Articles | Volume 11, issue 5
https://doi.org/10.5194/gmd-11-1849-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-1849-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Cohesive and mixed sediment in the Regional Ocean Modeling System (ROMS v3.6) implemented in the Coupled Ocean–Atmosphere–Wave–Sediment Transport Modeling System (COAWST r1234)
Christopher R. Sherwood
CORRESPONDING AUTHOR
U.S. Geological Survey, 384 Woods Hole Road, Woods Hole, MA 02543-1598, USA
Alfredo L. Aretxabaleta
U.S. Geological Survey, 384 Woods Hole Road, Woods Hole, MA 02543-1598, USA
Courtney K. Harris
Virginia Institute of Marine Science, College of William & Mary, Gloucester Point, VA 23062, USA
J. Paul Rinehimer
Virginia Institute of Marine Science, College of William & Mary, Gloucester Point, VA 23062, USA
currently at: WEST Consultants, Bellevue, WA 98055, USA
Romaric Verney
IFREMER, Plouzane, France
Bénédicte Ferré
U.S. Geological Survey, 384 Woods Hole Road, Woods Hole, MA 02543-1598, USA
currently at: CAGE-Centre for Arctic Gas Hydrate, Environment, and
Climate; Department of Geosciences, UiT The Arctic University of Norway, 9037 Tromsø, Norway
Related authors
No articles found.
Coline Poppeschi, Guillaume Charria, Anne Daniel, Romaric Verney, Peggy Rimmelin-Maury, Michaël Retho, Eric Goberville, Emilie Grossteffan, and Martin Plus
Biogeosciences, 19, 5667–5687, https://doi.org/10.5194/bg-19-5667-2022, https://doi.org/10.5194/bg-19-5667-2022, 2022
Short summary
Short summary
This paper aims to understand interannual changes in the initiation of the phytoplankton growing period (IPGP) in the current context of global climate changes over the last 20 years. An important variability in the timing of the IPGP is observed with a trend towards a later IPGP during this last decade. The role and the impact of extreme events (cold spells, floods, and wind burst) on the IPGP is also detailed.
Neil K. Ganju, Jeremy M. Testa, Steven E. Suttles, and Alfredo L. Aretxabaleta
Ocean Sci., 16, 593–614, https://doi.org/10.5194/os-16-593-2020, https://doi.org/10.5194/os-16-593-2020, 2020
Short summary
Short summary
Seagrasses, as plants, need light for photosynthesis and production. This study measured the changes in productivity and light in a back-barrier estuary and connected those changes with the type of seabed within the estuary. We found that the locations with seagrass on the seabed had more light getting through the water and higher productivity because of the way seagrass keeps sediment on the seabed during wave events. When sediment stays on the bed, it cannot reduce the light in the water.
Alfredo L. Aretxabaleta, Neil K. Ganju, Zafer Defne, and Richard P. Signell
Nat. Hazards Earth Syst. Sci., 19, 1823–1838, https://doi.org/10.5194/nhess-19-1823-2019, https://doi.org/10.5194/nhess-19-1823-2019, 2019
Short summary
Short summary
Water levels in bays are affected by open-ocean changes and wind. Tides are more dampened in the bays than storm surges and sea level rise. We compare observed and modeled levels with ocean conditions and combine them with analytical models. We consider the local setup, caused by wind along the bay. Expansion using the ADCIRC tidal database will allow coverage of other bay systems on the United States East Coast. Spatial estimates of water level can inform decisions about bay flooding hazards.
Neil K. Ganju, Jeremy M. Testa, Steven E. Suttles, and Alfredo L. Aretxabaleta
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-335, https://doi.org/10.5194/bg-2018-335, 2018
Revised manuscript not accepted
Short summary
Short summary
Estuaries are productive ecosystems that provide habitat for flora and fauna. We measured changes in light and oxygen, along with variables such as tides and waves, to understand how productivity in the estuary changed over daily and seasonal time periods. We found large differences in productivity between channels and seagrass beds, as well as a link between light climate and productivity. This study will help us understand how estuaries will respond to future changes in conditions.
Tarandeep S. Kalra, Alfredo Aretxabaleta, Pranay Seshadri, Neil K. Ganju, and Alexis Beudin
Geosci. Model Dev., 10, 4511–4523, https://doi.org/10.5194/gmd-10-4511-2017, https://doi.org/10.5194/gmd-10-4511-2017, 2017
Short summary
Short summary
The paper details the sensitivity of vegetation properties that are input to a 3-D submerged aquatic vegetation model within a coupled hydrodynamics and wave model. It describes a novel strategy to perform sensitivity analysis efficiently by using a combination of the Effective Quadratures method and Sobol' indices. This method reduces the number of simulations to understand the sensitivity patterns and also quantifies the amount of sensitivity.
Julia M. Moriarty, Courtney K. Harris, Katja Fennel, Marjorie A. M. Friedrichs, Kehui Xu, and Christophe Rabouille
Biogeosciences, 14, 1919–1946, https://doi.org/10.5194/bg-14-1919-2017, https://doi.org/10.5194/bg-14-1919-2017, 2017
Short summary
Short summary
In coastal aquatic environments, resuspension of sediment and organic material from the seabed into the overlying water can impact biogeochemistry. Here, we used a novel modeling approach to quantify this impact for the Rhône River delta. In the model, resuspension increased oxygen consumption during individual resuspension events, and when results were averaged over 2 months. This implies that observations and models that only represent calm conditions may underestimate net oxygen consumption.
