Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-2811-2023
© 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-16-2811-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Enhanced ocean wave modeling by including effect of breaking under both deep- and shallow-water conditions
Yue Xu
Department of Hydraulic Engineering, Tsinghua University, Beijing,
China
Department of Ocean Science and Engineering, Southern University of
Science and Technology, Shenzhen, China
Related authors
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Peida Han and Xiping Yu
Ocean Sci., 18, 1573–1590, https://doi.org/10.5194/os-18-1573-2022, https://doi.org/10.5194/os-18-1573-2022, 2022
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Hurricane Irene generated strong near-inertial currents in ocean waters when passing over the Mid-Atlantic Bight of the US East Coast in late August 2011. It is demonstrated that a combination of valuable field data and detailed model results can be exploited to study the development and decay mechanism of this event. The near-inertial kinetic energy is shown to mainly have been gained from wind power during the hurricane event. Its decay, however, depends on several factors.
Related subject area
Oceanography
The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methylmercury in fish
Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0)
Arctic Ocean simulations in the CMIP6 Ocean Model Intercomparison Project (OMIP)
ChemicalDrift 1.0: an open-source Lagrangian chemical-fate and transport model for organic aquatic pollutants
The Met Office operational wave forecasting system: the evolution of the regional and global models
4DVarNet-SSH: end-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry
Development and validation of a global 1∕32° surface-wave–tide–circulation coupled ocean model: FIO-COM32
Reproducible and relocatable regional ocean modelling: fundamentals and practices
Adding Sea Ice Effects to A Global Operational Model (NEMO v3.6) for Forecasting Total Water Level: Approach and Impact
Barotropic tides in MPAS-Ocean (E3SM V2): impact of ice shelf cavities
Using the two-way nesting technique AGRIF with MARS3D V11.2 to improve hydrodynamics and estimate environmental indicators
Multidecadal and climatological surface current simulations for the southwestern Indian Ocean at 1∕50° resolution
Improving Antarctic Bottom Water precursors in NEMO for climate applications
The tidal effects in the Finite-volumE Sea ice–Ocean Model (FESOM2.1): a comparison between parameterised tidal mixing and explicit tidal forcing
HIDRA2: deep-learning ensemble sea level and storm tide forecasting in the presence of seiches – the case of the northern Adriatic
Moana Ocean Hindcast – a > 25-year simulation for New Zealand waters using the Regional Ocean Modeling System (ROMS) v3.9 model
An internal solitary wave forecasting model in the northern South China Sea (ISWFM-NSCS)
A nonhydrostatic oceanic regional model, ORCTM v1, for internal solitary wave simulation
How does 4DVar data assimilation affect the vertical representation of mesoscale eddies? A case study with observing system simulation experiments (OSSEs) using ROMS v3.9
An ensemble Kalman filter-based ocean data assimilation system improved by adaptive observation error inflation (AOEI)
GULF18, a high-resolution NEMO-based tidal ocean model of the Arabian/Persian Gulf
The Baltic Sea Model Intercomparison Project (BMIP) – a platform for model development, evaluation, and uncertainty assessment
Waves in SKRIPS: WaveWatch III coupling implementation and a case study of cyclone Mekunu
An ensemble Kalman filter system with the Stony Brook Parallel Ocean Model v1.0
Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite derived chlorophyll
Wind work at the air-sea interface: a modeling study in anticipation of future space missions
Improved upper-ocean thermodynamical structure modeling with combined effects of surface waves and M2 internal tides on vertical mixing: a case study for the Indian Ocean
The bulk parameterizations of turbulent air–sea fluxes in NEMO4: the origin of sea surface temperature differences in a global model study
NeverWorld2: an idealized model hierarchy to investigate ocean mesoscale eddies across resolutions
Observing system simulation experiments reveal that subsurface temperature observations improve estimates of circulation and heat content in a dynamic western boundary current
Parallel implementation of the SHYFEM (System of HydrodYnamic Finite Element Modules) model
Block-structured, equal-workload, multi-grid-nesting interface for the Boussinesq wave model FUNWAVE-TVD (Total Variation Diminishing)
Evaluation of an emergent feature of sub-shelf melt oscillations from an idealized coupled ice sheet–ocean model using FISOC (v1.1) – ROMSIceShelf (v1.0) – Elmer/Ice (v9.0)
GNOM v1.0: an optimized steady-state model of the modern marine neodymium cycle
Implementation and evaluation of open boundary conditions for sea ice in a regional coupled ocean (ROMS) and sea ice (CICE) modeling system
ROMSPath v1.0: offline particle tracking for the Regional Ocean Modeling System (ROMS)
DINCAE 2.0: multivariate convolutional neural network with error estimates to reconstruct sea surface temperature satellite and altimetry observations
RADIv1: a non-steady-state early diagenetic model for ocean sediments in Julia and MATLAB/GNU Octave
IBI-CCS: a regional high-resolution model to simulate sea level in western Europe
Empirical Lagrangian parametrization for wind-driven mixing of buoyant particles at the ocean surface
Improving ocean modeling software NEMO 4.0 benchmarking and communication efficiency
Improvements in the regional South China Sea Operational Oceanography Forecasting System (SCSOFSv2)
Reconsideration of wind stress, wind waves, and turbulence in simulating wind-driven currents of shallow lakes in the Wave and Current Coupled Model (WCCM) version 1.0
ISWFoam: a numerical model for internal solitary wave simulation in continuously stratified fluids
PyCO2SYS v1.8: marine carbonate system calculations in Python
Plume spreading test case for coastal ocean models
The interpretation of temperature and salinity variables in numerical ocean model output and the calculation of heat fluxes and heat content
S2P3-R v2.0: computationally efficient modelling of shelf seas on regional to global scales
The Lagrangian-based Floating Macroalgal Growth and Drift Model (FMGDM v1.0): application to the Yellow Sea green tide
Nemo-Nordic 2.0: operational marine forecast model for the Baltic Sea
Johannes Bieser, David J. Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Sørensen, and Corinna Schrum
Geosci. Model Dev., 16, 2649–2688, https://doi.org/10.5194/gmd-16-2649-2023, https://doi.org/10.5194/gmd-16-2649-2023, 2023
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MERCY is a 3D model to study mercury (Hg) cycling in the ocean. Hg is a highly harmful pollutant regulated by the UN Minamata Convention on Mercury due to widespread human emissions. These emissions eventually reach the oceans, where Hg transforms into the even more toxic and bioaccumulative pollutant methylmercury. MERCY predicts the fate of Hg in the ocean and its buildup in the food chain. It is the first model to consider Hg accumulation in fish, a major source of Hg exposure for humans.
