carbon- and oxygen-enriched waters into the ocean interior.
Yoshihiro Nakayama, Dimitris Menemenlis, Ou Wang, Hong Zhang, Ian Fenty, and An T. Nguyen
Geosci. Model Dev., 14, 4909–4924, https://doi.org/10.5194/gmd-14-4909-2021, https://doi.org/10.5194/gmd-14-4909-2021, 2021
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High ice shelf melting in the Amundsen Sea has attracted many observational campaigns in the past decade. One method to combine observations with numerical models is the adjoint method. After 20 iterations, the cost function, defined as a sum of the weighted model–data difference, is reduced by 65 % by adjusting initial conditions, atmospheric forcing, and vertical diffusivity. This study demonstrates adjoint-method optimization with explicit representation of ice shelf cavity circulation.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, https://doi.org/10.5194/essd-13-299-2021, 2021
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On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
Fei Chai, Yuntao Wang, Xiaogang Xing, Yunwei Yan, Huijie Xue, Mark Wells, and Emmanuel Boss
Biogeosciences, 18, 849–859, https://doi.org/10.5194/bg-18-849-2021, https://doi.org/10.5194/bg-18-849-2021, 2021
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The unique observations by a Biogeochemical Argo float in the NW Pacific Ocean captured the impact of a super typhoon on upper-ocean physical and biological processes. Our result reveals typhoons can increase the surface chlorophyll through strong vertical mixing without bringing nutrients upward from the depth. The vertical redistribution of chlorophyll contributes little to enhance the primary production, which is contradictory to many former satellite-based studies related to this topic.
Jianrong Zhu, Xinyue Cheng, Linjiang Li, Hui Wu, Jinghua Gu, and Hanghang Lyu
Hydrol. Earth Syst. Sci., 24, 5043–5056, https://doi.org/10.5194/hess-24-5043-2020, https://doi.org/10.5194/hess-24-5043-2020, 2020
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An extremely severe saltwater intrusion event occurred in February 2014 in the Changjiang estuary and seriously influenced the water intake of the reservoir. For the event cause and for freshwater safety, the dynamic mechanism was studied with observed data and a numerical model. The results indicated that this event was caused by a persistent and strong northerly wind, which formed a horizontal estuarine circulation, surpassed seaward runoff and drove highly saline water into the estuary.
Mark J. Hopwood, Dustin Carroll, Thorben Dunse, Andy Hodson, Johnna M. Holding, José L. Iriarte, Sofia Ribeiro, Eric P. Achterberg, Carolina Cantoni, Daniel F. Carlson, Melissa Chierici, Jennifer S. Clarke, Stefano Cozzi, Agneta Fransson, Thomas Juul-Pedersen, Mie H. S. Winding, and Lorenz Meire
The Cryosphere, 14, 1347–1383, https://doi.org/10.5194/tc-14-1347-2020, https://doi.org/10.5194/tc-14-1347-2020, 2020
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Here we compare and contrast results from five well-studied Arctic field sites in order to understand how glaciers affect marine biogeochemistry and marine primary production. The key questions are listed as follows. Where and when does glacial freshwater discharge promote or reduce marine primary production? How does spatio-temporal variability in glacial discharge affect marine primary production? And how far-reaching are the effects of glacial discharge on marine biogeochemistry?
S. Zheng, Y. Du, J. Li, and X. Cheng
Ocean Sci., 11, 361–371, https://doi.org/10.5194/os-11-361-2015, https://doi.org/10.5194/os-11-361-2015, 2015
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Eddies in the South Indian Ocean (SIO) were statistically investigated based on 2082 surface drifters, and 19252 eddies were identified with 60% anticyclonic eddies. Mesoscale and submesoscale eddies show different spatial distributions. Large eddies mainly appear in regions with large eddy kinetic energy. The submesoscale anticyclonic eddies are densely distributed in the subtropical basin in the central SIO. The number of mesoscale eddies shows statistically significant seasonal variability.
A. Wang, Y. Du, W. Zhuang, and Y. Qi
Ocean Sci., 11, 305–312, https://doi.org/10.5194/os-11-305-2015, https://doi.org/10.5194/os-11-305-2015, 2015
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Here, we investigated the seasonal variability of subsurface high-salinity water (SHSW) in the northern South China Sea (SCS) and its relationship with the North Equatorial Current-Kuroshio circulation system. Results give new insight into water exchange through the Luzon Strait (LS). The changes in western Pacific large-scale circulation modulate the water exchange in the LS, and thus influence the SHSW in the interior SCS basin.
Related subject area
Oceanography
A new global high-resolution wave model for the tropical ocean using WAVEWATCH III version 7.14
sedInterFoam 1.0: a three-phase numerical model for sediment transport applications with free surfaces
The Ross Sea and Amundsen Sea Ice–Sea Model (RAISE v1.0): a high-resolution ocean–sea ice–ice shelf coupling model for simulating the Dense Shelf Water and Antarctic Bottom Water in the Ross Sea, Antarctica
Sensitivity of the tropical Atlantic to vertical mixing in two ocean models (ICON-O v2.6.6 and FESOM v2.5)
HIDRA3: a deep-learning model for multipoint ensemble sea level forecasting in the presence of tide gauge sensor failures
A wave-resolving two-dimensional vertical Lagrangian approach to model microplastic transport in nearshore waters based on TrackMPD 3.0
HOTSSea v1: a NEMO-based physical Hindcast of the Salish Sea (1980–2018) supporting ecosystem model development
DalROMS-NWA12 v1.0, a coupled circulation–ice–biogeochemistry modelling system for the northwest Atlantic Ocean: development and validation
A revised ocean mixed layer model for better simulating the diurnal variation in ocean skin temperature
Evaluating an accelerated forcing approach for improving computational efficiency in coupled ice sheet–ocean modelling
An optimal transformation method for inferring ocean tracer sources and sinks
PPCon 1.0: Biogeochemical-Argo profile prediction with 1D convolutional networks
Updates to the Met Office’s global ocean-sea ice forecasting system including model and data assimilation changes
Using automatic calibration to improve the physics behind complex numerical models: An example from a 3D lake model using Delft3d (v6.02.10) and DYNO-PODS (v1.0)
An Effective Communication Topology for Performance Optimization: A Case Study of the Finite Volume WAve Modeling (FVWAM)
Experimental design for the Marine Ice Sheet–Ocean Model Intercomparison Project – phase 2 (MISOMIP2)
Development of a total variation diminishing (TVD) sea ice transport scheme and its application in an ocean (SCHISM v5.11) and sea ice (Icepack v1.3.4) coupled model on unstructured grids
Spurious numerical mixing under strong tidal forcing: a case study in the south-east Asian seas using the Symphonie model (v3.1.2)
Modelling the water isotope distribution in the Mediterranean Sea using a high-resolution oceanic model (NEMO-MED12-watiso v1.0): evaluation of model results against in situ observations
LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry
GREAT v1.0: Global Real-time Early Assessment of Tsunamis
PIBM 1.0: An individual-based model for simulating phytoplankton acclimation, diversity, and evolution in the ocean
Towards a real-time modeling of global ocean waves by the fully GPU-accelerated spectral wave model WAM6-GPU v1.0
A simple approach to represent precipitation-derived freshwater fluxes into nearshore ocean models: an FVCOM4.1 case study of Quatsino Sound, British Columbia
An optimal transformation method applied to diagnose the ocean carbon budget
Implementation and assessment of a model including mixotrophs and the carbonate cycle (Eco3M_MIX-CarbOx v1.0) in a highly dynamic Mediterranean coastal environment (Bay of Marseille, France) – Part 2: Towards a better representation of total alkalinity when modeling the carbonate system and air–sea CO2 fluxes
Development of a novel storm surge inundation model framework for efficient prediction
Skin sea surface temperature schemes in coupled ocean–atmosphere modelling: the impact of chlorophyll-interactive e-folding depth