M. Grifoll, A. L. Aretxabaleta, J. L. Pelegrí, and M. Espino
Ocean Sci., 12, 137–151, https://doi.org/10.5194/os-12-137-2016, https://doi.org/10.5194/os-12-137-2016, 2016
Short summary
Short summary
We investigate the rapidly changing equilibrium between the momentum sources and sinks during the passage of a single two-peak storm over the Catalan inner shelf (NW Mediterranean Sea). At 24m water depth, a primary momentum balance between acceleration, pressure gradient and frictional forces (surface and bottom) is established. The frictional adjustment timescale was around 10h, consistent with the e-folding time obtained from bottom drag parameterizations.
A. L. Aretxabaleta, K. W. Smith, and J. Ballabrera-Poy
Ocean Sci. Discuss., https://doi.org/10.5194/osd-12-983-2015, https://doi.org/10.5194/osd-12-983-2015, 2015
Revised manuscript has not been submitted
Short summary
Short summary
We estimate global surface salinity means and trends using historical (1950-2014) monthly fields and recent SMOS satellite data. We separate the regimes by fitting a Gaussian Mixture Model with a non-subjective method. There are three separate regimes: A (1950-1990) with small trends; B (1990-2009) with enhanced trends; and C (2009-2014) with significantly larger trends. The trend acceleration could be related to an enhanced hydrological cycle or to changes in sampling methodology.
N. K. Ganju, J. L. Miselis, and A. L. Aretxabaleta
Biogeosciences, 11, 7193–7205, https://doi.org/10.5194/bg-11-7193-2014, https://doi.org/10.5194/bg-11-7193-2014, 2014
Short summary
Short summary
Light availability to seagrass is an important factor in their success. We deployed instrumentation to measure light in Barnegat Bay, New Jersey, and found lower availability in the southern bay due to high turbidity (suspended sediment), while the northern bay has higher availability. In the northern bay, dissolved organic material and chlorophyll are most responsible for blocking light to the seagrass canopy. We also found that boat wakes do not have a large effect on sediment resuspension.
Related subject area
Oceanography
LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry
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
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
Spurious numerical mixing under strong tidal forcing: a case study in the South East Asian Seas using the Symphonie model (v3.1.2)
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
Experimental design for the marine ice sheet and ocean model intercomparison project – phase 2 (MISOMIP2)
Impact of increased resolution on Arctic Ocean simulations in Ocean Model Intercomparison Project phase 2 (OMIP-2)
Modelling the water isotopes distribution in the Mediterranean Sea using a high-resolution oceanic model (NEMO-MED12-watiso-v1.0): Evaluation of model results against in-situ observations
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
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)
PPCon 1.0: Biogeochemical Argo Profile Prediction with 1D Convolutional Networks
Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard
Open-ocean tides simulated by ICON-O, version icon-2.6.6
Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll
An optimal transformation method for inferring ocean tracer sources and sinks
Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var
Using the COAsT Python package to develop a standardised validation workflow for ocean physics models
Improving Antarctic Bottom Water precursors in NEMO for climate applications
Formulation, optimization, and sensitivity of NitrOMZv1.0, a biogeochemical model of the nitrogen cycle in oceanic oxygen minimum zones
Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu
Adding sea ice effects to a global operational model (NEMO v3.6) for forecasting total water level: approach and impact
Enhanced ocean wave modeling by including effect of breaking under both deep- and shallow-water conditions
An internal solitary wave forecasting model in the northern South China Sea (ISWFM-NSCS)
The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methylmercury in fish
Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0)
Arctic Ocean simulations in the CMIP6 Ocean Model Intercomparison Project (OMIP)
ChemicalDrift 1.0: an open-source Lagrangian chemical-fate and transport model for organic aquatic pollutants
The Met Office operational wave forecasting system: the evolution of the regional and global models
4DVarNet-SSH: end-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry
Development and validation of a global 1∕32° surface-wave–tide–circulation coupled ocean model: FIO-COM32
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud
EGUsphere, https://doi.org/10.5194/egusphere-2024-613, https://doi.org/10.5194/egusphere-2024-613, 2024
Short summary
Short summary
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 and compromise their realism. We illustrate here the spurious effect that tides can have on simulations of South East Asia. Although they play an important role in setting the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. The paper also provides insights on how to reduce these errors.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-95, https://doi.org/10.5194/egusphere-2024-95, 2024
Short summary
Short summary
Global climate models do not reliably simulate sea-level change arising from 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 2nd 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.
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
Short summary
Short summary
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.
Mohamed Ayache, Jean-Claude Dutay, Anne Mouchet, Kazuyo Tachikawa, Camille Risi, and Gilles Ramstein
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-237, https://doi.org/10.5194/gmd-2023-237, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
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.
Qian Wang, Fei Chai, Yang Zhang, Yinglong Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-236, https://doi.org/10.5194/gmd-2023-236, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
EGUsphere, https://doi.org/10.5194/egusphere-2023-1876, https://doi.org/10.5194/egusphere-2023-1876, 2023
Short summary
Short summary
Harness AI for better ocean insights. BGC-Argo floats collect deep ocean data, yet forecasting vital nutrient levels is a challenge. Our novel AI approach, PPCon, learns from Argo float measurements and provides improved nutrient predictions. This enhances our understanding of ocean dynamics and nutrient distribution.
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
Short summary
Short summary
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
Short summary
Short summary
The new ocean general circulation model ICON-O is developed for running experiments at kilometer scales and beyond. One targeted application is to simulate internal tides crucial for ocean mixing. To ensure their realism, which is difficult to assess, we evaluate the barotropic tides that generate internal tides. We show that ICON-O is able to realistically simulate the major aspects of the observed barotropic tides and discuss the aspects that impact the quality of the simulated tides.
