Articles | Volume 15, issue 11
Development and technical paper
02 Jun 2022
Development and technical paper | 02 Jun 2022
ROMSPath v1.0: offline particle tracking for the Regional Ocean Modeling System (ROMS)
Elias J. Hunter et al.
No articles found.
Bronwyn E. Cahill, Piotr Kowalczuk, Lena Kritten, Ulf Gräwe, John Wilkin, and Jürgen Fischer
This work quantifies the impact of optically significant water constituents on surface heating rates and thermal energy fluxes in the Western Baltic Sea. During productive months in 2018 (April to September), we found that the combined effect of CDOM and particulate absorption contributes to sea surface heating of between 0.4 and 0.9 K m-1 d-1 and a mean loss of heat (c. 5 Wm-2) from the sea to the atmosphere. This result may be important for regional heat balance budgets.
Alexander G. López, John L. Wilkin, and Julia C. Levin
Geosci. Model Dev., 13, 3709–3729,Short summary
This article describes a regional circulation model, Doppio, for the Mid-Atlantic Bight and the Gulf of Maine. The model demonstrates useful skill in comparison to a comprehensive suite of observations. Development focused on achieving a model configuration that allows decadal-scale simulations of physical ocean circulation that can underpin studies of ecosystems and biogeochemistry. Doppio captures the temperature and salinity stratification well, along with the large-scale mean circulation.
Related subject area
OceanographyThe tidal effects in the Finite-volumE Sea ice–Ocean Model (FESOM2.1): a comparison between parameterised tidal mixing and explicit tidal forcingHIDRA2: deep-learning ensemble sea level and storm tide forecasting in the presence of seiches – the case of the northern AdriaticMoana Ocean Hindcast – a > 25-year simulation for New Zealand waters using the Regional Ocean Modeling System (ROMS) v3.9 modelA nonhydrostatic oceanic regional model, ORCTM v1, for internal solitary wave simulationHow does 4DVar data assimilation affect the vertical representation of mesoscale eddies? A case study with observing system simulation experiments (OSSEs) using ROMS v3.9An 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 GulfThe Baltic Sea Model Intercomparison Project (BMIP) – a platform for model development, evaluation, and uncertainty assessmentAn ensemble Kalman filter system with the Stony Brook Parallel Ocean Model v1.0Wind work at the air-sea interface: a modeling study in anticipation of future space missionsImproved upper-ocean thermodynamical structure modeling with combined effects of surface waves and M2 internal tides on vertical mixing: a case study for the Indian OceanThe bulk parameterizations of turbulent air–sea fluxes in NEMO4: the origin of sea surface temperature differences in a global model studyNeverWorld2: an idealized model hierarchy to investigate ocean mesoscale eddies across resolutionsObserving system simulation experiments reveal that subsurface temperature observations improve estimates of circulation and heat content in a dynamic western boundary currentParallel implementation of the SHYFEM (System of HydrodYnamic Finite Element Modules) modelBarotropic Tides in MPAS-Ocean: Impact of Ice Shelf CavitiesBlock-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 cycleImplementation and evaluation of open boundary conditions for sea ice in a regional coupled ocean (ROMS) and sea ice (CICE) modeling systemDINCAE 2.0: multivariate convolutional neural network with error estimates to reconstruct sea surface temperature satellite and altimetry observationsRADIv1: a non-steady-state early diagenetic model for ocean sediments in Julia and MATLAB/GNU OctaveIBI-CCS: a regional high-resolution model to simulate sea level in western EuropeEmpirical Lagrangian parametrization for wind-driven mixing of buoyant particles at the ocean surfaceImproving ocean modeling software NEMO 4.0 benchmarking and communication efficiencyImprovements 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 1.0ISWFoam: a numerical model for internal solitary wave simulation in continuously stratified fluidsPyCO2SYS v1.8: marine carbonate system calculations in PythonPlume spreading test case for coastal ocean modelsThe interpretation of temperature and salinity variables in numerical ocean model output and the calculation of heat fluxes and heat