Resolution dependence of interlinked Southern Ocean biases in global coupled HadGEM3 models
DELWAVE 1.0: deep learning surrogate model of surface wave climate in the Adriatic Basin
StraitFlux – precise computations of water strait fluxes on various modeling grids
Comparison of the Coastal and Regional Ocean COmmunity model (CROCO) and NCAR-LES in non-hydrostatic simulations
Intercomparisons of Tracker v1.1 and four other ocean particle-tracking software packages in the Regional Ocean Modeling System
CAR36, a regional high-resolution ocean forecasting system for improving drift and beaching of Sargassum in the Caribbean archipelago
Implementation of additional spectral wave field exchanges in a three-dimensional wave–current coupled WAVEWATCH-III (version 6.07) and CROCO (version 1.2) configuration: assessment of their implications for macro-tidal coastal hydrodynamics
Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system
LOCATE v1.0: numerical modelling of floating marine debris dispersion in coastal regions using Parcels v2.4.2
New insights into the South China Sea throughflow and water budget seasonal cycle: evaluation and analysis of a high-resolution configuration of the ocean model SYMPHONIE version 2.4
MQGeometry-1.0: a multi-layer quasi-geostrophic solver on non-rectangular geometries
Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on El Niño–Southern Oscillation forecasts
Great Lakes wave forecast system on high-resolution unstructured meshes
Impact of increased resolution on Arctic Ocean simulations in Ocean Model Intercomparison Project phase 2 (OMIP-2)
A high-resolution physical–biogeochemical model for marine resource applications in the northwest Atlantic (MOM6-COBALT-NWA12 v1.0)
A flexible z-layers approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)
Implementation and assessment of a model including mixotrophs and the carbonate cycle (Eco3M_MIX-CarbOx v1.0) in a highly dynamic Mediterranean coastal environment (Bay of Marseille, France) – Part 1: Evolution of ecosystem composition under limited light and nutrient conditions
Ocean wave tracing v.1: a numerical solver of the wave ray equations for ocean waves on variable currents at arbitrary depths
Design and evaluation of an efficient high-precision ocean surface wave model with a multiscale grid system (MSG_Wav1.0)
Evaluation of the CMCC global eddying ocean model for the Ocean Model Intercomparison Project (OMIP2)
Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard
Open-ocean tides simulated by ICON-O, version icon-2.6.6
Axelle Gaffet, Xavier Bertin, Damien Sous, Héloïse Michaud, Aron Roland, and Emmanuel Cordier
Geosci. Model Dev., 18, 1929–1946, https://doi.org/10.5194/gmd-18-1929-2025, https://doi.org/10.5194/gmd-18-1929-2025, 2025
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This study presents a new global wave model that improves predictions of sea states in tropical areas by using a high-resolution grid and corrected wind fields. The model is validated globally with satellite data and nearshore using in situ data. The model allows for the first time direct comparisons with in situ data collected at 10–30 m water depth, which is very close to shore due to the steep slope usually surrounding volcanic islands.
Antoine Mathieu, Yeulwoo Kim, Tian-Jian Hsu, Cyrille Bonamy, and Julien Chauchat
Geosci. Model Dev., 18, 1561–1573, https://doi.org/10.5194/gmd-18-1561-2025, https://doi.org/10.5194/gmd-18-1561-2025, 2025
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Most of the tools available to model sediment transport do not account for complex physical mechanisms such as surface-wave-driven processes. In this study, a new model, sedInterFoam, allows us to reproduce numerically complex configurations in order to investigate coastal sediment transport applications dominated by surface waves and to gain insight into the complex physical processes associated with breaking waves and morphodynamics.
Zhaoru Zhang, Chuan Xie, Chuning Wang, Yuanjie Chen, Heng Hu, and Xiaoqiao Wang
Geosci. Model Dev., 18, 1375–1393, https://doi.org/10.5194/gmd-18-1375-2025, https://doi.org/10.5194/gmd-18-1375-2025, 2025
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A coupled fine-resolution ocean–ice model is developed for the Ross Sea and adjacent regions in Antarctica, a key area for the formation of global ocean bottom water, the Antarctic Bottom Water (AABW), which affects global ocean circulation. The model has a high skill level in simulating sea ice production driving the AABW source water formation and AABW properties when assessed against observations. A model experiment shows a significant impact of ice shelf melting on the AABW characteristics.
Swantje Bastin, Aleksei Koldunov, Florian Schütte, Oliver Gutjahr, Marta Agnieszka Mrozowska, Tim Fischer, Radomyra Shevchenko, Arjun Kumar, Nikolay Koldunov, Helmuth Haak, Nils Brüggemann, Rebecca Hummels, Mia Sophie Specht, Johann Jungclaus, Sergey Danilov, Marcus Dengler, and Markus Jochum
Geosci. Model Dev., 18, 1189–1220, https://doi.org/10.5194/gmd-18-1189-2025, https://doi.org/10.5194/gmd-18-1189-2025, 2025
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Vertical mixing is an important process, for example, for tropical sea surface temperature, but cannot be resolved by ocean models. Comparisons of mixing schemes and settings have usually been done with a single model, sometimes yielding conflicting results. We systematically compare two widely used schemes with different parameter settings in two different ocean models and show that most effects from mixing scheme parameter changes are model-dependent.
Marko Rus, Hrvoje Mihanović, Matjaž Ličer, and Matej Kristan
Geosci. Model Dev., 18, 605–620, https://doi.org/10.5194/gmd-18-605-2025, https://doi.org/10.5194/gmd-18-605-2025, 2025
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HIDRA3 is a deep-learning model for predicting sea levels and storm surges, offering significant improvements over previous models and numerical simulations. It utilizes data from multiple tide gauges, enhancing predictions even with limited historical data and during sensor outages. With its advanced architecture, HIDRA3 outperforms current state-of-the-art models by achieving a mean absolute error of up to 15 % lower, proving effective for coastal flood forecasting under diverse conditions.
Isabel Jalón-Rojas, Damien Sous, and Vincent Marieu
Geosci. Model Dev., 18, 319–336, https://doi.org/10.5194/gmd-18-319-2025, https://doi.org/10.5194/gmd-18-319-2025, 2025
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This study presents a novel modeling approach for understanding microplastic transport in coastal waters. The model accurately replicates experimental data and reveals key transport mechanisms. The findings enhance our knowledge of how microplastics move in nearshore environments, aiding in coastal management and efforts to combat plastic pollution globally.
Greig Oldford, Tereza Jarníková, Villy Christensen, and Michael Dunphy
Geosci. Model Dev., 18, 211–237, https://doi.org/10.5194/gmd-18-211-2025, https://doi.org/10.5194/gmd-18-211-2025, 2025
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We developed a 3D ocean model called the Hindcast of the Salish Sea (HOTSSea v1) that recreates physical conditions throughout the Salish Sea from 1980 to 2018. It was not clear that acceptable accuracy could be achieved because of computational and data limitations, but the model's predictions agreed well with observations. When we used the model to examine ocean temperature trends in areas that lack observations, it indicated that some seasons and areas are warming faster than others.
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
Geosci. Model Dev., 17, 8697–8733, https://doi.org/10.5194/gmd-17-8697-2024, https://doi.org/10.5194/gmd-17-8697-2024, 2024
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We developed a modelling system of the northwest Atlantic Ocean that simulates the currents, temperature, salinity, and parts of the biochemical cycle of the ocean, as well as sea ice. The system combines advanced, open-source models and can be used to study, for example, the ocean capture of atmospheric carbon dioxide, which is a key process in the global climate. The system produces realistic results, and we use it to investigate the roles of tides and sea ice in the northwest Atlantic Ocean.