Y. Joseph Zhang, Tomas Fernandez-Montblanc, William Pringle, Hao-Cheng Yu, Linlin Cui, and Saeed Moghimi
Geosci. Model Dev., 16, 2565–2581, https://doi.org/10.5194/gmd-16-2565-2023, https://doi.org/10.5194/gmd-16-2565-2023, 2023
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Simulating global ocean from deep basins to coastal areas is a daunting task but is important for disaster mitigation efforts. We present a new 3D global ocean model on flexible mesh to study both tidal and nontidal processes and total water prediction. We demonstrate the potential for
seamlesssimulation, on a single mesh, from the global ocean to a few estuaries along the US West Coast. The model can serve as the backbone of a global tide surge and compound flooding forecasting framework.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
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Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Manuel Aghito, Loris Calgaro, Knut-Frode Dagestad, Christian Ferrarin, Antonio Marcomini, Øyvind Breivik, and Lars Robert Hole
Geosci. Model Dev., 16, 2477–2494, https://doi.org/10.5194/gmd-16-2477-2023, https://doi.org/10.5194/gmd-16-2477-2023, 2023
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The newly developed ChemicalDrift model can simulate the transport and fate of chemicals in the ocean and in coastal regions. The model combines ocean physics, including transport due to currents, turbulence due to surface winds and the sinking of particles to the sea floor, with ocean chemistry, such as the partitioning, the degradation and the evaporation of chemicals. The model will be utilized for risk assessment of ocean and sea-floor contamination from pollutants emitted from shipping.
Nieves G. Valiente, Andrew Saulter, Breogan Gomez, Christopher Bunney, Jian-Guo Li, Tamzin Palmer, and Christine Pequignet
Geosci. Model Dev., 16, 2515–2538, https://doi.org/10.5194/gmd-16-2515-2023, https://doi.org/10.5194/gmd-16-2515-2023, 2023
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We document the Met Office operational global and regional wave models which provide wave forecasts up to 7 d ahead. Our models present coarser resolution offshore to higher resolution near the coastline. The increased resolution led to replication of the extremes but to some overestimation during modal conditions. If currents are included, wave directions and long period swells near the coast are significantly improved. New developments focus on the optimisation of the models with resolution.
Maxime Beauchamp, Quentin Febvre, Hugo Georgenthum, and Ronan Fablet
Geosci. Model Dev., 16, 2119–2147, https://doi.org/10.5194/gmd-16-2119-2023, https://doi.org/10.5194/gmd-16-2119-2023, 2023
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4DVarNet is a learning-based method based on traditional data assimilation (DA). This new class of algorithms can be used to provide efficient reconstructions of a dynamical system based on single observations. We provide a 4DVarNet application to sea surface height reconstructions based on nadir and future Surface Water and Ocean and Topography data. It outperforms other methods, from optimal interpolation to sophisticated DA algorithms. This work is part of on-going AI Chair Oceanix projects.
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev., 16, 1755–1777, https://doi.org/10.5194/gmd-16-1755-2023, https://doi.org/10.5194/gmd-16-1755-2023, 2023
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A new global surface-wave–tide–circulation coupled ocean model (FIO-COM32) with a resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are shown to be important contributors to the significant improvements in FIO-COM32 simulations. It is time to merge these separated model components (surface waves, tidal currents and ocean circulation) and start a new generation of ocean model development.
Jeff Polton, James Harle, Jason Holt, Anna Katavouta, Dale Partridge, Jenny Jardine, Sarah Wakelin, Julia Rulent, Anthony Wise, Katherine Hutchinson, David Byrne, Diego Bruciaferri, Enda O'Dea, Michela De Dominicis, Pierre Mathiot, Andrew Coward, Andrew Yool, Julien Palmiéri, Gennadi Lessin, Claudia Gabriela Mayorga-Adame, Valérie Le Guennec, Alex Arnold, and Clément Rousset
Geosci. Model Dev., 16, 1481–1510, https://doi.org/10.5194/gmd-16-1481-2023, https://doi.org/10.5194/gmd-16-1481-2023, 2023
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The aim is to increase the capacity of the modelling community to respond to societally important questions that require ocean modelling. The concept of reproducibility for regional ocean modelling is developed: advocating methods for reproducible workflows and standardised methods of assessment. Then, targeting the NEMO framework, we give practical advice and worked examples, highlighting key considerations that will the expedite development cycle and upskill the user community.
Pengcheng Wang and Natacha B. Bernier
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-18, https://doi.org/10.5194/gmd-2023-18, 2023
Revised manuscript accepted for GMD
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In operational flood forecast systems, the effect of sea ice is typically neglected. To address this limitation, we developed an effective and efficient way of adding ice effects to total water level forecast systems. The method takes advantage of forecast fields from external ice-ocean models and features a novel, consistent representation of the tidal relative ice-ocean velocity. Its impact is demonstrated via improved seasonality of tides and corrected overestimations of storm surges.
Nairita Pal, Kristin N. Barton, Mark R. Petersen, Steven R. Brus, Darren Engwirda, Brian K. Arbic, Andrew F. Roberts, Joannes J. Westerink, and Damrongsak Wirasaet
Geosci. Model Dev., 16, 1297–1314, https://doi.org/10.5194/gmd-16-1297-2023, https://doi.org/10.5194/gmd-16-1297-2023, 2023
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Understanding tides is essential to accurately predict ocean currents. Over the next several decades coastal processes such as flooding and erosion will be severely impacted due to climate change. Tides affect currents along the coastal regions the most. In this paper we show the results of implementing tides in a global ocean model known as MPAS–Ocean. We also show how Antarctic ice shelf cavities affect global tides. Our work points towards future research with tide–ice interactions.
Sébastien Petton, Valérie Garnier, Matthieu Caillaud, Laurent Debreu, and Franck Dumas
Geosci. Model Dev., 16, 1191–1211, https://doi.org/10.5194/gmd-16-1191-2023, https://doi.org/10.5194/gmd-16-1191-2023, 2023
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The nesting AGRIF library is implemented in the MARS3D hydrodynamic model, a semi-implicit, free-surface numerical model which uses a time scheme as an alternating-direction implicit (ADI) algorithm. Two applications at the regional and coastal scale are introduced. We compare the two-nesting approach to the classic offline one-way approach, based on an in situ dataset. This method is an efficient means to significantly improve the physical hydrodynamics and unravel ecological challenges.
Noam S. Vogt-Vincent and Helen L. Johnson
Geosci. Model Dev., 16, 1163–1178, https://doi.org/10.5194/gmd-16-1163-2023, https://doi.org/10.5194/gmd-16-1163-2023, 2023
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Ocean currents transport things over large distances across the ocean surface. Predicting this transport is key for tackling many environmental problems, such as marine plastic pollution and coral reef resilience. However, doing this requires a good understanding ocean currents, which is currently lacking. Here, we present and validate state-of-the-art simulations for surface currents in the southwestern Indian Ocean, which will support future marine dispersal studies across this region.
Katherine Hutchinson, Julie Deshayes, Christian Éthé, Clément Rousset, Casimir de Lavergne, Martin Vancoppenolle, Nicolas C. Jourdain, and Pierre Mathiot
EGUsphere, https://doi.org/10.5194/egusphere-2023-99, https://doi.org/10.5194/egusphere-2023-99, 2023
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Bottom Water constitutes the lower limb of the ocean’s overturning system and is primarily formed in the Antarctic Weddell and Ross Seas due to interactions between the atmosphere, ocean, sea ice and ice shelves. Here we use a global ocean 1° resolution model with the three large ice shelves important for the formation of the parent waters of Bottom Water explicitly represented and find doing so reduces salinity biases, improves water mass realism, and gives realistic ice shelf melt rates.