contentS2P3-R v2.0: computationally efficient modelling of shelf seas on regional to global scalesThe Lagrangian-based Floating Macroalgal Growth and Drift Model (FMGDM v1.0): application to the Yellow Sea green tideNemo-Nordic 2.0: operational marine forecast model for the Baltic SeaAustralian tidal currents – assessment of a barotropic model (COMPAS v1.3.0 rev6631) with an unstructured gridSedapp v2021: a nonlinear diffusion-based forward stratigraphic model for shallow marine environmentsA discrete interaction numerical model for coagulation and fragmentation of marine detritic particulate matter (Coagfrag v.1)Parallel computing efficiency of SWAN 40.91Integrating CVMix into GOTM (v6.0): a consistent framework for testing, comparing, and applying ocean mixing schemesA NEMO-based model of Sargassum distribution in the tropical Atlantic: description of the model and sensitivity analysis (NEMO-Sarg1.0)Evaluating the physical and biogeochemical state of the global ocean component of UKESM1 in CMIP6 historical simulationsIron and sulfur cycling in the cGENIE.muffin Earth system model (v0.9.21)BFM17 v1.0: a reduced biogeochemical flux model for upper-ocean biophysical simulationsA mechanistic analysis of tropical Pacific dynamic sea level in GFDL-OM4 under OMIP-I and OMIP-II forcingsComparison of ocean vertical mixing schemes in the Max Planck Institute Earth System Model (MPI-ESM1.2)MESMO 3: Flexible phytoplankton stoichiometry and refractory dissolved organic matterHIDRA 1.0: deep-learning-based ensemble sea level forecasting in the northern AdriaticTowards multiscale modeling of ocean surface turbulent mixing using coupled MPAS-Ocean v6.3 and PALM v5.0Improved representation of river runoff in Estimating the Circulation and Climate of the Ocean Version 4 (ECCOv4) simulations: implementation, evaluation, and impacts to coastal plume regionsThe Regional Ice Ocean Prediction System v2: a pan-Canadian ocean analysis system using an online tidal harmonic analysis
Pengyang Song, Dmitry Sidorenko, Patrick Scholz, Maik Thomas, and Gerrit Lohmann
Geosci. Model Dev., 16, 383–405,Short summary
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,Short summary
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,Short summary
The current paper describes the configuration and evaluation of the Moana Ocean Hindcast, a > 25-year simulation of the ocean state around New Zealand using the Regional Ocean Modeling System v3.9. This is the first open-access, long-term, continuous, realistic ocean simulation for this region and provides information for improving the understanding of the ocean processes that affect the New Zealand exclusive economic zone.
Hao Huang, Pengyang Song, Shi Qiu, Jiaqi Guo, and Xueen Chen
Geosci. Model Dev., 16, 109–133,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
Comparisons of oceanographic climate data from different models often suffer from different model setups, forcing fields, and output of variables. This paper provides a protocol to harmonize these elements to set up multidecadal simulations for the Baltic Sea, a marginal sea in Europe. First results are shown from six different model simulations from four different model platforms. Topical studies for upwelling, marine heat waves, and stratification are also assessed.
Shun Ohishi, Tsutomu Hihara, Hidenori Aiki, Joji Ishizaka, Yasumasa Miyazawa, Misako Kachi, and Takemasa Miyoshi
Geosci. Model Dev., 15, 8395–8410,Short summary
We develop an ensemble-Kalman-filter-based regional ocean data assimilation system in which satellite and in situ observations are assimilated at a daily frequency. We find the best setting for dynamical balance and accuracy based on sensitivity experiments focused on how to inflate the ensemble spread and how to apply the analysis update to the model evolution. This study has a broader impact on more general data assimilation systems in which the initial shocks are a significant issue.
Hector S. Torres, Patrice Klein, Jinbo Wang, Alexander Wineteer, Bo Qiu, Andrew F. Thompson, Lionel Renault, Ernesto Rodriguez, Dimitris Menemenlis, Andrea Molod, Christopher N. Hill, Ehud Strobach, Hong Zhang, Mar Flexas, and Dragana Perkovic-Martin
Geosci. Model Dev., 15, 8041–8058,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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.