Bror F. Jönsson, Christopher L. Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael L. Forget, Christian Müller, Marie-Fanny Racault, Christopher N. Hill, Thomas Jackson, and Shubha Sathyendranath
Geosci. Model Dev., 16, 4639–4657, https://doi.org/10.5194/gmd-16-4639-2023, https://doi.org/10.5194/gmd-16-4639-2023, 2023
Short summary
Short summary
While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover's distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.
Jan David Zika and Sohail Taimoor
EGUsphere, https://doi.org/10.5194/egusphere-2023-1220, https://doi.org/10.5194/egusphere-2023-1220, 2023
Short summary
Short summary
We describe a method to relate the fluxes of heat and fresh water at the sea surface, to the resulting distribution of sea water among categories such as warm and salty, cold and salty, etc. 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.
Rafael Santana, Helen Macdonald, Joanne O'Callaghan, Brian Powell, Sarah Wakes, and Sutara H. Suanda
Geosci. Model Dev., 16, 3675–3698, https://doi.org/10.5194/gmd-16-3675-2023, https://doi.org/10.5194/gmd-16-3675-2023, 2023
Short summary
Short summary
We show the importance of assimilating subsurface temperature and velocity data in a model of the East Auckland Current. Assimilation of velocity increased the representation of large oceanic vortexes. Assimilation of temperature is needed to correctly simulate temperatures around 100 m depth, which is the most difficult region to simulate in ocean models. Our simulations showed improved results in comparison to the US Navy global model and highlight the importance of regional models.
David Byrne, Jeff Polton, Enda O'Dea, and Joanne Williams
Geosci. Model Dev., 16, 3749–3764, https://doi.org/10.5194/gmd-16-3749-2023, https://doi.org/10.5194/gmd-16-3749-2023, 2023
Short summary
Short summary
Validation is a crucial step during the development of models for ocean simulation. The purpose of validation is to assess how accurate a model is. It is most commonly done by comparing output from a model to actual observations. In this paper, we introduce and demonstrate usage of the COAsT Python package to standardise the validation process for physical ocean models. We also discuss our five guiding principles for standardised validation.
Katherine Hutchinson, Julie Deshayes, Christian Éthé, Clément Rousset, Casimir de Lavergne, Martin Vancoppenolle, Nicolas C. Jourdain, and Pierre Mathiot
Geosci. Model Dev., 16, 3629–3650, https://doi.org/10.5194/gmd-16-3629-2023, https://doi.org/10.5194/gmd-16-3629-2023, 2023
Short summary
Short summary
Bottom Water constitutes the lower half of the ocean’s overturning system and is primarily formed in the Weddell and Ross Sea in the Antarctic due to interactions between the atmosphere, ocean, sea ice and ice shelves. Here we use a global ocean 1° resolution model with explicit representation of the three large ice shelves important for the formation of the parent waters of Bottom Water. We find doing so reduces salt biases, improves water mass realism and gives realistic ice shelf melt rates.
Daniele Bianchi, Daniel McCoy, and Simon Yang
Geosci. Model Dev., 16, 3581–3609, https://doi.org/10.5194/gmd-16-3581-2023, https://doi.org/10.5194/gmd-16-3581-2023, 2023
Short summary
Short summary
We present NitrOMZ, a new model of the oceanic nitrogen cycle that simulates chemical transformations within oxygen minimum zones (OMZs). We describe the model formulation and its implementation in a one-dimensional representation of the water column before evaluating its ability to reproduce observations in the eastern tropical South Pacific. We conclude by describing the model sensitivity to parameter choices and environmental factors and its application to nitrogen cycling in the ocean.
Rui Sun, Alison Cobb, Ana B. Villas Bôas, Sabique Langodan, Aneesh C. Subramanian, Matthew R. Mazloff, Bruce D. Cornuelle, Arthur J. Miller, Raju Pathak, and Ibrahim Hoteit
Geosci. Model Dev., 16, 3435–3458, https://doi.org/10.5194/gmd-16-3435-2023, https://doi.org/10.5194/gmd-16-3435-2023, 2023
Short summary
Short summary
In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS. We then performed a case study using the newly implemented model to study Tropical Cyclone Mekunu, which occurred in the Arabian Sea. We found that the coupled model better simulates the cyclone than the uncoupled model, but the impact of waves on the cyclone is not significant. However, the waves change the sea surface temperature and mixed layer, especially in the cold waves produced due to the cyclone.
Pengcheng Wang and Natacha B. Bernier
Geosci. Model Dev., 16, 3335–3354, https://doi.org/10.5194/gmd-16-3335-2023, https://doi.org/10.5194/gmd-16-3335-2023, 2023
Short summary
Short summary
Effects of sea ice are typically neglected in operational flood forecast systems. In this work, we capture these effects via the addition of a parameterized ice–ocean stress. The parameterization takes advantage of forecast fields from an advanced ice–ocean model and features a novel, consistent representation of the tidal relative ice–ocean velocity. The new parameterization leads to improved forecasts of tides and storm surges in polar regions. Associated physical processes are discussed.
Yue Xu and Xiping Yu
Geosci. Model Dev., 16, 2811–2831, https://doi.org/10.5194/gmd-16-2811-2023, https://doi.org/10.5194/gmd-16-2811-2023, 2023
Short summary
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.
Yankun Gong, Xueen Chen, Jiexin Xu, Jieshuo Xie, Zhiwu Chen, Yinghui He, and Shuqun Cai
Geosci. Model Dev., 16, 2851–2871, https://doi.org/10.5194/gmd-16-2851-2023, https://doi.org/10.5194/gmd-16-2851-2023, 2023
Short summary
Short summary
Internal solitary waves (ISWs) play crucial roles in mass transport and ocean mixing in the northern South China Sea. Massive numerical investigations have been conducted in this region, but there was no systematic evaluation of a three-dimensional model about precisely simulating ISWs. Here, an ISW forecasting model is employed to evaluate the roles of resolution, tidal forcing and stratification in accurately reproducing wave properties via comparison to field and remote-sensing observations.