Pengyang Song, Dmitry Sidorenko, Patrick Scholz, Maik Thomas, and Gerrit Lohmann
Geosci. Model Dev., 16, 383–405, https://doi.org/10.5194/gmd-16-383-2023, https://doi.org/10.5194/gmd-16-383-2023, 2023
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Tides have essential effects on the ocean and climate. Most previous research applies parameterised tidal mixing to discuss their effects in models. By comparing the effect of a tidal mixing parameterisation and tidal forcing on the ocean state, we assess the advantages and disadvantages of the two methods. Our results show that tidal mixing in the North Pacific Ocean strongly affects the global thermohaline circulation. We also list some effects that are not considered in the parameterisation.
Marko Rus, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev., 16, 271–288, https://doi.org/10.5194/gmd-16-271-2023, https://doi.org/10.5194/gmd-16-271-2023, 2023
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We propose a new fast and reliable deep-learning architecture HIDRA2 for sea level and storm surge modeling. HIDRA2 features new feature encoders and a fusion-regression block. We test HIDRA2 on Adriatic storm surges, which depend on an interaction between tides and seiches. We demonstrate that HIDRA2 learns to effectively mimic the timing and amplitude of Adriatic seiches. This is essential for reliable HIDRA2 predictions of total storm surge sea levels.
Joao Marcos Azevedo Correia de Souza, Sutara H. Suanda, Phellipe P. Couto, Robert O. Smith, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 211–231, https://doi.org/10.5194/gmd-16-211-2023, https://doi.org/10.5194/gmd-16-211-2023, 2023
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The current paper describes the configuration and evaluation of the Moana Ocean Hindcast, a > 25-year simulation of the ocean state around New Zealand using the Regional Ocean Modeling System v3.9. This is the first open-access, long-term, continuous, realistic ocean simulation for this region and provides information for improving the understanding of the ocean processes that affect the New Zealand exclusive economic zone.
Yankun Gong, Xueen Chen, Jiexin Xu, Jieshuo Xie, Zhiwu Chen, Yinghui He, and Shuqun Cai
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-287, https://doi.org/10.5194/gmd-2022-287, 2023
Revised manuscript accepted for GMD
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Internal solitary waves (ISWs) play a crucial role in mass transport and ocean mixing in the northern South China Sea. Massive numerical investigations have been conducted in this region, but there was no systematic evaluation of a three-dimensional model about precisely simulating ISWs. Here, an ISW forecasting model is employed to evaluate the roles of resolution, tidal forcing and stratification in accurately reproducing wave properties via comparing to field and remote-sensing observations.
Hao Huang, Pengyang Song, Shi Qiu, Jiaqi Guo, and Xueen Chen
Geosci. Model Dev., 16, 109–133, https://doi.org/10.5194/gmd-16-109-2023, https://doi.org/10.5194/gmd-16-109-2023, 2023
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The Oceanic Regional Circulation and Tide Model (ORCTM) is developed to reproduce internal solitary wave dynamics. The three-dimensional nonlinear momentum equations are involved with the nonhydrostatic pressure obtained via solving the Poisson equation. The validation experimental results agree with the internal wave theories and observations, demonstrating that the ORCTM can successfully describe the life cycle of nonlinear internal solitary waves under different oceanic environments.
David E. Gwyther, Shane R. Keating, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 157–178, https://doi.org/10.5194/gmd-16-157-2023, https://doi.org/10.5194/gmd-16-157-2023, 2023
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Ocean eddies are important for weather, climate, biology, navigation, and search and rescue. Since eddies change rapidly, models that incorporate or assimilate observations are required to produce accurate eddy timings and locations, yet the model accuracy is rarely assessed below the surface. We use a unique type of ocean model experiment to assess three-dimensional eddy structure in the East Australian Current and explore two pathways in which this subsurface structure is being degraded.
Shun Ohishi, Takemasa Miyoshi, and Misako Kachi
Geosci. Model Dev., 15, 9057–9073, https://doi.org/10.5194/gmd-15-9057-2022, https://doi.org/10.5194/gmd-15-9057-2022, 2022
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An adaptive observation error inflation (AOEI) method was proposed for atmospheric data assimilation to mitigate erroneous analysis updates caused by large observation-minus-forecast differences for satellite brightness temperature around clear- and cloudy-sky boundaries. This study implemented the AOEI with an ocean data assimilation system, leading to an improvement of analysis accuracy and dynamical balance around the frontal regions with large meridional temperature differences.
Diego Bruciaferri, Marina Tonani, Isabella Ascione, Fahad Al Senafi, Enda O'Dea, Helene T. Hewitt, and Andrew Saulter
Geosci. Model Dev., 15, 8705–8730, https://doi.org/10.5194/gmd-15-8705-2022, https://doi.org/10.5194/gmd-15-8705-2022, 2022
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More accurate predictions of the Gulf's ocean dynamics are needed. We investigate the impact on the predictive skills of a numerical shelf sea model of the Gulf after changing a few key aspects. Increasing the lateral and vertical resolution and optimising the vertical coordinate system to best represent the leading physical processes at stake significantly improve the accuracy of the simulated dynamics. Additional work may be needed to get real benefit from using a more realistic bathymetry.
Matthias Gröger, Manja Placke, H. E. Markus Meier, Florian Börgel, Sandra-Esther Brunnabend, Cyril Dutheil, Ulf Gräwe, Magnus Hieronymus, Thomas Neumann, Hagen Radtke, Semjon Schimanke, Jian Su, and Germo Väli
Geosci. Model Dev., 15, 8613–8638, https://doi.org/10.5194/gmd-15-8613-2022, https://doi.org/10.5194/gmd-15-8613-2022, 2022
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Comparisons of oceanographic climate data from different models often suffer from different model setups, forcing fields, and output of variables. This paper provides a protocol to harmonize these elements to set up multidecadal simulations for the Baltic Sea, a marginal sea in Europe. First results are shown from six different model simulations from four different model platforms. Topical studies for upwelling, marine heat waves, and stratification are also assessed.
Rui Sun, Alison Cobb, Ana B. Villas Bôas, Sabique Langodan, Aneesh C. Subramanian, Matthew R. Mazloff, Bruce D. Cornuelle, Arthur J. Miller, Raju Pathak, and Ibrahim Hoteit
EGUsphere, https://doi.org/10.5194/egusphere-2022-1298, https://doi.org/10.5194/egusphere-2022-1298, 2022
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In this work, we integrated the WaveWatch III model into the regional coupled model SKRIPS. We then performed a case study using the newly implemented model to study the tropical cyclone Mekunu, which occurred in the Arabian Sea. We found that the coupled model better simulates the cyclone than the uncoupled model, but the impact of waves on the cyclone is not significant. However, the waves change the sea surface temperature and mixed layer, especially in the cold wave due to the cyclone.
Shun Ohishi, Tsutomu Hihara, Hidenori Aiki, Joji Ishizaka, Yasumasa Miyazawa, Misako Kachi, and Takemasa Miyoshi
Geosci. Model Dev., 15, 8395–8410, https://doi.org/10.5194/gmd-15-8395-2022, https://doi.org/10.5194/gmd-15-8395-2022, 2022
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We develop an ensemble-Kalman-filter-based regional ocean data assimilation system in which satellite and in situ observations are assimilated at a daily frequency. We find the best setting for dynamical balance and accuracy based on sensitivity experiments focused on how to inflate the ensemble spread and how to apply the analysis update to the model evolution. This study has a broader impact on more general data assimilation systems in which the initial shocks are a significant issue.