Nairita Pal, Kristin Nicole Barton, Mark Roger Petersen, Steven Richard Brus, Darren Engwirda, Brian K. Arbic, Andrew Frank Roberts, Joannes J. Westerink, and Damrongsak Wiraset
Geosci. Model Dev. Discuss.,
Preprint under review for GMDShort summary
Understanding tides is essential to accurately predict ocean currents. Over the next several decades coastal processes such as flooding, erosion will be severely impacted due to climate change. Tides affect currents along the coastal regions the most. In this manuscript 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 tides-ice interactions.
Young-Kwang Choi, Fengyan Shi, Matt Malej, Jane M. Smith, James T. Kirby, and Stephan T. Grilli
Geosci. Model Dev., 15, 5441–5459,Short summary
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,Short summary
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,Short summary
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,Short summary
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.
Alexander Barth, Aida Alvera-Azcárate, Charles Troupin, and Jean-Marie Beckers
Geosci. Model Dev., 15, 2183–2196,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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.
David A. Griffin, Mike Herzfeld, Mark Hemer, and Darren Engwirda
Geosci. Model Dev., 14, 5561–5582,Short summary
In support of the developing ocean renewable energy sector, and indeed all mariners, we have developed a new tidal model for Australian waters and thoroughly evaluated it using a new compilation of tide gauge and current meter data. We show that while there is certainly room for improvement, the model provides useful predictions of tidal currents for about 80 % (by area) of Australian shelf waters. So we intend to commence publishing tidal current predictions for those regions soon.
Jingzhe Li, Piyang Liu, Shuyu Sun, Zhifeng Sun, Yongzhang Zhou, Liang Gong, Jinliang Zhang, and Dongxing Du
Geosci. Model Dev., 14, 4925–4937,Short summary
This paper introduces Sedapp, a basin fill simulation tool. Sedapp is an open-source computer code written in R language. Using this program, one can simulate the formation of sedimentary strata, especially in shallow marine environments injected by rivers. With proper parameter settings, the simulation results are very similar to the real geological bodies. Sedapp can also be used in continental fault basin environments, which may serve as a tool for oil exploration.
Gwenaëlle Gremion, Louis-Philippe Nadeau, Christiane Dufresne, Irene R. Schloss, Philippe Archambault, and Dany Dumont
Geosci. Model Dev., 14, 4535–4554,Short summary
An accurate description of detritic organic particles is key to improving estimations of carbon export into the ocean abyss in ocean general circulation models. Yet, most parametrization are numerically impractical due to the required number of tracers needed to resolve the particle size spectrum. Here, a new parametrization that aims to minimize the tracers number while accurately describing the particles dynamics is developed and tested in a series of idealized numerical experiments.
Christo Rautenbach, Julia C. Mullarney, and Karin R. Bryan
Geosci. Model Dev., 14, 4241–4247,Short summary
The simulation of ocean waves is important for various reasons, e.g. ship route safety and coastal vulnerability assessments. SWAN is a popular tool with which ocean waves may be predicted. Simulations using this tool can be computationally expensive. The present study thus aimed to understand which typical parallel-computing SWAN model set-up will be most effective. There thus do exist configurations where these simulations are most time-saving and effective.
Qing Li, Jorn Bruggeman, Hans Burchard, Knut Klingbeil, Lars Umlauf, and Karsten Bolding
Geosci. Model Dev., 14, 4261–4282,Short summary
Different ocean vertical mixing schemes are usually developed in different modeling framework, making the comparison across such schemes difficult. Here, we develop a consistent framework for testing, comparing, and applying different ocean mixing schemes by integrating CVMix into GOTM, which also extends the capability of GOTM towards including the effects of ocean surface waves. A suite of test cases and toolsets for developing and evaluating ocean mixing schemes is also described.
Julien Jouanno, Rachid Benshila, Léo Berline, Antonin Soulié, Marie-Hélène Radenac, Guillaume Morvan, Frédéric Diaz, Julio Sheinbaum, Cristele Chevalier, Thierry Thibaut, Thomas Changeux, Frédéric Menard, Sarah Berthet, Olivier Aumont, Christian Ethé, Pierre Nabat, and Marc Mallet
Geosci. Model Dev., 14, 4069–4086,Short summary
The tropical Atlantic has been facing a massive proliferation of Sargassum since 2011, with severe environmental and socioeconomic impacts. We developed a modeling framework based on the NEMO ocean model, which integrates transport by currents and waves, and physiology of Sargassum with varying internal nutrient quota, and considers stranding at the coast. Results demonstrate the ability of the model to reproduce and forecast the seasonal cycle and large-scale distribution of Sargassum biomass.