Johannes Bieser, David J. Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Soerensen, and Corinna Schrum
Geosci. Model Dev., 16, 2649–2688, https://doi.org/10.5194/gmd-16-2649-2023, https://doi.org/10.5194/gmd-16-2649-2023, 2023
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Amoudry, L. O. and Souza, A. J.: Deterministic coastal morphological and sediment transport modeling: a review and discussion, Rev. Geophys., 49, RG2002, https://doi.org/10.1029/2010RG000341, 2011.
Ariathurai, R. and Arulanandan, K.: Erosion Rates of Cohesive Soils, Journal of Hydraulic Division, ASCE, 104, 279–283, 1978.
Booij, N., Ris, R. C., and Holthuijsen, L. H.: A third-generation wave model for coastal regions: 1. Model description and validation, J. Geophys. Res., 104, 7649–7666, https://doi.org/10.1029/98JC02622, 1999.
Boudreau, B. P.: Is burial velocity a master parameter for bioturbation?, Geochim. Cosmochim. Ac., 58, 1243–1250, 1994.
Boudreau, B. P.: Diagenetic Models and Their Implementation, Springer-Verlag, Berlin, 414 pp., 1997.
Beudin, A., Kalra, T. S., Ganju, N. K., and Warner, J. C.: Development of a Coupled Wave-Flow-Vegetation Interaction Model, Comput. Geosci., 100, 76–86, https://doi.org/10.1016/j.cageo.2016.12.010, 2017.
Birchler, J. J., Harris, C. K., Kniskern, T. A., and Sherwood, C.R .: Numerical model of geochronological tracers for deposition and reworking applied to the Mississippi subaqueous delta, J. Coast. Res., SI 85: 1–5, https://doi.org/10.2112/SI85-001.1, 2018.
Burchard, H. and Baumert, H.: The formation of estuary turbidity maxima due to density effects in the salt wedge. A hydrodynamic process study, J. Phys. Oceanogr., 20, 309–321, 1998.
Butman B., Aretxabaleta, A. L., Dickhudt, P. J., Dalyander, P. S., Sherwood, C. R., Anderson, D. M., Keafer, B. A., and Signell, R. P.: Investigating the importance of sediment resuspension in Alexandrium fundyense cyst population dynamics in the Gulf of Maine, Deep-Sea Res. Pt. II, 103, 74–95, https://doi.org/10.1016/j.dsr2.2013.10.011, 2014.
Caldwell, R. L. and Edmonds, D. A.: The effects of sediment properties on deltaic processes and morphologies: A numerical modeling study, J. Geophys. Res.-Earth, 119, 961–982, https://doi.org/10.1002/2013JF002965, 2014.
Cartwright, G. M., Friedrichs, C. T., and Smith, J. S.: A test of the ADV-based Reynolds-flux method for in situ estimation of sediment settling velocity in a muddy estuary, Geo-Mar. Lett., 33, 477–484, https://doi.org/10.1007/s00367-013-0340-4, 2013.
de Boer, P. L.: Mechanical effects of micro-organisms on intertidal bedform migration, Sedimentology, 28, 129–132, https://doi.org/10.1111/j.1365-3091.1981.tb01670.x, 1981.
de Deckere, E. M. G. T., Tolhurst, T. J., and de Brouwer, J. F. C.: Destabilization of Cohesive Intertidal Sediments by Infauna, Estuar. Coast. Shelf S., 53, 665–669, https://doi.org/10.1006/ecss.2001.0811, 2001.
del Barrio, P., Ganju, N. K., Aretxabaleta, A. L., Hayn, M., García, A., and Howarth, R. W.: Modeling Future Scenarios of Light Attenuation and Potential Seagrass Success in a Eutrophic Estuary, Estuar. Coast. Shelf S., 149, 13–23, https://doi.org/10.1016/j.ecss.2014.07.005, 2014.
Dickhudt, P. J.: Controls on erodibility in a partially mixed estuary: York River, Virginia, MS thesis, College of William and Mary, Gloucester Point, VA, 2008.
Dickhudt, P. J., Friedrichs, C. T., Schaffner, L. C., and Sanford, L. P.: Spatial and temporal variation in cohesive sediment erodibility in the York River estuary, eastern USA: A biologically influenced equilibrium modified by seasonal deposition, Mar. Geol., 267, 128–140, https://doi.org/10.1016/j.margeo.2009.09.009, 2009.
Dickhudt, P. J., Friedrichs, C. T., and Sanford, L. P.: Mud matrix solids fraction and bed erodibility in the York River estuary, USA, and other muddy environments, Cont. Shelf Res., 31, S3–S13, https://doi.org/10.1016/j.csr.2010.02.008, 2011.
DiToro, D. M.: Sediment Flux Modeling, Wiley-Interscience, New York, 624 pp., 2001.
Ditschke, D. and Markofsky, M.: A time-dependent flocculation model, in: Sediment and Ecohydraulics – INTERCOH 2005, Proceedings in Marine Science, edited by: Kusuda, T., Yamanishi, H., Spearman, J., and Gailani, J. Z., Elsevier, Amsterdam, 9, 241–253, https://doi.org/10.1016/S1568-2692(08)80019-8, 2008.
Droppo, I. G., Leppard, G. G., Liss, S. N., and Milligan, T. G.: Opportunities, needs, and strategic direction for research on flocculation in natural and engineered systems, in: Flocculation in Natural and Engineered Environmental Systems, edited by: Droppo, I. G., Leppard, G. G., Liss, S. N., and Milligan, T. G., CRC Press, London, 407–421, 2005.