Eui-Jong Kang, Byung-Ju Sohn, Sang-Woo Kim, Wonho Kim, Young-Cheol Kwon, Seung-Bum Kim, Hyoung-Wook Chun, and Chao Liu
Geosci. Model Dev., 17, 8553–8568, https://doi.org/10.5194/gmd-17-8553-2024, https://doi.org/10.5194/gmd-17-8553-2024, 2024
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Sea surface temperature (SST) is vital in climate, weather, and ocean sciences because it influences air–sea interactions. Errors in the ECMWF model's scheme for predicting ocean skin temperature prompted a revision of the ocean mixed layer model. Validation against infrared measurements and buoys showed a good correlation with minimal deviations. The revised model accurately simulates SST variations and aligns with solar radiation distributions, showing promise for weather and climate models.
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev., 17, 8243–8265, https://doi.org/10.5194/gmd-17-8243-2024, https://doi.org/10.5194/gmd-17-8243-2024, 2024
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We introduce an accelerated forcing approach to address timescale discrepancies between the ice sheets and ocean components in coupled modelling by reducing the ocean simulation duration. The approach is evaluated using idealized coupled models, and its limitations in real-world applications are discussed. Our results suggest it can be a valuable tool for process-oriented coupled ice sheet–ocean modelling and downscaling climate simulations with such models.
Jan D. Zika and Taimoor Sohail
Geosci. Model Dev., 17, 8049–8068, https://doi.org/10.5194/gmd-17-8049-2024, https://doi.org/10.5194/gmd-17-8049-2024, 2024
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We describe a method to relate fluxes of heat and freshwater at the sea surface to the resulting distribution of seawater among categories such as warm and salty or cold and salty. The method exploits the laws that govern how heat and salt change when water mixes. The method will allow the climate community to improve estimates of how much heat the ocean is absorbing and how rainfall and evaporation are changing across the globe.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
Geosci. Model Dev., 17, 7347–7364, https://doi.org/10.5194/gmd-17-7347-2024, https://doi.org/10.5194/gmd-17-7347-2024, 2024
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Monitoring the ocean is essential for studying marine life and human impact. Our new software, PPCon, uses ocean data to predict key factors like nitrate and chlorophyll levels, which are hard to measure directly. By leveraging machine learning, PPCon offers more accurate and efficient predictions.
Davi Mignac, Jennifer Waters, Daniel J. Lea, Matthew J. Martin, James While, Anthony T. Weaver, Arthur Vidard, Catherine Guiavarc’h, Dave Storkey, David Ford, Edward W. Blockley, Jonathan Baker, Keith Haines, Martin R. Price, Michael J. Bell, and Richard Renshaw
EGUsphere, https://doi.org/10.5194/egusphere-2024-3143, https://doi.org/10.5194/egusphere-2024-3143, 2024
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We describe major improvements of the Met Office's global ocean-sea ice forecasting system. The models and the way observations are used to improve the forecasts were changed, which led to a significant error reduction of 1-day forecasts. The new system performance in past conditions, where sub-surface observations are scarce, was improved with more consistent ocean heat content estimates. The new system will be of better use for climate studies and will provide improved forecasts for end users.
Marina Amadori, Abolfazl Irani Rahaghi, Damien Bouffard, and Marco Toffolon
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-118, https://doi.org/10.5194/gmd-2024-118, 2024
Revised manuscript accepted for GMD
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Models simplify reality using assumptions, which can sometimes introduce flaws and affect their accuracy. Properly calibrating model parameters is essential, and although automated tools can speed up this process, they may occasionally produce incorrect values due to inconsistencies in the model. We demonstrate that by carefully applying automated tools, we were able to identify and correct a flaw in a widely used model for lake environments.
Renbo Pang, Fujiang Yu, Yuanyong Gao, Ye Yuan, Liang Yuan, and Zhiyi Gao
EGUsphere, https://doi.org/10.5194/egusphere-2024-2515, https://doi.org/10.5194/egusphere-2024-2515, 2024
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The application of the distributed graph communication topology in earth models has been rarely studied. We tested and compared this topology with the traditional point-to-point communication method using a global wave model. We found that this topology is more efficient. Additionally, using this topology can greatly improve the performance of the wave model and could help improve the performance of other earth models.
Jan De Rydt, Nicolas C. Jourdain, Yoshihiro Nakayama, Mathias van Caspel, Ralph Timmermann, Pierre Mathiot, Xylar S. Asay-Davis, Hélène Seroussi, Pierre Dutrieux, Ben Galton-Fenzi, David Holland, and Ronja Reese
Geosci. Model Dev., 17, 7105–7139, https://doi.org/10.5194/gmd-17-7105-2024, https://doi.org/10.5194/gmd-17-7105-2024, 2024
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Global climate models do not reliably simulate sea-level change due to ice-sheet–ocean interactions. We propose a community modelling effort to conduct a series of well-defined experiments to compare models with observations and study how models respond to a range of perturbations in climate and ice-sheet geometry. The second Marine Ice Sheet–Ocean Model Intercomparison Project will continue to lay the groundwork for including ice-sheet–ocean interactions in global-scale IPCC-class models.
Qian Wang, Yang Zhang, Fei Chai, Y. Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev., 17, 7067–7081, https://doi.org/10.5194/gmd-17-7067-2024, https://doi.org/10.5194/gmd-17-7067-2024, 2024
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We coupled an unstructured hydro-model with an advanced column sea ice model to meet the growing demand for increased resolution and complexity in unstructured sea ice models. Additionally, we present a novel tracer transport scheme for the sea ice coupled model and demonstrate that this scheme fulfills the requirements for conservation, accuracy, efficiency, and monotonicity in an idealized test. Our new coupled model also has good performance in realistic tests.
Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud
Geosci. Model Dev., 17, 6967–6986, https://doi.org/10.5194/gmd-17-6967-2024, https://doi.org/10.5194/gmd-17-6967-2024, 2024
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Mixing is a crucial aspect of the ocean, but its accurate representation in computer simulations is made challenging by errors that result in unwanted mixing, compromising simulation realism. Here we illustrate the spurious effect that tides can have on simulations of south-east Asia. Although they play an important role in determining the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. We also provide insights into how to reduce these errors.
Mohamed Ayache, Jean-Claude Dutay, Anne Mouchet, Kazuyo Tachikawa, Camille Risi, and Gilles Ramstein
Geosci. Model Dev., 17, 6627–6655, https://doi.org/10.5194/gmd-17-6627-2024, https://doi.org/10.5194/gmd-17-6627-2024, 2024
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Water isotopes (δ18O, δD) are one of the most widely used proxies in ocean climate research. Previous studies using water isotope observations and modelling have highlighted the importance of understanding spatial and temporal isotopic variability for a quantitative interpretation of these tracers. Here we present the first results of a high-resolution regional dynamical model (at 1/12° horizontal resolution) developed for the Mediterranean Sea, one of the hotspots of ongoing climate change.
Cara Nissen, Nicole S. Lovenduski, Mathew Maltrud, Alison R. Gray, Yohei Takano, Kristen Falcinelli, Jade Sauvé, and Katherine Smith
Geosci. Model Dev., 17, 6415–6435, https://doi.org/10.5194/gmd-17-6415-2024, https://doi.org/10.5194/gmd-17-6415-2024, 2024
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Autonomous profiling floats have provided unprecedented observational coverage of the global ocean, but uncertainties remain about whether their sampling frequency and density capture the true spatiotemporal variability of physical, biogeochemical, and biological properties. Here, we present the novel synthetic biogeochemical float capabilities of the Energy Exascale Earth System Model version 2 and demonstrate their utility as a test bed to address these uncertainties.