Andrew Yool, Julien Palmiéri, Colin G. Jones, Lee de Mora, Till Kuhlbrodt, Ekatarina E. Popova, A. J. George Nurser, Joel Hirschi, Adam T. Blaker, Andrew C. Coward, Edward W. Blockley, and Alistair A. Sellar
Geosci. Model Dev., 14, 3437–3472,Short summary
The ocean plays a key role in modulating the Earth’s climate. Understanding this role is critical when using models to project future climate change. Consequently, it is necessary to evaluate their realism against the ocean's observed state. Here we validate UKESM1, a new Earth system model, focusing on the realism of its ocean physics and circulation, as well as its biological cycles and productivity. While we identify biases, generally the model performs well over a wide range of properties.
Sebastiaan J. van de Velde, Dominik Hülse, Christopher T. Reinhard, and Andy Ridgwell
Geosci. Model Dev., 14, 2713–2745,Short summary
Biogeochemical interactions between iron and sulfur are central to the long-term biogeochemical evolution of Earth’s oceans. Here, we introduce an iron–sulphur cycle in a model of Earth's oceans. Our analyses show that the results of the model are robust towards parameter choices and that simulated concentrations and reactions are comparable to those observed in ancient ocean analogues (anoxic lakes). Our model represents an important step forward in the study of iron–sulfur cycling.
Katherine M. Smith, Skyler Kern, Peter E. Hamlington, Marco Zavatarelli, Nadia Pinardi, Emily F. Klee, and Kyle E. Niemeyer
Geosci. Model Dev., 14, 2419–2442,Short summary
We present a newly developed reduced-order biogeochemical flux model that is complex and flexible enough to capture open-ocean ecosystem dynamics but reduced enough to incorporate into highly resolved numerical simulations with limited additional computational cost. The model provides improved correlations between model output and field data, indicating that significant improvements in the reproduction of real-world data can be achieved with a small number of variables.
Chia-Wei Hsu, Jianjun Yin, Stephen M. Griffies, and Raphael Dussin
Geosci. Model Dev., 14, 2471–2502,Short summary
The new surface forcing from JRA55-do (OMIP II) significantly improved the underestimated sea level trend across the entire Pacific Ocean along 10° N in the simulation forced by CORE (OMIP I). We summarize and list out the reasons for the existing sea level biases across all studied timescales as a reference for improving the sea level simulation in the future. This study on the evaluation and improvement of ocean climate models should be of broad interest to a large modeling community.
Oliver Gutjahr, Nils Brüggemann, Helmuth Haak, Johann H. Jungclaus, Dian A. Putrasahan, Katja Lohmann, and Jin-Song von Storch
Geosci. Model Dev., 14, 2317–2349,Short summary
We compare four ocean vertical mixing schemes in 100-year coupled simulations with the Max Planck Institute Earth System Model (MPI-ESM1.2) and analyse their model biases. Overall, the mixing schemes modify biases in the ocean interior that vary with region and variable but produce a similar global bias pattern. We therefore cannot classify any scheme as superior but conclude that the chosen mixing scheme may be important for regional biases.
Katsumi Matsumoto, Tatsuro Tanioka, and Jacob Zahn
Geosci. Model Dev., 14, 2265–2288,Short summary
MESMO is a mathematical model that represents the essential components of the Earth, such as the global ocean, atmosphere, and sea ice. It is used to study the global climate and the global carbon cycle. We describe the third version of MESMO. A novel feature of the new version is its mathematical representations of the chemical composition of marine phytoplankton and the marine dissolved organic matter, which are both recognized as important for the global ocean carbon cycle.