Dyer, K. R.: Coastal and Estuarine Sediment Dynamics, John Wiley and Sons, Chichester, 1986.
Edmonds, D. A. and Slingerland, R. L.: Significant effect of sediment cohesion on delta morphology, Nat. Geosci., 3, 105–109, https://doi.org/10.1038/ngeo730, 2010.
Einstein H. A. and Krone R. B.: Experiments to determine modes of cohesive sediment transport in salt water, J. Geophys. Res., 67, 1451–1461, https://doi.org/10.1029/JZ067i004p01451, 1962.
Eisma, D.: Flocculation and de-flocculation of suspended matter in estuaries, Neth. J. Sea Res., 20, 183–199, 1986.
Fall, K. A., Harris, C. K., Friedrichs, C. T., Rinehimer, J. P., and Sherwood, C. R.: Model behavior and sensitivity in an application of the cohesive bed component of the Community Sediment Transport Modeling System for the York River Estuary, VA, USA, J. Mar. Sci. Eng., 2, 413–436, https://doi.org/10.3390/jmse2020413, 2014.
Fasham, M. J. R., Ducklow, H. W., and McKelvie S. M.: A nitrogen-based model of plankton dynamics in the oceanic mixed layer, J. Mar. Res., 48, 591–639, 1990.
Fennel, K., Wilkin, J., Levin, J., Moisan, J., and O'Reilly, J.: Nitrogen cycling in the Middle Atlantic Bight: Results from a three-dimensional model and implications for the North Atlantic nitrogen budget, Global Biogeochem. Cy., 20, GB3007, https://doi.org/10.1029/2005GB002456, 2006.
Harris, C. K. and Wiberg, P. L.: Approaches to quantifying long-term continental shelf sediment transport with an example from the northern California STRESS mid-shelf site, Cont. Shelf Res., 17, 1389–1418, 1997.
Harris, C. K. and Wiberg, P. L.: A two-dimensional, time-dependent model of suspended sediment transport and bed reworking for continental shelves, Comput. Geosci., 27, 675–690, 2001.
Hill, P. S. and Nowell, A. R. M.: Comparison of two models of aggregation in continental-shelf bottom boundary layers, J. Geophys. Res., 100, 22749–22763, 1995.
Hirano, M.: River bed degradation with armouring, in: Proceedings, Japan Society of Civil Engineers, Japan, 195, 55-65, https://doi.org/10.2208/jscej1969.1971.195_55, 1971.
Hsu T.-J., Jenkins, J. T., and Liu, P. L.-F.: On two-phase sediment transport: Dilute flow, J. Geophys. Res., 108, 3057, https://doi.org/10.1029/2001JC001276, 2003.
Huettel, M., Ziebis, W., and Forster, S.: Flow-induced uptake of particulate matter in permeable sediments, Limnol. Oceanogr., 41, 309–322, https://doi.org/10.4319/lo.1996.41.2.0309, 1999.
HydroQual, Inc.: A Primer for ECOMSED Version 1.4 Users Manual, HydroQual, Inc., Mahwah, NJ, 2004.
Jacobs, W., Le Hir, P., Van Kesteren, W., and Cann, P.: Erosion threshold of sand – mud mixtures, Cont. Shelf Res., 31, S14–S25, https://doi.org/10.1016/j.csr.2010.05.012, 2011.
Keyvani, A. and Strom, K.: Influence of Cycles of High and Low Turbulent Shear on the Growth Rate and Equilibrium Size of Mud Flocs, Mar. Geol., 354, 1–14, https://doi.org/10.1016/j.margeo.2014.04.010, 2014.
Khelifa, A. and Hill, P. S.: Models for effective density and settling velocity of flocs, J. Hydraul. Res., 44, 390–401, 2006.
Kirby, R.: High Concentration Suspension (Fluid Mud) Layers in Estuaries, in: Physical Processes in Estuaries, edited by: Dronkers, J. and van Leussen, W., Springer, Berlin, Heidelberg, 463–487, https://doi.org/10.1007/978-3-642-73691-9_23, 1988.
Knoch, D. and Malcherek, A.: A numerical model for simulation of fluid mud with different rheological behaviors, Ocean Dynam., 61, 245–256, https://doi.org/10.1007/s10236-010-0327-x, 2011.
Kranenburg, C.: The fractal structure of cohesive sediment aggregates, Estuar. Coast. Shelf Sci., 39, 451–460, 1994.
Krone, R. B.: Flume studies of the transport of sediment in estuarial shoaling processes, Final Report, Hydraulic Engineering Laboratory and Sanitary Engineering Research Laboratory, Univ. of California, Berkeley, 1962.
Le Hir, P., Bassoullet, P., and Jestin, H.: Application of the continuous modeling concept to simulate high-concentration suspended sediment in a macrotidal estuary, in: Proceedings in Marine Science, Coastal and Estuarine Fine Sediment Processes, edited by: McAnally, W. H. and Mehta, A. J., Elsevier, 229–247, https://doi.org/10.1016/S1568-2692(00)80124-2, 2000.
Le Hir, P., Cayocca, F., and Waeles, B.: Dynamics of sand and mud mixtures: A multiprocess-based modelling strategy, Cont. Shelf Res., 3, S135–S149, 2011.
Lecroart, P., Maire, O., Schmidt, S., Grémare, A., Anschutz, P., and Meysman F. J. R.: Bioturbation, short-lived radioisotopes, and the tracer-dependence of biodiffusion coefficients, Geochim. Cosmochim. Ac., 74, 21, 6049–6063, https://doi.org/10.1016/j.gca.2010.06.010, 2010.
Letter, J. V.: Significance of probabilistic parameterization in cohesive sediment bed exchange, PhD thesis, Univ. of Florida, Gainesville, 2009.