Bror Fredrik Jönsson, Christopher Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael Forget, Christian Müller, Marie-Fanny Racault, Christopher Nigel Hill, Thomas Jackson, and Shubha Sathyendranath
EGUsphere, https://doi.org/10.5194/egusphere-2022-849, https://doi.org/10.5194/egusphere-2022-849, 2022
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While biogeochemical models and satellite-derived ocean-color data provide unprecedented information it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth Mover Distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.
Hector S. Torres, Patrice Klein, Jinbo Wang, Alexander Wineteer, Bo Qiu, Andrew F. Thompson, Lionel Renault, Ernesto Rodriguez, Dimitris Menemenlis, Andrea Molod, Christopher N. Hill, Ehud Strobach, Hong Zhang, Mar Flexas, and Dragana Perkovic-Martin
Geosci. Model Dev., 15, 8041–8058, https://doi.org/10.5194/gmd-15-8041-2022, https://doi.org/10.5194/gmd-15-8041-2022, 2022
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Wind work at the air-sea interface is the scalar product of winds and currents and is the transfer of kinetic energy between the ocean and the atmosphere. Using a new global coupled ocean-atmosphere simulation performed at kilometer resolution, we show that all scales of winds and currents impact the ocean dynamics at spatial and temporal scales. The consequential interplay of surface winds and currents in the numerical simulation motivates the need for a winds and currents satellite mission.
Zhanpeng Zhuang, Quanan Zheng, Yongzeng Yang, Zhenya Song, Yeli Yuan, Chaojie Zhou, Xinhua Zhao, Ting Zhang, and Jing Xie
Geosci. Model Dev., 15, 7221–7241, https://doi.org/10.5194/gmd-15-7221-2022, https://doi.org/10.5194/gmd-15-7221-2022, 2022
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We evaluate the impacts of surface waves and internal tides on the upper-ocean mixing in the Indian Ocean. The surface-wave-generated turbulent mixing is dominant if depth is < 30 m, while the internal-tide-induced mixing is larger than surface waves in the ocean interior from 40
to 130 m. The simulated thermal structure, mixed layer depth and surface current are all improved when the mixing schemes are jointly incorporated into the ocean model because of the strengthened vertical mixing.
Giulia Bonino, Doroteaciro Iovino, Laurent Brodeau, and Simona Masina
Geosci. Model Dev., 15, 6873–6889, https://doi.org/10.5194/gmd-15-6873-2022, https://doi.org/10.5194/gmd-15-6873-2022, 2022
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The sea surface temperature (SST) is highly influenced by the transfer of energy driven by turbulent air–sea fluxes (TASFs). In the NEMO ocean general circulation model, TASFs are computed by means of bulk formulas. Bulk formulas require the choice of a given bulk parameterization, which influences the magnitudes of the TASFs. Our results show that parameterization-related SST differences are primarily sensitive to the wind stress differences across parameterizations.
Gustavo M. Marques, Nora Loose, Elizabeth Yankovsky, Jacob M. Steinberg, Chiung-Yin Chang, Neeraja Bhamidipati, Alistair Adcroft, Baylor Fox-Kemper, Stephen M. Griffies, Robert W. Hallberg, Malte F. Jansen, Hemant Khatri, and Laure Zanna
Geosci. Model Dev., 15, 6567–6579, https://doi.org/10.5194/gmd-15-6567-2022, https://doi.org/10.5194/gmd-15-6567-2022, 2022
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We present an idealized ocean model configuration and a set of simulations performed using varying horizontal grid spacing. While the model domain is idealized, it resembles important geometric features of the Atlantic and Southern oceans. The simulations described here serve as a framework to effectively study mesoscale eddy dynamics, to investigate the effect of mesoscale eddies on the large-scale dynamics, and to test and evaluate eddy parameterizations.
David E. Gwyther, Colette Kerry, Moninya Roughan, and Shane R. Keating
Geosci. Model Dev., 15, 6541–6565, https://doi.org/10.5194/gmd-15-6541-2022, https://doi.org/10.5194/gmd-15-6541-2022, 2022
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The ocean current flowing along the southeastern coast of Australia is called the East Australian Current (EAC). Using computer simulations, we tested how surface and subsurface observations might improve models of the EAC. Subsurface observations are particularly important for improving simulations, and if made in the correct location and time, can have impact 600 km upstream. The stability of the current affects model estimates could be capitalized upon in future observing strategies.
Giorgio Micaletto, Ivano Barletta, Silvia Mocavero, Ivan Federico, Italo Epicoco, Giorgia Verri, Giovanni Coppini, Pasquale Schiano, Giovanni Aloisio, and Nadia Pinardi
Geosci. Model Dev., 15, 6025–6046, https://doi.org/10.5194/gmd-15-6025-2022, https://doi.org/10.5194/gmd-15-6025-2022, 2022
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The full exploitation of supercomputing architectures requires a deep revision of the current climate models. This paper presents the parallelization of the three-dimensional hydrodynamic model SHYFEM (System of HydrodYnamic Finite Element Modules). Optimized numerical libraries were used to partition the model domain and solve the sparse linear system of equations in parallel. The performance assessment demonstrates a good level of scalability with a realistic configuration used as a benchmark.
Young-Kwang Choi, Fengyan Shi, Matt Malej, Jane M. Smith, James T. Kirby, and Stephan T. Grilli
Geosci. Model Dev., 15, 5441–5459, https://doi.org/10.5194/gmd-15-5441-2022, https://doi.org/10.5194/gmd-15-5441-2022, 2022
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The multi-grid-nesting technique is an important methodology used for modeling transoceanic tsunamis and coastal effects. In this study, we developed a two-way nesting interface in a multi-grid-nesting system for the Boussinesq wave model FUNWAVE-TVD. The interface acts as a
backboneof the nesting framework, handling data input, output, time sequencing, and internal interactions between grids at different scales.
Chen Zhao, Rupert Gladstone, Benjamin Keith Galton-Fenzi, David Gwyther, and Tore Hattermann
Geosci. Model Dev., 15, 5421–5439, https://doi.org/10.5194/gmd-15-5421-2022, https://doi.org/10.5194/gmd-15-5421-2022, 2022
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We use a coupled ice–ocean model to explore an oscillation feature found in several contributing models to MISOMIP1. The oscillation is closely related to the discretized grounding line retreat and likely strengthened by the buoyancy–melt feedback and/or melt–geometry feedback near the grounding line, and frequent ice–ocean coupling. Our model choices have a non-trivial impact on mean melt and ocean circulation strength, which might be interesting for the coupled ice–ocean community.
Benoît Pasquier, Sophia K. V. Hines, Hengdi Liang, Yingzhe Wu, Steven L. Goldstein, and Seth G. John
Geosci. Model Dev., 15, 4625–4656, https://doi.org/10.5194/gmd-15-4625-2022, https://doi.org/10.5194/gmd-15-4625-2022, 2022
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Neodymium isotopes in seawater have the potential to provide key information about ocean circulation, both today and in the past. This can shed light on the underlying drivers of global climate, which will improve our ability to predict future climate change, but uncertainties in our understanding of neodymium cycling have limited use of this tracer. We present a new model of neodymium in the modern ocean that runs extremely fast, matches observations, and is freely available for development.