Lojze Žust, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev., 14, 2057–2074,Short summary
Adriatic basin sea level modelling is a challenging problem due to the interplay between terrain, weather, tides and seiches. Current state-of-the-art numerical models (e.g. NEMO) require large computational resources to produce reliable forecasts. In this study we propose HIDRA, a novel deep learning approach for sea level modeling, which drastically reduces the numerical cost while demonstrating predictive capabilities comparable to that of the NEMO model, outperforming it in many instances.
Qing Li and Luke Van Roekel
Geosci. Model Dev., 14, 2011–2028,Short summary
Physical processes in the ocean span multiple spatial and temporal scales. Simultaneously resolving all these in a simulation is computationally challenging. Here we develop a more efficient technique to better study the interactions across scales, particularly focusing on the ocean surface turbulent mixing, by coupling a global ocean circulation model MPAS-Ocean and a large eddy simulation model PALM. The latter is customized and ported on a GPU to further accelerate the computation.
Yang Feng, Dimitris Menemenlis, Huijie Xue, Hong Zhang, Dustin Carroll, Yan Du, and Hui Wu
Geosci. Model Dev., 14, 1801–1819,Short summary
Simulation of coastal plume regions was improved in global ECCOv4 with a series of sensitivity tests. We find modeled SSS is closer to SMAP when using daily point-source runoff as well as increasing the resolution from coarse to intermediate. The plume characteristics, freshwater transport, and critical water properties are modified greatly. But this may not happen with a further increase to high resolution. The study will advance the seamless modeling of land–ocean–atmosphere feedback in ESMs.
Gregory C. Smith, Yimin Liu, Mounir Benkiran, Kamel Chikhar, Dorina Surcel Colan, Audrey-Anne Gauthier, Charles-Emmanuel Testut, Frederic Dupont, Ji Lei, François Roy, Jean-François Lemieux, and Fraser Davidson
Geosci. Model Dev., 14, 1445–1467,Short summary
Canada's coastlines include diverse ocean environments. In response to the strong need to support marine activities and security, we present the first pan-Canadian operational regional ocean analysis system. A novel online tidal harmonic analysis method is introduced that uses a sliding-window approach. Innovations are compared to those from the Canadian global analysis system. Particular improvements are found near the Gulf Stream due to the higher model grid resolution.
Ai, B., Jia, M., Xu, H., Xu, J., Wen, Z., Li, B., and Zhang, D.: Coverage path planning for maritime search and rescue using reinforcement learning, Ocean Eng., 241, 110098, https://doi.org/10.1016/j.oceaneng.2021.110098, 2021.
Banas, N. S., McDonald, P. S., and Armstrong, D. A.: Green Crab Larval Retention in Willapa Bay, Washington: An Intensive Lagrangian Modeling Approach, Estuar. Coast., 32, 893–905, https://doi.org/10.1007/s12237-009-9175-7, 2009.
Beegle-Krause, J.: General Noaa Oil Modeling Environment (Gnome): A New Spill Trajectory Model, International Oil Spill Conference Proceedings, 2001, 865–871, https://doi.org/10.7901/2169-3358-2001-2-865, 2001.
Beron-Vera, F. J. and LaCasce, J. H.: Statistics of Simulated and Observed Pair Separations in the Gulf of Mexico, J. Phys. Oceanogr., 46, 2183–2199, https://doi.org/10.1175/JPO-D-15-0127.1, 2016.
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.-Oceans, 104, 7649–7666, https://doi.org/10.1029/98jc02622, 1999.
Cassiani, M., Stohl, A., Olivié, D., Seland, Ø., Bethke, I., Pisso, I., and Iversen, T.: The offline Lagrangian particle model FLEXPART–NorESM/CAM (v1): model description and comparisons with the online NorESM transport scheme and with the reference FLEXPART model, Geosci. Model Dev., 9, 4029–4048, https://doi.org/10.5194/gmd-9-4029-2016, 2016.
Chu, P. C., Ivanov, L. M., Kantha, L. H., Margolina, T. M., Melnichenko, O. V., and Poberezhny, Y. A.: Lagrangian predictability of high-resolution regional models: the special case of the Gulf of Mexico, Nonlin. Processes Geophys., 11, 47–66, https://doi.org/10.5194/npg-11-47-2004, 2004.