Letter, J. V. and Mehta, A. J.: A heuristic examination of cohesive sediment bed exchange in turbulent flows, Coast. Eng., 58, 779–789, 2011.
Li, Q. W., Benson M. Harlan, M., Robichaux, P., Sha, X., Xu, K., and Straub, K. M.: Influence of sediment cohesion on deltaic morphodynamics and stratigraphy over basin-filling time scales, J. Geophys. Res.-Earth, 122, 1808–1826, https://doi.org/10.1002/2017JF004216, 2017.
Lick, W., Huang, H., and Jepsen, R.: Flocculation of fine-grained sediment due to differential settling, J. Geophys. Res., 98, 10279–10288, 1993.
Lumborg, U.: Modelling the deposition, erosion, and flux of cohesive sediment through Oresund, J. Mar. Syst., 56, 179–193, 2005.
Lumborg, U. and Pejrup, M.: Modelling of cohesive sediment transport in a tidal lagoon – an annual budget, Mar. Geol., 218, 1–16, 2005.
Lumborg, U. and Windelin, A.: Hydrography and cohesive sediment modelling: application to the Romo Dyb tidal area, J. Mar. Syst., 38, 287–303, 2003.
Maa, J. P.-Y., Sanford, L. P., and Schoellhamer, D. H. (Eds): Estuarine and Coastal Fine Sediment Dynamics: INTERCOH 2003, vol. 8, Proceedings in Marine Science, Elsevier, Amsterdam, 2007.
MacCready, P. and Geyer, W. R.: Estuarine salt flux through an isohaline surface, J. Geophys. Res., 106, 11629–11637, 2001.
MacDonald, I., Vincent, C. E., Thorne, P. D., and Moate, B. D.: Acoustic scattering from a suspension of flocculated sediments, J. Geophys. Res., 118, 2581–2594, https://doi.org/10.1002/jgrc.20197, 2013.
Maerz, J., Verney, R., Wirtz, K., and Feudel, U.: Modeling flocculation processes: Intercomparison of a size class-based model and a distribution-based model, Cont. Shelf Res., 31, S84–S93, https://doi.org/10.1016/j.csr.2010.05.011, 2011.
Malarkey, J., Baas, J. H., Hope, J. A., Aspden, R. J., Parsons, D. R., Peakall, J., Paterson, D. M., Schindler, R. J., Ye, L., Lichtman, I. D., Bass, S. J., Davies, A. G., Manning, A. J., and Thorne, P. D.: The pervasive role of biological cohesion in bedform development, Nat. Commun., 6, 6257, https://doi.org/10.1038/ncomms7257, 2015.
Manning, A. J. and Dyer, K. R.: Mass settling flux of fine sediments in Northern European estuaries: measurements and predictions, Mar. Geol., 245, 107–122, 2007.
Manning, A. J., Baugh, J. V., Spearman, J. R., and Whitehouse, R. J. S.: Flocculation settling characteristics of mud: sand mixtures, Ocean Dynam., 60, 237–253, https://doi.org/10.1007/s10236-009-0251-0, 2010.
Manning, A. J., Baugh, J. V., Spearman, J. R., Pidduck, E. L., and Whitehouse, R. J. S.: The settling dynamics of flocculating mud-sand mixtures: Part 1 – Empirical algorithm development, Ocean Dynam., 61, 311–350, https://doi.org/10.1007/s10236-011-0394-7, 2011.
McCave, I. N.: Size spectra and aggregation of suspended particles in the deep ocean, Deep-Sea Res., 31, 329–352, 1984.
McCave, I. N. and Swift, S. A.: A physical model for the deposition of fine-grained sediments in the deep sea, GSA Bulletin, 87, 541–546, 1976.
Mehta, A. J.: Characterization of cohesive sediment properties and transport processes in estuaries, in: Lecture Notes on Coastal and Estuarine Studies, edited by: Mehta, A. J., Springer, Berlin, 14, 290–325, 1986.
Mehta, A. J.: Understanding fluid mud in a dynamic environment, Geo-Mar. Lett., 11, 113–118, https://doi.org/10.1007/BF02430995, 1991.
Mehta, A. J.: An Introduction to the Hydraulics of Fine Sediment Transport, World Scientific, 1039 pp, 2014.
Mehta, A. J., Manning, A. J., and Khare, Y. P.: A note on the Krone deposition equation and significance of floc aggregation, Mar. Geol., 354, 34–39, https://doi.org/10.1016/j.margeo.2014.04.002, 2014.
Mengual, B., Hir, P.L., Cayocca, F., and Garlan, T.: Modelling Fine Sediment Dynamics: Towards a Common Erosion Law for Fine Sand, Mud and Mixtures, Water, 9, 564, https://doi.org/10.3390/w9080564, 2017.
Merkel, U. H. and Kopmann, R.: A continuous vertical grain sorting model for Telemac & Sisyphe, in: River Flow 2012, edited by: Munoz, R. M., Taylor & Francis, London, 2012.
Michalakes, J., Chen, S., Dudhia, J., Hart, L., Klemp, J., Middlecoff, J., and Skamarock, W.: Development of a next-generation regional weather research and forecast model, in: Developments in Teracomputing, World Scientific, 269–276, https://doi.org/10.1142/9789812799685_0024, 2001.
Mietta, F., Chassagne, C., Manning, A. J., and Winterwerp, J. C.: Influence of shear rate, organic matter content, pH and salinity on mud flocculation, Ocean Dynam., 59, 751–763, https://doi.org/10.1007/s10236-009-0231-4, 2009.
Mitchener, H. and Torfs, H.: Erosion of mud/sand mixtures, Coast. Eng., 29, 1–25, 1996.