Usama Kadri, Ali Abdolali, and Maxim Filimonov
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-139, https://doi.org/10.5194/gmd-2024-139, 2024
Revised manuscript accepted for GMD
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The GREAT v1.0 software introduces a novel tsunami warning technology for global real-time analysis. It leverages acoustic signals generated by tsunamis, which propagate faster than the tsunami itself, enabling real-time detection and assessment. Integrating various models, the software provides reliable and rapid assessment, mapping risk areas, and estimating tsunami amplitude. This advancement reduces false alarms and enhances global tsunami warning systems' accuracy and efficiency.
Iria Sala and Bingzhang Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-130, https://doi.org/10.5194/gmd-2024-130, 2024
Preprint under review for GMD
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Phytoplankton, tiny photosynthetic organisms, produce nearly half of Earth's oxygen. To analyze their physiology, diversity, and evolution in the ocean, we developed a model that treats phytoplankton as individual particles. Moreover, our model considers phytoplankton size, temperature, and light traits, and allows for mutations in phytoplankton cells. Thus, our model provides a valuable tool for advancing the study of phytoplankton physiology, diversity, and evolution.
Ye Yuan, Fujiang Yu, Zhi Chen, Xueding Li, Fang Hou, Yuanyong Gao, Zhiyi Gao, and Renbo Pang
Geosci. Model Dev., 17, 6123–6136, https://doi.org/10.5194/gmd-17-6123-2024, https://doi.org/10.5194/gmd-17-6123-2024, 2024
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Accurate and timely forecasting of ocean waves is of great importance to the safety of marine transportation and offshore engineering. In this study, GPU-accelerated computing is introduced in WAve Modeling Cycle 6 (WAM6). With this effort, global high-resolution wave simulations can now run on GPUs up to tens of times faster than the currently available models can on a CPU node with results that are just as accurate.
Krysten Rutherford, Laura Bianucci, and William Floyd
Geosci. Model Dev., 17, 6083–6104, https://doi.org/10.5194/gmd-17-6083-2024, https://doi.org/10.5194/gmd-17-6083-2024, 2024
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Nearshore ocean models often lack complete information about freshwater fluxes due to numerous ungauged rivers and streams. We tested a simple rain-based hydrological model as inputs into an ocean model of Quatsino Sound, Canada, with the aim of improving the representation of the land–ocean connection in the nearshore model. Through multiple tests, we found that the performance of the ocean model improved when providing 60 % or more of the freshwater inputs from the simple runoff model.
Neill Mackay, Taimoor Sohail, Jan David Zika, Richard G. Williams, Oliver Andrews, and Andrew James Watson
Geosci. Model Dev., 17, 5987–6005, https://doi.org/10.5194/gmd-17-5987-2024, https://doi.org/10.5194/gmd-17-5987-2024, 2024
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The ocean absorbs carbon dioxide from the atmosphere, mitigating climate change, but estimates of the uptake do not always agree. There is a need to reconcile these differing estimates and to improve our understanding of ocean carbon uptake. We present a new method for estimating ocean carbon uptake and test it with model data. The method effectively diagnoses the ocean carbon uptake from limited data and therefore shows promise for reconciling different observational estimates.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 17, 5851–5882, https://doi.org/10.5194/gmd-17-5851-2024, https://doi.org/10.5194/gmd-17-5851-2024, 2024
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The carbonate system is typically studied using measurements, but modeling can contribute valuable insights. Using a biogeochemical model, we propose a new representation of total alkalinity, dissolved inorganic carbon, pCO2, and pH in a highly dynamic Mediterranean coastal area, the Bay of Marseille, a useful addition to measurements. Through a detailed analysis of pCO2 and air–sea CO2 fluxes, we show that variations are strongly impacted by the hydrodynamic processes that affect the bay.
Xuanxuan Gao, Shuiqing Li, Dongxue Mo, Yahao Liu, and Po Hu
Geosci. Model Dev., 17, 5497–5509, https://doi.org/10.5194/gmd-17-5497-2024, https://doi.org/10.5194/gmd-17-5497-2024, 2024
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Storm surges generate coastal inundation and expose populations and properties to danger. We developed a novel storm surge inundation model for efficient prediction. Estimates compare well with in situ measurements and results from a numerical model. The new model is a significant improvement on existing numerical models, with much higher computational efficiency and stability, which allows timely disaster prevention and mitigation.
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024, https://doi.org/10.5194/gmd-17-5145-2024, 2024
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This study explores methods to reconstruct diurnal variations in skin sea surface temperature in a model of the Mediterranean Sea. Our new approach, considering chlorophyll concentration, enhances spatial and temporal variations in the warm layer. Comparative analysis shows context-dependent improvements. The proposed "chlorophyll-interactive" method brings the surface net total heat flux closer to zero annually, despite a net heat loss from the ocean to the atmosphere.
David Storkey, Pierre Mathiot, Michael J. Bell, Dan Copsey, Catherine Guiavarc'h, Helene T. Hewitt, Jeff Ridley, and Malcolm J. Roberts
EGUsphere, https://doi.org/10.5194/egusphere-2024-1414, https://doi.org/10.5194/egusphere-2024-1414, 2024
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The Southern Ocean is a key region of the world ocean in the context of climate change studies. We show that the HadGEM3 coupled model with intermediate ocean resolution struggles to accurately simulate the Southern Ocean. Increasing the frictional drag that the sea floor exerts on ocean currents, and introducing a representation of unresolved ocean eddies both appear to reduce the large-scale biases in this model.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
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We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024, https://doi.org/10.5194/gmd-17-4603-2024, 2024
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Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data are complicated by the distortion of the used modelling grids and the large number of different grid types. We present two new methods that allow the calculation of oceanic fluxes of volume, heat, salinity, and ice through almost arbitrary sections for various models and reanalyses that are independent of the used modelling grids.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024, https://doi.org/10.5194/gmd-17-4095-2024, 2024
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Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356, https://doi.org/10.5194/gmd-17-3341-2024, https://doi.org/10.5194/gmd-17-3341-2024, 2024
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The new offline particle tracking package, Tracker v1.1, is introduced to the Regional Ocean Modeling System, featuring an efficient nearest-neighbor algorithm to enhance particle-tracking speed. Its performance was evaluated against four other tracking packages and passive dye. Despite unique features, all packages yield comparable results. Running multiple packages within the same circulation model allows comparison of their performance and ease of use.
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173, https://doi.org/10.5194/gmd-17-3157-2024, https://doi.org/10.5194/gmd-17-3157-2024, 2024
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In order to improve Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher-resolution ocean currents. To this goal a 3 km resolution regional ocean model has been developed. Its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation was found to be quite realistic.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
Geosci. Model Dev., 17, 2829–2853, https://doi.org/10.5194/gmd-17-2829-2024, https://doi.org/10.5194/gmd-17-2829-2024, 2024
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Here a new method of modelling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean currents and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave–current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
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Ocean forecasting relies on the combination of numerical models and ocean observations through data assimilation (DA). Here we assess the performance of two DA systems in a dynamic western boundary current, the East Australian Current, across a common modelling and observational framework. We show that the more advanced, time-dependent method outperforms the time-independent method for forecast horizons of 5 d. This advocates the use of advanced methods for highly variable oceanic regions.
Ivan Hernandez, Leidy M. Castro-Rosero, Manuel Espino, and Jose M. Alsina Torrent
Geosci. Model Dev., 17, 2221–2245, https://doi.org/10.5194/gmd-17-2221-2024, https://doi.org/10.5194/gmd-17-2221-2024, 2024
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The LOCATE numerical model was developed to conduct Lagrangian simulations of the transport and dispersion of marine debris at coastal scales. High-resolution hydrodynamic data and a beaching module that used particle distance to the shore for land–water boundary detection were used on a realistic debris discharge scenario comparing hydrodynamic data at various resolutions. Coastal processes and complex geometric structures were resolved when using nested grids and distance-to-shore beaching.