Clark, S., Hubbard, K. A., McGillicuddy, D. J., Ralston, D. K., and Shankar, S.: Investigating Pseudo-nitzschia australis introduction to the Gulf of Maine with observations and models, Cont. Shelf Res., 228, 104493, https://doi.org/10.1016/j.csr.2021.104493, 2021.
Dagestad, K.-F., Röhrs, J., Breivik, Ø., and Ådlandsvik, B.: OpenDrift v1.0: a generic framework for trajectory modelling, Geosci. Model Dev., 11, 1405–1420, https://doi.org/10.5194/gmd-11-1405-2018, 2018.
Döös, K., Jönsson, B., and Kjellsson, J.: Evaluation of oceanic and atmospheric trajectory schemes in the TRACMASS trajectory model v6.0, Geosci. Model Dev., 10, 1733–1749, https://doi.org/10.5194/gmd-10-1733-2017, 2017.
Drévillon, M., Bourdallé-Badie, R., Derval, C., Lellouche, J. M., Rémy, E., Tranchant, B., Benkiran, M., Greiner, E., Guinehut, S., Verbrugge, N., Garric, G., Testut, C. E., Laborie, M., Nouel, L., Bahurel, P., Bricaud, C., Crosnier, L., Dombrowsky, E., Durand, E., Ferry, N., Hernandez, F., Le Galloudec, O., Messal, F., and Parent, L.: The GODAE/Mercator-Ocean global ocean forecasting system: results, applications and prospects, J. Oper. Oceanogr., 1, 51–57, https://doi.org/10.1080/1755876x.2008.11020095, 2014.
Egbert, G. D. and Erofeeva, S. Y.: Efficient Inverse Modeling of Barotropic Ocean Tides, J. Atmos. Ocean. Tech., 19, 183–204, https://doi.org/10.1175/1520-0426(2002)019<0183:Eimobo>2.0.Co;2, 2002.
Feng, M., Caputi, N., Penn, J., Slawinski, D., de Lestang, S., Weller, E., Pearce, A., and Brickman, D.: Ocean circulation, Stokes drift, and connectivity of western rock lobster (Panulirus cygnus) population, Can. J. Fish. Aquat. Sci., 68, 1182–1196, https://doi.org/10.1139/f2011-065, 2011.
Fuchs, H. L., Gerbi, G. P., Hunter, E. J., and Christman, A. J.: Waves cue distinct behaviors and differentiate transport of congeneric snail larvae from sheltered versus wavy habitats, P. Natl. Acad. Sci. USA, 115, E7532–E7540, https://doi.org/10.1073/pnas.1804558115, 2018.
Garvine, R. W.: Subtidal frequency estuary-shelf interaction: Observations near Delaware Bay, J. Geophys. Res., 96, 7049–7064, https://doi.org/10.1029/91jc00079, 1991.
Garwood, J. C., Fuchs, H. L., Gerbi, G. P., Hunter, E. J., Chant, R. J., and Wilkin, J. L.: Estuarine retention of larvae: Contrasting effects of behavioral responses to turbulence and waves, Limnol. Oceanogr., 67, 992–1005, https://doi.org/10.1002/lno.12052, 2022.
Gerbi, G. P., Kastner, S. E., and Brett, G.: The Role of Whitecapping in Thickening the Ocean Surface Boundary Layer, J. Phys. Oceanogr., 45, 2006–2024, https://doi.org/10.1175/JPO-D-14-0234.1, 2015.
Gerbi, G. P., Hunter, E., Wilkin, J. L., Chant, R., Fuchs, H. L., and Garwood, J. C.: SWAN configuration of a nested model of the Mid-Atlantic Bight and Delaware Bay, Zenodo [data set], https://doi.org/10.5281/zenodo.6081147, 2022a.
Gerbi, G. P., Hunter, E., Wilkin, J. L., Chant, R., Fuchs, H. L., and Garwood, J. C.: ROMS configuration of a two-way nested model of the Mid-Atlantic Bight and Delaware Bay, Zenodo [data set], https://doi.org/10.5281/zenodo.6090300, 2022b.