Pedro Duarte, Jostein Brændshøi, Dmitry Shcherbin, Pauline Barras, Jon Albretsen, Yvonne Gusdal, Nicholas Szapiro, Andreas Martinsen, Annette Samuelsen, Keguang Wang, and Jens Boldingh Debernard
Geosci. Model Dev., 15, 4373–4392, https://doi.org/10.5194/gmd-15-4373-2022, https://doi.org/10.5194/gmd-15-4373-2022, 2022
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Sea ice models are often implemented for very large domains beyond the regions of sea ice formation, such as the whole Arctic or all of Antarctica. In this study, we implement changes in the Los Alamos Sea Ice Model, allowing it to be implemented for relatively small regions within the Arctic or Antarctica and yet considering the presence and influence of sea ice outside the represented areas. Such regional implementations are important when spatially detailed results are required.
Elias J. Hunter, Heidi L. Fuchs, John L. Wilkin, Gregory P. Gerbi, Robert J. Chant, and Jessica C. Garwood
Geosci. Model Dev., 15, 4297–4311, https://doi.org/10.5194/gmd-15-4297-2022, https://doi.org/10.5194/gmd-15-4297-2022, 2022
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ROMSPath is an offline particle tracking model tailored for use with output from Regional Ocean Modeling System (ROMS) simulations. It is an update to an established system, the Lagrangian TRANSport (LTRANS) model, including a number of improvements. These include a modification of the model coordinate system which improved accuracy and numerical efficiency, and added functionality for nested grids and Stokes drift.
Alexander Barth, Aida Alvera-Azcárate, Charles Troupin, and Jean-Marie Beckers
Geosci. Model Dev., 15, 2183–2196, https://doi.org/10.5194/gmd-15-2183-2022, https://doi.org/10.5194/gmd-15-2183-2022, 2022
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Earth-observing satellites provide routine measurement of several ocean parameters. However, these datasets have a significant amount of missing data due to the presence of clouds or other limitations of the employed sensors. This paper describes a method to infer the value of the missing satellite data based on a convolutional autoencoder (a specific type of neural network architecture). The technique also provides a reliable error estimate of the interpolated value.
Olivier Sulpis, Matthew P. Humphreys, Monica M. Wilhelmus, Dustin Carroll, William M. Berelson, Dimitris Menemenlis, Jack J. Middelburg, and Jess F. Adkins
Geosci. Model Dev., 15, 2105–2131, https://doi.org/10.5194/gmd-15-2105-2022, https://doi.org/10.5194/gmd-15-2105-2022, 2022
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A quarter of the surface of the Earth is covered by marine sediments rich in calcium carbonates, and their dissolution acts as a giant antacid tablet protecting the ocean against human-made acidification caused by massive CO2 emissions. Here, we present a new model of sediment chemistry that incorporates the latest experimental findings on calcium carbonate dissolution kinetics. This model can be used to predict how marine sediments evolve through time in response to environmental perturbations.
Alisée A. Chaigneau, Guillaume Reffray, Aurore Voldoire, and Angélique Melet
Geosci. Model Dev., 15, 2035–2062, https://doi.org/10.5194/gmd-15-2035-2022, https://doi.org/10.5194/gmd-15-2035-2022, 2022
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Climate-change-induced sea level rise is a major threat for coastal and low-lying regions. Projections of coastal sea level changes are thus of great interest for coastal risk assessment and have significantly developed in recent years. In this paper, the objective is to provide high-resolution (6 km) projections of sea level changes in the northeastern Atlantic region bordering western Europe. For that purpose, a regional model is used to refine existing coarse global projections.
Victor Onink, Erik van Sebille, and Charlotte Laufkötter
Geosci. Model Dev., 15, 1995–2012, https://doi.org/10.5194/gmd-15-1995-2022, https://doi.org/10.5194/gmd-15-1995-2022, 2022
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Turbulent mixing is a vital process in 3D modeling of particle transport in the ocean. However, since turbulence occurs on very short spatial scales and timescales, large-scale ocean models generally have highly simplified turbulence representations. We have developed parametrizations for the vertical turbulent transport of buoyant particles that can be easily applied in a large-scale particle tracking model. The predicted vertical concentration profiles match microplastic observations well.
Gaston Irrmann, Sébastien Masson, Éric Maisonnave, David Guibert, and Erwan Raffin
Geosci. Model Dev., 15, 1567–1582, https://doi.org/10.5194/gmd-15-1567-2022, https://doi.org/10.5194/gmd-15-1567-2022, 2022
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To be efficient on supercomputers, software must be high-performance at computing many concurrent tasks. Communications between tasks is often necessary but time consuming, and ocean modelling software NEMO 4.0 is no exception.
In this work we describe approaches enabling fewer communications, an optimization to share the workload more equally between tasks and a new flexible configuration to assess NEMO's performance easily.
Xueming Zhu, Ziqing Zu, Shihe Ren, Miaoyin Zhang, Yunfei Zhang, Hui Wang, and Ang Li
Geosci. Model Dev., 15, 995–1015, https://doi.org/10.5194/gmd-15-995-2022, https://doi.org/10.5194/gmd-15-995-2022, 2022
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SCSOFS has provided daily updated marine forecasting in the South China Sea for the next 5 d since 2013. Comprehensive updates have been conducted to the configurations of SCSOFS's physical model and data assimilation scheme in order to improve its forecasting skill. The three most sensitive updates are highlighted. Scientific comparison and accuracy assessment results indicate that remarkable improvements have been achieved in SCSOFSv2 with respect to the original version SCSOFSv1.
Tingfeng Wu, Boqiang Qin, Anning Huang, Yongwei Sheng, Shunxin Feng, and Céline Casenave
Geosci. Model Dev., 15, 745–769, https://doi.org/10.5194/gmd-15-745-2022, https://doi.org/10.5194/gmd-15-745-2022, 2022
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Most hydrodynamic models were initially developed based in marine environments. They cannot be directly applied to large lakes. Based on field observations and numerical experiments of a large shallow lake, we developed a hydrodynamic model by adopting new schemes of wind stress, wind waves, and turbulence for large lakes. Our model can greatly improve the simulation of lake currents. This study will be a reminder to limnologists to prudently use ocean models to study lake hydrodynamics.
Jingyuan Li, Qinghe Zhang, and Tongqing Chen
Geosci. Model Dev., 15, 105–127, https://doi.org/10.5194/gmd-15-105-2022, https://doi.org/10.5194/gmd-15-105-2022, 2022
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A numerical model, ISWFoam with a modified k–ω SST model, is developed to simulate internal solitary waves (ISWs) in continuously stratified, incompressible, viscous fluids based on a fully three-dimensional (3D) Navier–Stokes equation with the finite-volume method. ISWFoam can accurately simulate the generation and evolution of ISWs, the ISW breaking phenomenon, waveform inversion of ISWs, and the interaction between ISWs and complex topography.
Matthew P. Humphreys, Ernie R. Lewis, Jonathan D. Sharp, and Denis Pierrot
Geosci. Model Dev., 15, 15–43, https://doi.org/10.5194/gmd-15-15-2022, https://doi.org/10.5194/gmd-15-15-2022, 2022
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The ocean helps to mitigate our impact on Earth's climate by absorbing about a quarter of the carbon dioxide (CO2) released by human activities each year. However, once absorbed, chemical reactions between CO2 and water reduce seawater pH (
ocean acidification), which may have adverse effects on marine ecosystems. Our Python package, PyCO2SYS, models the chemical reactions of CO2 in seawater, allowing us to quantify the corresponding changes in pH and related chemical properties.