Moriarty, J. M., Harris, C. K., Fennel, K., Friedrichs, M. A. M., Xu, K., and Rabouille, C.: The roles of resuspension, diffusion and biogeochemical processes on oxygen dynamics offshore of the Rhône River, France: a numerical modeling study, Biogeosciences, 14, 1919–1946, https://doi.org/10.5194/bg-14-1919-2017, 2017.
Nguyen, H.-H. and Chua, L. H. C.: Simplified physically based model for estimating effective floc density, J. Hydraul. Eng., 137, 843–846, 2011.
Panagiotopoulos, I., Voulgaris, G., and Collins, M. B.: The influence of clay on the threshold of movement in fine sandy beds, Coast. Eng., 32, 19–43, 1997.
Parsons, D. R., Schindler, R. J., Hope, J. A., Malarkey, J., Baas, J. H., Peakall, J., Manning, A. J., Ye, L., Simmons, S., Paterson D. M., Aspden, R. J., Bass, S, J., Davies, A. G., Lichtman, I. D., and Thorne, P. D.: The role of biophysical cohesion on subaqueous bed form size, Geophys. Res. Lett., 43, 1566–1573, https://doi.org/10.1002/2016GL067667, 2016.
Paterson, D. M., Crawford, R. M., and Little, C.: Subaerial exposure and changes in the stability of intertidal estuarine sediments, Estuar. Coast. Shelf S., 30, 541–556, https://doi.org/10.1016/0272-7714(90)90091-5, 1990.
Pilditch, C. A., Widdows, J., Kuhn, N. J., Pope, N. D., and Brinsley, M. D.: Effects of low tide rainfall on the erodibility of intertidal cohesive sediments, Cont. Shelf Res., 28, 1854–1865. https://doi.org/10.1016/j.csr.2008.05.001, 2008.
Ralston, D. K., Geyer, W. R., and Warner, J. C.: Bathymetric controls on sediment transport in the Hudson River estuary: Lateral asymmetry and frontal trapping, J. Geophys. Res., 117, C10013, https://doi.org/10.1029/2012JC008124, 2012.
Rinehimer, J. P., Harris, C. K., Sherwood, C. R., and Sanford, L. P.: Sediment consolidation in a muddy, tidally-dominated environment: Model behavior and sensitivity, in: 10th International Conference on Estuarine and Coastal Modeling, 5–7 November 2007, Newport, Rhode Island, USA, 819–838, https://doi.org/10.1061/40990(324)44, 2008.
Sanford, L. P.: Modeling a dynamically varying mixed sediment bed with erosion, deposition, bioturbation, consolidation, and armoring, Comput. Geosci., 34, 1263–1283, 2008.
Sanford, L. P. and Maa, J. P. Y.: A unified erosion formulation for fine sediments, Mar. Geol., 179, 9–23, 2001.
Shchepetkin, A. F. and McWilliams, J. C.: The Regional Oceanic Modeling System (ROMS): A Split-Explicit, Free-Surface, Topography-Following-Coordinate Oceanic Model, Ocean Model., 9, 347–404, https://doi.org/10.1016/j.ocemod.2004.08.002, 2005.
Sherwood, C. R., Drake, D. E., Wiberg, P. L., and Wheatcroft, R. A.: Prediction of the fate of p,p'-DDE in sediment on the Palos Verdes shelf, California, USA, Cont. Shelf Res., 22, 1025–1058, 2002.
Slade, W. H., Boss, E. S., and Russo, C.: Effects of particle aggregation and disaggregation on their inherent optical properties, Opt. Express, 19, 7945–7959, 2011.
Smoluchowski, M.: Versuch einer mathematischen theorie des koagulations-kinetik kolloid losungren, Zeitschrift fur Physikalische Chemie, 92, 129–168, 1917.
Soulsby, R. L., Manning, A. J., Spearman, J., and Whitehouse, R. J. S.: Settling Velocity and Mass Settling Flux of Flocculated Estuarine Sediments, Mar. Geol., 339, 1–12, https://doi.org/10.1016/j.margeo.2013.04.006, 2013.
Spearman, J. and Manning, A. J.: On the significance of mud transport algorithms for the modelling of intertidal flats, Chapter 28, in: Proceedings in Marine Science, Sediment and Ecohydraulics, edited by: Kusuda, T., Yamanishi, H., Spearman, J., and Gailani, J. Z., Elsevier, https://doi.org/10.1016/S1568-2692(08)80030-7, 411–430, 2008.
Spearman, J. R., Manning, A. J., and Whitehouse, R. J. S.: The settling dynamics of flocculating mud-sand mixtures: Part 2 – Numerical modelling, Ocean Dyn., 61, 351–370, 2011.
Swift, D. J. P., Stull, J. K., Niedoroda, A. W., Reed, C. W., Wong, G. T. F., and Foyle, B. A.: Estimates of the Biodiffusion Coefficient, DB, from Composition of the Benthic Infaunal Community, Report prepared for the Los Angeles County Sanitation Districts, Contribution No. 5 of the Sediment Dynamics Laboratory, Old Dominion University, Norfolk, Virginia, 1994.
Swift, D. J. P., Stull, J. K., Niedoroda, A. W., Reed, C. W., and Wong, G. T. F.: Contaminant dispersal on the Palos Verdes continental margin: II. Estimates of biodiffusion coefficient, Db, from composition of the benthic infaunal community, Sci. Total Environ., 179, 91–107, 1996.
Tassi, P. and Villaret, C.: SISYPHE v6.3 User's Manual, EDF, Laboratoire National d'Hydrulique et Environnement, Chatou, France, 73 pp., 2014.