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
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A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
Geosci. Model Dev., 17, 1749–1764, https://doi.org/10.5194/gmd-17-1749-2024, https://doi.org/10.5194/gmd-17-1749-2024, 2024
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We present a new way of solving the quasi-geostrophic (QG) equations, a simple set of equations describing ocean dynamics. Our method is solely based on the numerical methods used to solve the equations and requires no parameter tuning. Moreover, it can handle non-rectangular geometries, opening the way to study QG equations on realistic domains. We release a PyTorch implementation to ease future machine-learning developments on top of the presented method.
Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song
Geosci. Model Dev., 17, 1651–1665, https://doi.org/10.5194/gmd-17-1651-2024, https://doi.org/10.5194/gmd-17-1651-2024, 2024
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Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.
Ali Abdolali, Saeideh Banihashemi, Jose Henrique Alves, Aron Roland, Tyler J. Hesser, Mary Anderson Bryant, and Jane McKee Smith
Geosci. Model Dev., 17, 1023–1039, https://doi.org/10.5194/gmd-17-1023-2024, https://doi.org/10.5194/gmd-17-1023-2024, 2024
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This article presents an overview of the development and implementation of Great Lake Wave Unstructured (GLWUv2.0), including the core model and workflow design and development. The validation was conducted against in situ data for the re-forecasted duration for summer and wintertime (ice season). The article describes the limitations and challenges encountered in the operational environment and the path forward for the next generation of wave forecast systems in enclosed basins like the GL.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
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Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Andrew C. Ross, Charles A. Stock, Alistair Adcroft, Enrique Curchitser, Robert Hallberg, Matthew J. Harrison, Katherine Hedstrom, Niki Zadeh, Michael Alexander, Wenhao Chen, Elizabeth J. Drenkard, Hubert du Pontavice, Raphael Dussin, Fabian Gomez, Jasmin G. John, Dujuan Kang, Diane Lavoie, Laure Resplandy, Alizée Roobaert, Vincent Saba, Sang-Ik Shin, Samantha Siedlecki, and James Simkins
Geosci. Model Dev., 16, 6943–6985, https://doi.org/10.5194/gmd-16-6943-2023, https://doi.org/10.5194/gmd-16-6943-2023, 2023
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We evaluate a model for northwest Atlantic Ocean dynamics and biogeochemistry that balances high resolution with computational economy by building on the new regional features in the MOM6 ocean model and COBALT biogeochemical model. We test the model's ability to simulate impactful historical variability and find that the model simulates the mean state and variability of most features well, which suggests the model can provide information to inform living-marine-resource applications.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
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We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, France Van Wambeke, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 16, 6701–6739, https://doi.org/10.5194/gmd-16-6701-2023, https://doi.org/10.5194/gmd-16-6701-2023, 2023
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While several studies have shown that mixotrophs play a crucial role in the carbon cycle, the impact of environmental forcings on their dynamics remains poorly investigated. Using a biogeochemical model that considers mixotrophs, we study the impact of light and nutrient concentration on the ecosystem composition in a highly dynamic Mediterranean coastal area: the Bay of Marseille. We show that mixotrophs cope better with oligotrophic conditions compared to strict auto- and heterotrophs.
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, and Øyvind Breivik
Geosci. Model Dev., 16, 6515–6530, https://doi.org/10.5194/gmd-16-6515-2023, https://doi.org/10.5194/gmd-16-6515-2023, 2023
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Surface waves that propagate in oceanic or coastal environments get influenced by their surroundings. Changes in the ambient current or the depth profile affect the wave propagation path, and the change in wave direction is called refraction. Some analytical solutions to the governing equations exist under ideal conditions, but for realistic situations, the equations must be solved numerically. Here we present such a numerical solver under an open-source license.
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev., 16, 6393–6412, https://doi.org/10.5194/gmd-16-6393-2023, https://doi.org/10.5194/gmd-16-6393-2023, 2023
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Ocean surface waves play an important role in the air–sea interface but are rarely activated in high-resolution Earth system simulations due to their expensive computational costs. To alleviate this situation, this paper designs a new wave modeling framework with a multiscale grid system. Evaluations of a series of numerical experiments show that it has good feasibility and applicability in the WAVEWATCH III model, WW3, and can achieve the goals of efficient and high-precision wave simulation.
Doroteaciro Iovino, Pier Giuseppe Fogli, and Simona Masina
Geosci. Model Dev., 16, 6127–6159, https://doi.org/10.5194/gmd-16-6127-2023, https://doi.org/10.5194/gmd-16-6127-2023, 2023
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This paper describes the model performance of three global ocean–sea ice configurations, from non-eddying (1°) to eddy-rich (1/16°) resolutions. Model simulations are obtained following the Ocean Model Intercomparison Project phase 2 (OMIP2) protocol. We compare key global climate variables across the three models and against observations, emphasizing the relative advantages and disadvantages of running forced ocean–sea ice models at higher resolution.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
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A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, and Vikram Singh
Geosci. Model Dev., 16, 5179–5196, https://doi.org/10.5194/gmd-16-5179-2023, https://doi.org/10.5194/gmd-16-5179-2023, 2023
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The new ocean general circulation model ICON-O is developed for running experiments at kilometer scales and beyond. One targeted application is to simulate internal tides crucial for ocean mixing. To ensure their realism, which is difficult to assess, we evaluate the barotropic tides that generate internal tides. We show that ICON-O is able to realistically simulate the major aspects of the observed barotropic tides and discuss the aspects that impact the quality of the simulated tides.
Cited articles
Adcroft, A. and Campin, J.-M.: Rescaled height coordinates for accurate
representation of free-surface flows in ocean circulation models, Ocean
Model., 7, 269–284, https://doi.org/10.1016/j.ocemod.2003.09.003, 2004.
Adcroft, A., Campin, J.-M. Hill, C., and Marshall, J.: Implementation of an
Atmosphere–Ocean General Circulation Model on the Expanded Spherical Cube,
Mon. Weather Rev., 132, 2845–2863, https://doi.org/10.1175/MWR2823.1, 2004.
Banas, N. S., MacCready, P., and Hickey, B. M.: The Columbia River plume as
cross-shelf exporter and along-coast barrier, Cont. Shelf Res.,
2, 292–301, https://doi.org/10.1016/j.csr.2008.03.011, 2009.
Barichivich, J., Gloor, E., Peylin, P., Brienen, R. J. W., Schöngart,
J., Espinoza, J. C., and Pattnayak, K. C.: Recent intensification of Amazon
flooding extremes driven by strengthened Walker circulation, Sci.
Adv., 4, eaat8785, https://doi.org/10.1126/sciadv.aat8785, 2018.
Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., Drange, H., Roelandt, C., Seierstad, I. A., Hoose, C., and Kristjánsson, J. E.: The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev., 6, 687–720, https://doi.org/10.5194/gmd-6-687-2013, 2013.
Bourgeois, T., Orr, J. C., Resplandy, L., Terhaar, J., Ethé, C., Gehlen, M., and Bopp, L.: Coastal-ocean uptake of anthropogenic carbon, Biogeosciences, 13, 4167–4185, https://doi.org/10.5194/bg-13-4167-2016, 2016.
Campin, J.-M., Marshall, J., and Ferreira, D.: Sea ice–ocean coupling using
a rescaled vertical coordinate z∗, Ocean Model., 24, 1–14,
https://doi.org/10.1016/j.ocemod.2008.05.005, 2008.