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.
Trevor J. McDougall, Paul M. Barker, Ryan M. Holmes, Rich Pawlowicz, Stephen M. Griffies, and Paul J. Durack
Geosci. Model Dev., 14, 6445–6466, https://doi.org/10.5194/gmd-14-6445-2021, https://doi.org/10.5194/gmd-14-6445-2021, 2021
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We show that the way that the air–sea heat flux is treated in ocean models means that the model's temperature variable should be interpreted as being Conservative Temperature, irrespective of whether the equation of state used in an ocean model is EOS-80 or TEOS-10.
Paul R. Halloran, Jennifer K. McWhorter, Beatriz Arellano Nava, Robert Marsh, and William Skirving
Geosci. Model Dev., 14, 6177–6195, https://doi.org/10.5194/gmd-14-6177-2021, https://doi.org/10.5194/gmd-14-6177-2021, 2021
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This paper describes the latest version of a simple model for simulating coastal oceanography in response to changes in weather and climate. The latest revision of this model makes scientific improvements but focuses on improvements that allow the model to be run simply at large scales and for long periods of time to explore the implications of (for example) future climate change along large areas of coastline.
Fucang Zhou, Jianzhong Ge, Dongyan Liu, Pingxing Ding, Changsheng Chen, and Xiaodao Wei
Geosci. Model Dev., 14, 6049–6070, https://doi.org/10.5194/gmd-14-6049-2021, https://doi.org/10.5194/gmd-14-6049-2021, 2021
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In this study, a physical–ecological model, the Floating Macroalgal Growth and Drift Model (FMGDM), was developed to determine the dynamic growth and drifting pattern of floating macroalgae. Based on Lagrangian tracking, the macroalgae bloom is jointly controlled by ocean flows, sea surface wind, temperature, irradiation, and nutrients. The FMGDM was robust in successfully reproducing the spatial and temporal dynamics of the massive green tide around the Yellow Sea.
Tuomas Kärnä, Patrik Ljungemyr, Saeed Falahat, Ida Ringgaard, Lars Axell, Vasily Korabel, Jens Murawski, Ilja Maljutenko, Anja Lindenthal, Simon Jandt-Scheelke, Svetlana Verjovkina, Ina Lorkowski, Priidik Lagemaa, Jun She, Laura Tuomi, Adam Nord, and Vibeke Huess
Geosci. Model Dev., 14, 5731–5749, https://doi.org/10.5194/gmd-14-5731-2021, https://doi.org/10.5194/gmd-14-5731-2021, 2021
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We present Nemo-Nordic 2.0, a novel operational marine model for the Baltic Sea. The model covers the Baltic Sea and the North Sea with approximately 1 nmi resolution. We validate the model's performance against sea level, water temperature, and salinity observations, as well as sea ice charts. The skill analysis demonstrates that Nemo-Nordic 2.0 can reproduce the hydrographic features of the Baltic Sea.
Cited articles
Ardhuin, F., Rogers, E., Babanin, A. V., Filipot, J.-F., Magne, R., Roland,
A., van der Westhuysen, A., Queffeulou, P., Lefevre, J.-M., Aouf, L., and
Collard, F.: Semiempirical dissipation source functions for ocean waves.
Part I: Definition, calibration, and validation,
J. Phys. Oceanogr., 40, 1917–1941, https://doi.org/10.1175/2010JPO4324.1, 2010.
Babanin, A. and Young, I.: Two-phase behaviour of the spectral dissipation
of wind waves, Proceedings of the 5th International Symposium Ocean Wave
Measurement and Analysis, Madrid, June 2005, 51, 2005.
Babanin, A. V., Banner, M. L., Young, I. R., and Donelan, M. A.:
Wave-follower field measurements of the wind-input spectral function. Part
III: Parameterization of the wind-input enhancement due to wave breaking,
J. Phys. Oceanogr., 37, 2764–2775,
https://doi.org/10.1175/2007JPO3757.1, 2007.
Badulin, S. I., Babanin, A. V., Zakharov, V. E., and Resio, D.: Weakly
turbulent laws of wind-wave growth, J. Fluid Mech., 591,
339–378, https://doi.org/10.1017/S0022112007008282, 2007.
Banner, M. L. and Melville, W. K.: On the separation of air flow over water
waves, J. Fluid Mech., 77, 825–842,
https://doi.org/10.1017/S0022112076002905, 1976.
Battjes, J. A. and Janssen, J. P. F. M.: Energy Loss and Set-Up Due to
Breaking of Random Waves, Coast. Eng., 32, 569–587,
https://doi.org/10.1061/9780872621909.034, 1978.
Berrisford, P., Soci, C., Bell, B., Dahlgren, P., A Horányi, Nicolas, J., Radu R., Villaume S., Bidlot J., and Haimberger L.: The era5 global reanalysis: preliminary extension to 1950, Q. J. Roy. Meteor. Soc., 147, 4186–4227, https://doi.org/10.1002/qj.4174, 2021.
Beyá, J., Álvarez, M., Gallardo, A., Hidalgo, H., and Winckler, P.:
Generation and validation of the Chilean Wave Atlas database,
Ocean Model., 116, 16–32, https://doi.org/10.1016/j.ocemod.2017.06.004, 2017.
Campos, R. M., Alves, J. H. G. M., Guedes Soares, C., Guimaraes, L. G., and
Parente, C. E.: Extreme wind-wave modeling and analysis in the south
Atlantic ocean, Ocean Model., 124, 75–93,
https://doi.org/10.1016/j.ocemod.2018.02.002, 2018.
Cavaleri, L., Alves, J. H. G. M., Ardhuin, F., Babanin, A., Banner, M.,
Belibassakis, K., Benoit, M., Donelan, M., Groeneweg, J., Herbers, T. H. C.,
Hwang, P., Janssen, P. A. E. M., Janssen, T., Lavrenov, I. V., Magne, R.,
Monbaliu, J., Onorato, M., Polnikov, V., Resio, D., Rogers, W. E., Sheremet,
A., McKee Smith, J., Tolman, H. L., van Vledder, G., Wolf, J., and Young,
I.: Wave modelling – The state of the art, Prog. Oceanogr., 75,
603–674, https://doi.org/10.1016/j.pocean.2007.05.005, 2007.
Cavaleri, L., Barbariol, F., and Benetazzo, A.: Wind–wave modeling: Where
we are, where to go, Journal of Marine Science and Engineering, 8, 260,
https://doi.org/10.3390/jmse8040260, 2020.
CERC: Shore protection manual, US Army Coast. Eng. Research Center,
Vols. 1–3, 1977.
Chalikov, D.: The parameterization of the wave boundary layer, J. Phys. Oceanogr., 25, 1333–1349,
https://doi.org/10.1175/1520-0485(1995)025<1333:TPOTWB>2.0.CO;2, 1995.
Chalikov, D. V. and Belevich, M. Y.: One-dimensional theory of the wave
boundary layer, Bound.-Lay. Meteorol., 63, 65–96,
https://doi.org/10.1007/BF00705377, 1993.