Thorne, P. D., MacDonald, I. T., and Vincent, C. E.: Modelling acoustic scattering by suspended flocculating sediments, Cont. Shelf Res., 88, 81–91, https://doi.org/10.1016/j.csr.2014.07.003, 2014.
Tolman, H. L. and the WAVEWATCH III Development Group: User manual and system documentation of WAVEWATCH III version 4.18, Technical Note, Environmental Modeling Center, National Centers for Environmental Prediction, National Weather Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce, College Park, MD, 2014.
van der Wegen, M., Dastgheib, A., Jaffe, B. E., and Roelvink, D.: Bed composition generation for morphodynamic modeling: case study of San Pablo Bay in California, USA, Ocean Dynam., 61, 173–186, https://doi.org/10.1007/s10236-010-0314-2, 2011.
van Ledden, M., van Kesteren, W. G. M., and Winterwerp, J. C.: A conceptual framework for the erosion behaviour of sand – mud mixtures, Cont. Shelf Res., 24, 1–11, https://doi.org/10.1016/j.csr.2003.09.002, 2004.
van Leussen, W.: Estuarine macroflocs and their role in fine-grained sediment transport, PhD thesis, University of Utrecht, Utrecht, The Netherlands, 1994.
van Leussen, W.: Aggregation of Particles, Settling Velocity of Mud Flocs A Review, in: Physical Processes in Estuaries, Springer, Berlin, Heidelberg, 347–403, https://doi.org/10.1007/978-3-642-73691-9_19, 1988.
Verney, R., Lafite, R., Brun-Cottan, J. C., and Le Hir, P.: Behaviour of a floc population during a tidal cycle: Laboratory experiments and numerical modeling, Cont. Shelf Res., 31, S64–S83, https://doi.org/10.1016/j.csr.2010.02.005, 2011.
Villaret, C., Hervouet, J.-M., Kopmann, R., Merkel, U., and Davies, A. G.: Morphodynamic modeling using the Telemac finite-element system, Comput. Geosci., 53, 105–113, https://doi.org/10.1016/j.cageo.2011.10.004, 2011.
Warner, J. C., Sherwood, C. R., Signell, R. P., Harris, C. K., and Arango, H. G.: Development of a three-dimensional, regional, coupled wave, current, and sediment-transport model, Comput. Geosci., 34, 1284–1306, 2008.
Warner, J. C., Armstrong, B., He, R., and Zambon, J. B.: Development of a coupled ocean-atmosphere-wave-sediment transport (COAWST) modeling system, Ocean Model., 35, 230–244, https://doi.org/10.1016/j.ocemod.2010.07.010, 2010.
Wheatcroft, R. A. and Martin, W. R.: Spatial variation in short-term (234Th) sediment bioturbation intensity along an organic-carbon gradient, J. Mar. Res., 54, 763–792, 1996.
Whitehouse, R. J. S., Soulsby, R. L., Roberts, W., and Mitchener, H.: Dynamics of Marine Muds, Thomas Telford, London, 2000.
Wiberg, P. L., Drake, D. E., and Cacchione, D. A.: Sediment resuspension and bed armoring during high bottom stress events on the northern California inner continental shelf: measurements and predictions, Cont. Shelf Res., 14, 1191–1219, 1994.
Winterwerp, J. C.: A simple model for turbulence induced flocculation of cohesive sediment, J. Hydraulic Res., 36, 309–326, https://doi.org/10.1080/00221689809498621, 1998.
Winterwerp, J. C.: On the Dynamics of High-Concentrated Mud Suspensions, Technical University of Delft, Delft, The Netherlands, 1999.
Winterwerp, J. C.: On the flocculation and settling velocity of estuarine mud, Cont. Shelf Res., 22, 1339–1360, 2002.
Winterwerp, J. C. and Kranenburg, C. (Eds.): Fine Sediment Dynamics in the Marine Environment, Proceed. Marine Sci., Vol. 5, Elsevier, Amsterdam, 2002.
Winterwerp, J. C. and van Kesteren, W. G. M.: Introduction to the Physics of Cohesive Sediment in the Marine Environment, Elsevier, Amsterdam, 2004.
Winterwerp, J. C., Bale, A. J., Christie, M. C., Dyer, K. R., Jones, S., Lintern, D. G., Manning, A. J., Roberts, W., and Kranenburg, C.: Flocculation and settling velocity of fine sediment, Proceed. Marine Sci., 5, 25–40, 2002.
Winterwerp, J. C., Manning, A. J., Martens, C., de Mulder, T., and Vanlede J.: A heuristic formula for turbulence-induced flocculation of cohesive sediment, Estuar. Coast. Shelf S., 68, 195–207, 2006.
Winterwerp, J. C., Maa, J. P.-Y., Sanford, L. P., and Schoellhamer, D. H.: On the sedimentation rate of cohesive sediment, Proceed. Marine Sci., 8, 209–226, 2007.
Xu, F., Wang, D.-P., and Riemer, N.: Modeling flocculation processes of fine-grained particles using a size-resolved method: Comparison with published laboratory experiments, Cont. Shelf Res., 28, 2668–2677, https://doi.org/10.1016/j.csr.2008.09.001, 2008.
Xu, F., Wang, D.-P., and Riemer, N.: An idealized model study of flocculation on sediment trapping in an estuary turbidity maximum, Cont. Shelf Res., 30, 1314–1323, https://doi.org/10.1016/j.csr.2010.04.014, 2010.
Short summary
Cohesive sediment (mud) is ubiquitous in the world's coastal regions, but its behavior is complicated and often oversimplified by computer models. This paper describes extensions to a widely used open-source coastal ocean model that allow users to simulate important components of cohesive sediment transport.
Cohesive sediment (mud) is ubiquitous in the world's coastal regions, but its behavior is...