Carroll, D., Menemenlis, Adkins, J. F., Bowman, K. W., Brix, H., Dutkiewicz, S., Gierach, M. M., Hill, C., Jahn, O., Landschützer, P., Lauderdale, J. Liu, J. M., Naviaux, J. D., Manizza, M., Rödenbeck, C., Schimel, D. S., Van der Stocken, T., and Zhang, H.: The ECCO‐Darwin data‐assimilative global ocean biogeochemistry model: Estimates of seasonal to multidecadal surface ocean pCO2 and air‐sea CO2 flux, J. Adv. Model. Earth Sy., 12, e2019MS001888, https://doi.org/10.1029/2019MS001888, 2020.
Chao, S.-Y.: River-forced estuarine plumes, J. Phys.
Oceanogr., 18, 72–88, https://doi.org/10.1175/1520-0485(1988)018<0072:RFEP>2.0.CO;2,
1988a.
Chao, S.-Y.: Wind-driven motion of estuarine plumes, J. Phys.
Oceanogr., 18, 1144–1166, https://doi.org/10.1175/1520-0485(1988)018<1144:WDMOEP>2.0.CO;2; 1988b.
Cione, J. J. and Uhlhorn, E. W.: Sea surface temperature variability in
hurricanes: Implications with respect to intensity change, Mon. Weather
Rev., 131, 1783–1796, https://doi.org/10.1175//2562.1, 2003.
de Boyer Montégut, C., Madec, G., Fischer, A. S., Lazar, A., and
Ludicone, D.: Mixed layer depth over the global ocean: An examination of
profile data and a profile-based climatology, J. Geophys. Res.-Oceans, 109, C12003,
https://doi.org/10.1029/2004jc002378, 2004.
Denamiel, C., Budgell, W. P., and Toumi, R.: The Congo River plume: Impact of
the forcing on the far-field and near-field dynamics, J. Geophys.
Res.-Oceans, 118, 964–989, https://doi.org/10.1002/jgrc.20062, 2013.
Du, Y. and Zhang, Y.: Satellite and Argo Observed Surface Salinity
Variations in the Tropical Indian Ocean and Their Association with the
Indian Ocean Dipole Mode, J. Climate, 28, 695–713,
https://doi.org/10.1175/JCLI-D-14-00435.1, 2015.
Fekete, B. M., Vörösmarty, C. J., and Grabs, W.: High-resolution
fields of global runoff combining observed river discharge and simulated
water balances, Global Biogeochem. Cy., 16, 15-11–15-10, https://doi.org/10.1029/1999gb001254, 2002.
Feng, Y.: Improved representation of river runoff in ECCOv4 simulations: implementation, evaluation and impacts to coastal plume regions, Zenodo, https://doi.org/10.5281/zenodo.4106405, 2020.
Feng, Y., DiMarco, S. F., Balaguru, K., and Xue, H.: Seasonal and interannual
variability of areal extent of the Gulf of Mexico hypoxia from a coupled
physical-biogeochemical model: A new implication for management practice,
J. Geophys. Res.-Biogeo., 124, 1939–1960,
https://doi.org/10.1029/2018JG004745, 2019.
Fennel, K., Hu, J., Laurent, A., Marta-Almeida, M., and Hetland, R.:
Sensitivity of hypoxia predictions for the northern Gulf of Mexico to
sediment oxygen consumption and model nesting, J. Geophys.
Res.-Oceans, 118, 990–1002, https://doi.org/10.1002/jgrc.20077, 2013.
Fennel, K., Alin, S., Barbero, L., Evans, W., Bourgeois, T., Cooley, S., Dunne, J., Feely, R. A., Hernandez-Ayon, J. M., Hu, X., Lohrenz, S., Muller-Karger, F., Najjar, R., Robbins, L., Shadwick, E., Siedlecki, S., Steiner, N., Sutton, A., Turk, D., Vlahos, P., and Wang, Z. A.: Carbon cycling in the North American coastal ocean: a synthesis, Biogeosciences, 16, 1281–1304, https://doi.org/10.5194/bg-16-1281-2019, 2019.
Fong, D. A. and Geyer, W. R.: Response of a river plume during an upwelling
favorable wind event, J. Geophys. Res.-Oceans, 106,
1067–1084, https://doi.org/10.1029/2000jc900134, 2001.
Fong, D. A. and Geyer, W. R.: The Alongshore Transport of Freshwater in a
Surface-Trapped River Plume, J. Phys. Oceanogr., 32,
957–972, https://doi.org/10.1175/1520-0485(2002)032<0957:TATOFI>2.0.CO;2, 2002.
Forget, G., Campin, J.-M., Heimbach, P., Hill, C. N., Ponte, R. M., and Wunsch, C.: ECCO version 4: an integrated framework for non-linear inverse modeling and global ocean state estimation, Geosci. Model Dev., 8, 3071–3104, https://doi.org/10.5194/gmd-8-3071-2015, 2015.
Fournier, S., Reager, J. T., Lee, T., Vazquez-Cuervo, J., David, C. H., and
Gierach, M. M.: SMAP observes flooding from land to sea: The Texas event of
2015, Geophys. Res. Lett. 43, L070821, https://doi.org/10.1002/2016GL070821,
2016a.
Fournier, S., Vialard, J., Lengaigne, M., Lee, T., Gierach, M. M., and
Chaitanya, A. V. S.: Modulation of the Ganges-Brahmaputra river plume by the
Indian Ocean dipole and eddies inferred from satellite observations, J.
Geophys. Res.-Oceans, 122, 9591–9604, https://doi.org/10.1002/2017JC013333,
2017a.
Fournier, S., Vandemark, D., Gaultier, L., Lee, T., Jonsson, B., and
Gierach, M. M.: Interannual variation in offshore advection of Amazon-Orinoco
plume waters: Observations, forcing mechanisms, and impacts, J.
Geophys. Res.-Oceans, 122, 8966–8982, https://doi.org/10.1002/2017JC013103,
2017b.
Fournier, S., Reager, J. T., Dzwonkowski, B., and Vazquez-Cuervo, J.:
Statistical mapping of freshwater origin and fate signatures as land/ocean
“regions of influence” in the Gulf of Mexico, J. Geophys.
Res.-Oceans, 124, 4954–4973, https://doi.org/10.1029/2018JC014784, 2019.
García Berdeal, I., Hickey, B. M., and Kawase, M.: Influence of wind
stress and ambient flow on a high discharge river plume, J. Geophys. Res.-Oceans, 107,
13-11–13-24, https://doi.org/10.1029/2001jc000932, 2002.
Garvine, R. W.: Penetration of buoyant coastal discharge onto the continental
shelf: a numerical model experiment, J. Phys. Oceanogr., 29,
1892–1909, https://doi.org/10.1175/1520-0485(1999)029<1892:POBCDO>2.0.CO;2, 1999.
Garvine, R. W.: The impact of model configuration in studies of buoyant
coastal discharge, J. Marine Resh., 59, 193–225,
https://doi.org/10.1357/002224001762882637, 2001.
Gaspar, P., Grégoris, Y., and Lefevre, J.-M.: A simple eddy kinetic
energy model for simulations of the oceanic vertical mixing: Tests at
station Papa and long-term upper ocean study site, J. Geophys. Res.-Oceans, 95, 16179–16193,
https://doi.org/10.1029/JC095iC09p16179, 1990.
Gierach, M. M., Vazquez-Cuervo, J., Lee, T., and Tsontos, V. M.: Aquarius
and SMOS detect effects of an extreme Mississippi River flooding event in
the Gulf of Mexico, Geophys. Res. Lett., 40, L50995,
https://doi.org/10.1002/grl.50995, 2013.