Chen, Y. and Yu, X.: Sensitivity of storm wave modeling to wind stress
evaluation methods, J. Adv. Model. Earth Sy., 9,
893–907, https://doi.org/10.1002/2016MS000850, 2017.
Csanady, G. T.: Air-sea interaction: laws and mechanisms, Cambridge
University Press, https://doi.org/10.1017/CBO9781139164672, 2001.
Donelan, M. A.: A nonlinear dissipation function due to wave breaking,
Proceedings of ECMWF Workshop on Ocean Wave Forecasting, Reading, UK, 2–4 July, 2001, 87–94, 2001.
Donelan, M. A. and Pierson, W. J.: Radar scattering and equilibrium ranges
in wind-generated waves with application to scatterometry, J. Geophys. Res.-Oceans, 92, 4971–5029,
https://doi.org/10.1029/JC092iC05p04971, 1987.
Donelan, M. A., Babanin, A. V., Young, I. R., and Banner, M. L.:
Wave-follower field measurements of the wind-input spectral function. Part
II: Parameterization of the wind input, J. Phys. Oceanogr.,
36, 1672–1689, https://doi.org/10.1175/JPO2933.1, 2006.
Earle, M. D., Steele, K. E., and Wang, D. W. C.: Use of advanced directional
wave spectra analysis methods, Ocean Eng., 26, 1421–1434,
https://doi.org/10.1016/S0029-8018(99)00010-4, 1999.
Eldeberky, Y.: Nonlinear transformationations of wave spectra in the
nearshore zone, Unpublished doctoral dissertation, Delft University of
Technology, Delft, The Netherlands, 1996.
Fan, Y. and Rogers, W. E.: Drag coefficient comparisons between observed and
model simulated directional wave spectra under hurricane conditions, Ocean
Model., 102, 1–13, https://doi.org/10.1016/j.ocemod.2016.04.004, 2016.
Fan, Y., Ginis, I., Hara, T., Wright, C. W., and Walsh, E. J.: Numerical
simulations and observations of surface wave fields under an extreme
tropical cyclone, J. Phys. Oceanogr., 39, 2097–2116,
https://doi.org/10.1175/2009JPO4224.1, 2009.
Hasselmann, K.: On the spectral dissipation of ocean waves due to white
capping, Bound.-Lay. Meteorol., 6, 107–127,
https://doi.org/10.1007/BF00232479, 1974.
Hasselmann, K., Barnett, T. P., Bouws, E., Carlson, H., Cartwright, D. E.,
Enke, K., Ewing, J., Gienapp, A., Hasselmann, D., and Kruseman, P.:
Measurements of wind-wave growth and swell decay during the Joint North Sea
Wave Project (JONSWAP), Ergaenzungsheft zur Deutschen Hydrographischen
Zeitschrift, Reihe A, https://doi.org/10.1093/ije/27.2.335, 1973.
Hwang, P. A.: Temporal and spatial variation of the drag coefficient of a
developing sea under steady wind-forcing, J. Geophys. Res.-Oceans, 110, 1–6, https://doi.org/10.1029/2005JC002912, 2005.
Hwang, P. A. and Wang, D. W.: An empirical investigation of source term
balance of small scale surface waves, Geophys. Res. Lett., 31, 121–141,
https://doi.org/10.1029/2004GL020080, 2004.
Janssen, P. A. E. M.: Wave-induced stress and the drag of air flow over sea
waves, J. Phys. Oceanogr., 19, 745–754,
https://doi.org/10.1175/1520-0485(1989)019<0745:WISATD>2.0.CO;2, 1989.
Janssen, P. A. E. M.: Quasi-linear theory of wind-wave generation applied to
wave forecasting, J. Phys. Oceanogr., 21, 1631–1642,
https://doi.org/10.1175/1520-0485(1991)021<1631:QLTOWW>2.0.CO;2, 1991.
Janssen, P. A. E. M.: The interaction of ocean waves and wind, Cambridge
University Press, https://doi.org/10.1017/CBO9780511525018, 2004.
Jones, I. S. and Toba, Y.: Wind stress over the ocean, Cambridge University
Press, https://doi.org/10.1017/CBO9780511552076, 2001.
Kahma, K. K. and Calkoen, C. J.: Reconciling discrepancies in the observed
growth of wind-generated waves, J. Phys. Oceanogr., 22,
1389–1405, https://doi.org/10.1175/1520-0485(1992)022<1389:RDITOG>2.0.CO;2, 1992.
Kim, T., Lin, L.-H., and Wang, H.: Application of maximum entropy method to
the real sea data, Coast. Eng., 24, 340–355,
https://doi.org/10.1061/9780784400890.027, 1994.
Leckler, F., Ardhuin, F., Filipot, J.-F., and Mironov, A.: Dissipation
source terms and whitecap statistics, Ocean Model., 70, 62–74,
https://doi.org/10.1016/j.ocemod.2013.03.007, 2013.
Liu, Q., Babanin, A., Fan, Y., Zieger, S., Guan, C., and Moon, I.-J.:
Numerical simulations of ocean surface waves under hurricane conditions:
Assessment of existing model performance, Ocean Model., 118, 73–93,
https://doi.org/10.1016/j.ocemod.2017.08.005, 2017.
Longuet-Higgins, M. S.: On wave breaking and the equilibrium spectrum of
wind-generated waves, P. R. Soc. Lond. A, 310, 151–159,
https://doi.org/10.1098/rspa.1969.0069, 1969.
Longuet-Higgins, M. S., Cartwright, D. E., and Smith, N. D: Observations of
the Directional Spectrum of Sea Waves Using The Motion of a Floating Buoy,
Ocean Wave Spectra, Prentice Hall, Englewood Cliffs, N. J., 111–136,
https://doi.org/10.1016/0011-7471(65)91457-9, 1963.
Makin, V. K. and Kudryavtsev, V. N.: Coupled sea surface-atmosphere model:
1. Wind over waves coupling, J. Geophys. Res.-Oceans, 104,
7613–7623, https://doi.org/10.1029/1999JC900006, 1999.
Melville, W. K. and Matusov, P.: Distribution of breaking waves at the ocean
surface, Nature, 417, 58–63, https://doi.org/10.1038/417058a, 2002.
Mentaschi, L., Besio, G., Cassola, F., and Mazzino, A.: Performance
evaluation of Wavewatch III in the Mediterranean Sea, Ocean Model., 90,
82–94, https://doi.org/10.1016/j.ocemod.2015.04.003, 2015.
Miles, J. W.: On the generation of surface waves by shear flows, J. Fluid Mech., 3, 185–204, https://doi.org/10.1017/S0022112057000567,
1957.
Miles, J. W.: A note on the interaction between surface waves and wind profiles, J. Fluid Mech., 22, 823–827, https://doi.org/10.1017/S0022112065001167, 1965.
Moody's Risk Management Solutions: Wind dataset, https://www.rms.com/event-response/hwind (last access: 22 May 2023), 2022.
Moon, I.-J., Ginis, I., and Hara, T.: Impact of the reduced drag coefficient
on ocean wave modeling under hurricane conditions, Mon. Weather Rev.,
136, 1217–1223, https://doi.org/10.1175/2007MWR2131.1, 2008.