Griffies, S. M., Gnanadesikan, A., Dixon, K. W., Dunne, J. P., Gerdes, R., Harrison, M. J., Rosati, A., Russell, J. L., Samuels, B. L., Spelman, M. J., Winton, M., and Zhang, R.: Formulation of an ocean model for global climate simulations, Ocean Sci., 1, 45–79, https://doi.org/10.5194/os-1-45-2005, 2005.
Halliwell, G. R.: Evaluation of vertical coordinate and vertical mixing
algorithms in the HYbrid-Coordinate Ocean Model (HYCOM), Ocean Model.,
7, 285–322, https://doi.org/10.1016/j.ocemod.2003.10.002, 2004.
Herzfeld, M.: Methods for freshwater riverine input into regional ocean
models, Ocean Model., 90, 1–15, https://doi.org/10.1016/j.ocemod.2015.04.001, 2015.
Huang, R. X.: Real Freshwater Flux as a Natural Boundary Condition for the
Salinity Balance and Thermohaline Circulation Forced by Evaporation and
Precipitation, J. Phys. Oceanogr., 23, 2428–2446,
https://doi.org/10.1175/1520-0485(1993)023<2428:RFFAAN>2.0.CO;2,
1993.
IPCC: Summary for Policymakers, in: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems, edited by: Shukla, P. R., Skea, J., Calvo Buendia, E., Masson-Delmotte, V., Pörtner, H.-O., Roberts, D. C., Zhai, P., Slade, R., Connors, S., van Diemen, R., Ferrat, M., Haughey, E., Luz, S., Neogi, S., Pathak, M., Petzold, J., Portugal Pereira, J., Vyas, P., Huntley, E., Kissick, K., Belkacemi, M., and Malley, J., in press,
2021.
Jolliff, J. K., Kindle, J. C., Shulman, I., Penta, B., Friedrichs, M. A. M.,
Helber, R., and Arnone, R. A.: Summary diagrams for coupled
hydrodynamic-ecosystem model skill assessment, J. Marine Syst.,
76, 64–82, https://doi.org/10.1016/j.jmarsys.2008.05.014, 2009.
Kourafalou, V. H., Oey, L.-Y., Wang, J. D., and Lee, T. N.: The fate of
river discharge on the continental shelf: 1. Modeling the river plume and
the inner shelf coastal current, J. Geophys. Res., 101, 3415–3434,
https://doi.org/10.1029/95JC03024, 1996.
Lacroix, F., Ilyina, T., and Hartmann, J.: Oceanic CO2 outgassing and biological production hotspots induced by pre-industrial river loads of nutrients and carbon in a global modeling approach, Biogeosciences, 17, 55–88, https://doi.org/10.5194/bg-17-55-2020, 2020.
Landschützer, P., Laruelle, G. G., Roobaert, A., and Regnier, P.: A uniform pCO2 climatology combining open and coastal oceans, Earth Syst. Sci. Data, 12, 2537–2553, https://doi.org/10.5194/essd-12-2537-2020, 2020.
Lentz, S. J.: The Amazon River plume during AMASSEDS: subtidal current
variability and the importance of wind forcing, J. Geophys.
Res.-Oceans, 100, 2377–2390, https://doi.org/10.1029/94JC00343, 1995a.
Lentz, S. J.: Seasonal variations in the horizontal structure of the Amazon
plume inferred from historical hydrographic data, J. Geophys.
Res.-Oceans, 100, 2391–2400, https://doi.org/10.1029/94JC01847, 1995b.
Liang, L., Xue, H., and Shu, Y.: The Indonesian throughflow and the
circulation in the Banda Sea: A modeling study, J. Geophys.
Res.-Oceans, 124, 3089–3106, https://doi.org/10.1029/2018JC014926, 2019.
Marshall, J., Adcroft, A., Hill, C., Perelman, L., and Heisey, C.: A
finite-volume, incompressible Navier Stokes model for studies of the ocean
on parallel computers, J. Geophys. Res.-Oceans, 102, 5753–5766, https://doi.org/10.1029/96jc02775, 1997.
Mecklenburg, S., Drusch, M., Kerr, Y. H., Font, J., Martin-Neira, M.,
Delwart, S., and Crapolicchio, R.: ESA's soil moisture and ocean salinity
mission: Mission performance and operations, IEEE T. Geosci.
Remote, 50, 1354–1366, https://doi.org/10.1109/TGRS.2012.2187666, 2012.
Menemenlis, D.: ECCOv4 setup, available at: http://wwwcvs.mitgcm.org/viewvc/MITgcm/MITgcm_contrib/llc_hires/ (last access: 29 March 2021), 2020a.
Menemenlis, D.: SMAP observations, available at: http://apdrc.soest.hawaii.edu/las/v6/dataset?catitem=2928 (last access: 29 March 2021), 2020b.
Menemenlis, D., Hill, C. N., Adcroft, A. J., Campin, J.-M., Cheng, B.,
Ciotti, R. B., and Zhang, J.: NASA Supercomputer Improves Prospects for
Ocean Climate Research, EOS Transactions AGU, 86, 89–96,
https://doi.org/10.1029/2005EO090002, 2005.
Menemenlis, D., Campin, J.-M., Heimbach, P., Hill, C. N., Lee, T., Nguyen,
A. T., and Zhang, H.: ECCO2: High Resolution Global Ocean and Sea Ice Data
Synthesis, Mercator Ocean Quarterly Newsletter, 31, 13–21, 2008.
Meng, Z., Ning, L. Yuping G., and Yang, F.: Exchanges of surface plastic
particles in the South China Sea through straits using Lagrangian method,
J. Tropical Oceanogr., 39, 109–116, available at: http://journal15.magtechjournal.com/Jwk3_rdhyxb/article/2020/1009-5470/1009-5470-39-5-109.shtml (last access: 29 March 2021), 2020 (in
Chinese with English abstract).
Molleri, G. S. F., Novo, E. M. L. M., and Kampel, M.: Space-time variability of
the Amazon River plume based on satellite ocean color, Cont. Shelf
Res., 30, 342–352, https://doi.org/10.1016/j.csr.2009.11.015, 2010.
Neetu, S., Lengaigne, M., Vincent, E. M., Vialard, J., Madec, G., Samson,
G., and Durand, F.: Influence of upper-ocean stratification on tropical
cyclones-induced surface cooling in the Bay of Bengal, J.
Geophys. Res.-Oceans, 117, C12020, https://doi.org/10.1029/2012JC008433, 2012.
Palma, E. D. and Matano, R. P.: An idealized study of near equatorial
river plumes, J. Geophys. Res.-Oceans, 122, 3599–3620,
https://doi.org/10.1002/2016JC012554, 2017.
Piecuch, C. G. and Wadehra, R.: Dynamic sea level variability due to
seasonal river discharge: A preliminary global ocean model study.
Geophys. Res. Lett., 47, e2020GL086984,
https://doi.org/10.1029/2020GL086984, 2020.
Rao, R. R. and Sivakumar, R.: Seasonal variability of the salt budget of the
mixed layer and near-surface layer salinity structure of the tropical Indian
Ocean from a new global ocean salinity climatology, J. Geophys.
Res.-Oceans, 108, 3009, https://doi.org/10.1029/2001JC000907, 2003.
Resplandy, L., Keeling, R. F., Rödenbeck, C., Stephens, B. B., Khatiwala,
S., Rodgers, K. B., Long, M. C., Bopp, L., and Tans, P. P.: Revision of global
carbon fluxes based on a reassessment of oceanic and riverine carbon
transport, Nat. Geosci., 11, 504–509, https://doi.org/10.1038/s41561-018-0151-3, 2018.
Roobaert, A., Laruelle, G. G. Landschützer, P., Gruber, N., Chou, L., and
Regnier, P.: The Spatiotemporal Dynamics of the Sources and Sinks of CO2 in
the Global Coastal Ocean, Global Biogeochem. Cy., 33, 1693–1714,
https://doi.org/10.1029/2019GB006239, 2019.
Roullet, G. and Madec, G.: Salt conservation, free surface, and varying
levels: A new formulation for ocean general circulation models, J. Geophys. Res.-Oceans, 105,
23927–23942, https://doi.org/10.1029/2000jc900089, 2000.
Santini, M. and Caporaso, L.: Evaluation of freshwater flow from rivers to
the sea in CMIP5 simulations: Insights from the Congo River basin, J.
Geophys. Res.-Atmos., 123, 10278–10300,
https://doi.org/10.1029/2017JD027422, 2018.
Schiller, R. V. and Kourafalou, V. H.: Modeling river plume dynamics with
the HYbrid Coordinate Ocean Model, Ocean Model., 33, 101–117,
https://doi.org/10.1016/j.ocemod.2009.12.005, 2011.
Seitzinger, S. P., Harrison, J. A., Dumont, E., Beusen, A. H. W., and
Bouwman, A. F.: Sources and delivery of carbon, nitrogen, and phosphorus to
the coastal zone: An overview of Global Nutrient Export from Watersheds
(NEWS) models and their application, Global Biogeochem. Cy., 19,
GB4S01, https://doi.org/10.1029/2005GB002606, 2005.
Seitzinger, S. P., Mayorga, E., Bouwman, A. F., Kroeze, C., Beusen, A. H.
W., Billen, G., Drecht, G. V., Dumont, E., Fekete, B. M., Garnier, J., and
Harrison, J. A.: Global river nutrient export: A scenario analysis of past
and future trends, Global Biogeochem. Cy., 24, GB0A08,
https://doi.org/10.1029/2009GB003587, 2010.
Sengupta, D., Goddalehundi, B. R., and Anitha, D. S.: Cyclone-induced mixing
does not cool SST in the post-monsoon North Bay of Bengal, Atmos.
Sci. Lett., 9, 1–6, https://doi.org/10.1002/asl.162, 2008.
Stammer, D., Ueyoshi, K., Köhl, A., Large, W. G., Josey, S. A., and
Wunsch, C.: Estimating air-sea fluxes of heat, freshwater, and momentum
through global ocean data assimilation, J. Geophys. Res.-Oceans,
109, C05023, https://doi.org/10.1029/2003jc002082, 2004.
Su, Z., Wang, J., Klein, P., Thompson, A. F., and Menemenlis, D.: Ocean sub
mesoscales as a key component of the global heat budget, Nat.
Commun., 9, 775, https://doi.org/10.1038/s41467-018-02983-w, 2018.
Suzuki, T., Yamazaki, D., Tsujino, H., Komuro, Y., Nakano, H., and Urakawa,
S.: A dataset of continental river discharge based on JRA-55 for use in a
global ocean circulation model, J. Oceanogr., 74, 421–429,
https://doi.org/10.1007/s10872-017-0458-5, 2018.
Timmermann, R., Danilov, S., Schröter, J., Böning, C., Sidorenko,
D., and Rollenhagen, K.: Ocean circulation and sea ice distribution in a
finite element global sea ice–ocean model, Ocean Model., 27, 114–129,
https://doi.org/10.1016/j.ocemod.2008.10.009, 2009.
Tseng, Y.-H., Bryan, F. O., and Whitney, M. M.: Impacts of the representation
of riverine freshwater input in the community earth system model, Ocean
Model., 105, 71–86, https://doi.org/10.1016/j.ocemod.2016.08.002, 2016.
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., Sommer, J. L., 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.
Vialard, J. and Delecluse, P.: An OGCM study for the TOGA decade. Part I:
Role of salinity in the physics of the western Pacific fresh pool, J.
Phys. Oceanogr., 28, 1071–1088, https://doi.org/10.1175/1520-0485(1998)028<1071:AOSFTT>2.0.CO;2,
1998.
Vinaychandran, P., Murty, V. S. N., and Ramesh Babu, V.: Observations of
barrier layer formation in the Bay of Bengal during summer monsoon, J.
Geophys. Res.-Oceans, 107, 8018, https://doi.org/10.1029/2001JC000831, 2002.
Volodin, E. M., Dianskii, N. A., and Gusev, A. V.: Simulating present-day
climate with the INMCM4.0 coupled model of the atmospheric and oceanic
general circulations, Izvestiya, Atmos. Ocean. Phys., 46,
414–431, https://doi.org/10.1134/S000143381004002X, 2010.
Walker, N. D.: Satellite assessment of Mississippi River plume variability:
causes and predictability, Remote Sens. Environ., 58, 21–35,
https://doi.org/10.1016/0034-4257(95)00259-6, 1996.
Ward, N. D., Megonigal, J. P., Bond-Lamberty, B., Bailey, V. L., Butman, D., Canuel, E. A., Diefenderfer, H., Ganju, N. K., Goñi, M. A., Graham, E. B., Hopkinson, C. S., Khangaonkar, T., Langley, J. A., McDowell, N. G., Myers-Pigg, A. N., Neumann, R. B., Osburn, C. L., Price, R. M., Rowland, J., Sengupta, A., Simard, M., Thornton, P. E., Tzortziou, M., Vargas, R., Weisenhorn, P. B., and Windham-Myers, L.: Representing the function
and sensitivity of coastal interfaces in Earth system models, Nat. Commun., 11, 2458, https://doi.org/10.1038/s41467-020-16236-2, 2020.
Willmott, C. J.: On the validation of models, Phys. Geogr., 2, 184–194,
https://doi.org/10.1080/02723646.1981.10642213, 1981.
Yankovsky, A. E. and Chapman D. C.: A Simple Theory for the Fate of Buoyant Coastal Discharges, J. Phys. Oceanogr., 27, 1386–1401, https://doi.org/10.1175/1520-0485(1997)027<1386:ASTFTF>2.0.CO;2, 1997.
Yueh, S. H., Tang, W., Fore, A. G., Neumann, G., Hayashi, A., Freedman, A.,
and Lagerloef, G. S. L-band passive and active microwave geophysical model
functions of ocean surface winds and applications to Aquarius retrieval,
IEEE T. Geosci. Remote, 51, 4619–4632,
https://doi.org/10.1109/TGRS.2013.2266915, 2013.
Yueh, S. H., Tang, W., Fore, A., Hayashi, A., Song, Y. T., and Lagerloef, G.:
Aquarius geophysical model function and combined active passive algorithm
for ocean surface salinity and wind retrieval, J. Geophys.
Res.-Oceans, 119, 5360–5379, https://doi.org/10.1002/2014JC009939, 2014.
Zhang, H.: MITgcm model setup and output for “Improved representation of river runoff in ECCO simulations: implementation, evaluation, and impacts to coastal plume regions” [Data set], Zenodo, https://doi.org/10.5281/zenodo.4095613, 2020.
Zhang, H., Menemenlis, D., and Fenty, G.: ECCO LLC270 ocean‐ice state estimate, available at: http://hdl.handle.net/1721.1/119821 (last access: 29 March 2021), 2018.
Short summary
Simulation of coastal plume regions was improved in global ECCOv4 with a series of sensitivity tests. We find modeled SSS is closer to SMAP when using daily point-source runoff as well as increasing the resolution from coarse to intermediate. The plume characteristics, freshwater transport, and critical water properties are modified greatly. But this may not happen with a further increase to high resolution. The study will advance the seamless modeling of land–ocean–atmosphere feedback in ESMs.
Simulation of coastal plume regions was improved in global ECCOv4 with a series of sensitivity...