Moskowitz, L.: Estimates of the power spectrums for fully developed seas for
wind speeds of 20 to 40 knots, J. Geophys. Res.,
69, 5161–5179, https://doi.org/10.1029/JZ069i024p05161, 1964.
National Centers for Environmental Information (NOAA): ETOPO 2022 15 Arc-Second Global Relief Model, [data set], https://doi.org/10.25921/fd45-gt74, 2022.
National Data Buoy Center (NOAA): Buoy dataset, https://www.ndbc.noaa.gov (last access: 22 May 2023), 2022.
Phillips, O. M.: Spectral and statistical properties of the equilibrium
range in wind-generated gravity waves, J. Fluid Mech., 156,
505–531, https://doi.org/10.1017/S0022112085002221, 1985.
Phillips, O. M., Posner, F. L., and Hansen, J. P.: High range resolution
radar measurements of the speed distribution of breaking events in
wind-generated ocean waves: Surface impulse and wave energy dissipation
rates, J. Phys. Oceanogr., 31, 450–460,
https://doi.org/10.1175/1520-0485(2001)031<0450:HRRRMO>2.0.CO;2, 2001.
Pierson Jr., W. J. and Moskowitz, L.: A proposed spectral form for fully
developed wind seas based on the similarity theory of S. A. Kitaigorodskii,
J. Geophys. Res., 69, 5181–5190,
https://doi.org/10.1029/JZ069i024p05181, 1964.
Polnikov, V. G.: On a description of a wind–wave energy dissipation function, in: The Air–sea Interface. Radio and Acoustic Sensing, Turbulence and Wave Dynamics, edited by: Donelan, M. A., Hui, W. H., and Plant, W. J., Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL, 277–282, 1993.
Rogers, W. E., Babanin, A. V., and Wang, D. W.: Observation-consistent input
and whitecapping dissipation in a model for wind-generated surface waves:
Description and simple calculations, J. Atmos. Ocean.
Tech., 29, 1329–1346, https://doi.org/10.1175/JTECH-D-11-00092.1, 2012.
Sanders, J. W: A growth-stage scaling model for the wind-driven sea,
Deutsche Hydrografische Zeitschrift, 29, 136–161,
https://doi.org/10.1007/BF02227029, 1976.
Snyder, R. L., Dobson, F. W., Elliott, J. A., and Long, R. B.: Array
measurements of atmospheric pressure fluctuations above surface gravity
waves, J. Fluid Mech., 102, 1–59,
https://10.1017/S0022112081002528, 1981.
Stewart, R. W.: The wave drag of wind over water, J. Fluid Mech., 10, 189–194, https://10.1017/S0022112061000172, 1961.
Stopa, J. E., Ardhuin, F., Babanin, A., and Zieger, S.: Comparison and
validation of physical wave parameterizations in spectral wave models, Ocean
Model., 103, 2–17, https://doi.org/10.1016/j.ocemod.2015.09.003, 2016.
Tolman, H. L: Validation of WAVEWATCH-III version 1.15, NOAA/NWS/NCEP/MMAB Tech. Rep., 213, 33 pp., 2002.
Tolman, H. L. and Chalikov, D.: Source terms in a third-generation wind wave
model, J. Phys. Oceanogr., 26, 2497–2518,
https://doi.org/10.1175/1520-0485(1996)026<2497:STIATG>2.0.CO;2, 1996.
Wang, D. W., Mitchell, D. A., Teague, W. J., Jarosz, E., and Hulbert, M. S.:
Extreme waves under Hurricane Ivan, Science, 309, 896–896,
https://10.1126/science.1112509, 2005.
WAVEWATCH III R Development Group (WW3DG): User manual and system
documentation of WAVEWATCH III R version 5.16, Technical Note 329,
NOAA/NWS/NCEP/MMAB, College Park, MD, USA, 326 pp. + Appendices, 2016.
Xu, Y. and Yu, X.: Enhanced formulation of wind energy input into waves in
developing sea, Prog. Oceanogr., 186, 102376,
https://doi.org/10.1016/j.pocean.2020.102376, 2020.
Xu, Y. and Yu, X.: Enhanced atmospheric wave boundary layer model for
evaluation of wind stress over waters of finite depth, Prog.
Oceanogr., 198, 102664, https://doi.org/10.1016/j.pocean.2021.102664,
2021.
Xu, Y. and Yu, X.: Enhanced Ocean Wave Modeling by Including Effect of
Breaking under Both Deep- and Shallow-Water Conditions – code files,
Zenodo [code], https://doi.org/10.5281/zenodo.7047221, 2022a.
Xu, Y. and Yu, X.: Enhanced Ocean Wave Modeling by Including Effect of
Breaking under Both Deep- and Shallow-Water Conditions – input files of the
controlled normal condition cases, Zenodo [code],
https://doi.org/10.5281/zenodo.7047234, 2022b.
Xu, Y. and Yu, X.: Enhanced Ocean Wave Modeling by Including Effect of
Breaking under Both Deep- and Shallow-Water Conditions – input files of
hurricane Ivan case, Zenodo [code], https://doi.org/10.5281/zenodo.7047240, 2022c.
Xu, Y. and Yu, X.: Enhanced Ocean Wave Modeling by Including Effect of
Breaking under Both Deep- and Shallow-Water Conditions – input files of
hurricane Katrina case, Zenodo [code], https://doi.org/10.5281/zenodo.7047244,
2022d.
Young, I. R.: Wind generated ocean waves, Elsevier, eBook ISBN 9780080543802, 1999.
Young, I. R. and Verhagen, L. A.: The growth of fetch limited waves in water
of finite depth. Part 1. Total energy and peak frequency, Coast. Eng., 29, 47–78, https://doi.org/10.1016/S0378-3839(96)00006-3, 1996.
Yuan, Y., Tung, C. C., and Huang, N. E.: Statistical characteristics of
breaking waves, in: Wave Dynamics and Radio Probing of the Ocean Surface,
edited by: Phillips, O. M., and Hasselmann, K., Springer US, Boston, MA,
265–272, https://doi.org/10.1007/978-1-4684-8980-4_18, 1986.
Zakharov, V., Resio, D., and Pushkarev, A.: Balanced source terms for wave generation within the Hasselmann equation, Nonlin. Processes Geophys., 24, 581–597, https://doi.org/10.5194/npg-24-581-2017, 2017.
Zakharov, V. E., Resio, D., and Pushkarev, A.: New wind input term
consistent with experimental, theoretical and numerical considerations,
arXiv [preprint], https://doi.org/10.48550/arXiv.1212.1069, 2012.
Zieger, S., Babanin, A. V., Erick Rogers, W., and Young, I. R.:
Observation-based source terms in the third-generation wave model WAVEWATCH,
Ocean Model., 96, 2–25, https://doi.org/10.1016/j.ocemod.2015.07.014,
2015.
Short summary
An accurate description of the wind energy input into ocean waves is crucial to ocean wave modeling, and a physics-based consideration of the effect of wave breaking is absolutely necessary to obtain such an accurate description, particularly under extreme conditions. This study evaluates the performance of a recently improved formula, taking into account not only the effect of breaking but also the effect of airflow separation on the leeside of steep wave crests in a reasonably consistent way.
An accurate description of the wind energy input into ocean waves is crucial to ocean wave...