Haidvogel, D. B., Arango, H. G., Hedstrom, K., Beckmann, A., Malanotte-Rizzoli, P., and Shchepetkin, A. F.: Model evaluation experiments in the North Atlantic Basin: simulations in nonlinear terrain-following coordinates, Dynam. Atmos. Oceans, 32, 239–281, https://doi.org/10.1016/s0377-0265(00)00049-x, 2000.
Hunter, E. J.: ROMSPath First Release (v1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.4457931, 2021a.
Hunter, E.: ROMSPath Second Release (v1.0.1), Zenodo [code], https://doi.org/10.5281/zenodo.5597732, 2021b.
Hunter, J. R., Craig, P. D., and Phillips, H. E.: On the use of random walk models with spatially variable diffusivity, J. Comput. Phys., 106, 366–376, https://doi.org/10.1016/S0021-9991(83)71114-9, 1993.
Janjic, Z., Black, T., Pyle, M., Rogers, E., Chuang, H. Y., and DiMego, G.: High resolution applications of the WRF NMM, 21st Conference onWeather Analysis and Forecasting/17th Conference on Numerical Weather Prediction, Washington DC, 5 August 2005, Abstract 16A.4, 2005.
Kumar, N. and Feddersen, F.: The Effect of Stokes Drift and Transient Rip Currents on the Inner Shelf. Part II: With Stratification, J. Phys. Oceanogr., 47, 243–260, https://doi.org/10.1175/jpo-d-16-0077.1, 2017a.
Kumar, N. and Feddersen, F.: The Effect of Stokes Drift and Transient Rip Currents on the Inner Shelf. Part I: No Stratification, J. Phys. Oceanogr., 47, 227–241, https://doi.org/10.1175/jpo-d-16-0076.1, 2017b.
LaCasce, J. H.: Statistics from Lagrangian observations, Prog. Oceanogr., 77, 1–29, https://doi.org/10.1016/j.pocean.2008.02.002, 2008.
Lange, M. and van Sebille, E.: Parcels v0.9: prototyping a Lagrangian ocean analysis framework for the petascale age, Geosci. Model Dev., 10, 4175–4186, https://doi.org/10.5194/gmd-10-4175-2017, 2017.
Lellouche, J.-M., Greiner, E., Le Galloudec, O., Garric, G., Regnier, C., Drevillon, M., Benkiran, M., Testut, C.-E., Bourdalle-Badie, R., Gasparin, F., Hernandez, O., Levier, B., Drillet, Y., Remy, E., and Le Traon, P.-Y.: Recent updates to the Copernicus Marine Service global ocean monitoring and forecasting real-time ∘ high-resolution system, Ocean Sci., 14, 1093–1126, https://doi.org/10.5194/os-14-1093-2018, 2018.
Lett, C., Verley, P., Mullon, C., Parada, C., Brochier, T., Penven, P., and Blanke, B.: A Lagrangian tool for modelling ichthyoplankton dynamics, Environ. Modell. Softw., 23, 1210–1214, https://doi.org/10.1016/j.envsoft.2008.02.005, 2008.
Levin, J., Arango, H. G., Laughlin, B., Wilkin, J., and Moore, A. M.: The impact of remote sensing observations on cross-shelf transport estimates from 4D-Var analyses of the Mid-Atlantic Bight, Adv. Space Res., 68, 553–570, https://doi.org/10.1016/j.asr.2019.09.012, 2019.
Liubartseva, S., Coppini, G., Lecci, R., and Clementi, E.: Tracking plastics in the Mediterranean: 2D Lagrangian model, Mar. Pollut. Bull., 129, 151–162, https://doi.org/10.1016/j.marpolbul.2018.02.019, 2018.
López, A. G., Wilkin, J. L., and Levin, J. C.: Doppio – a ROMS (v3.6)-based circulation model for the Mid-Atlantic Bight and Gulf of Maine: configuration and comparison to integrated coastal observing network observations, Geosci. Model Dev., 13, 3709–3729, https://doi.org/10.5194/gmd-13-3709-2020, 2020.
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for geophysical fluid problems, Rev. Geophys., 20, 851–875, https://doi.org/10.1029/RG020i004p00851, 1982.
Mesinger, F., DiMego, G., Kalnay, E., Mitchell, K., Shafran, P. C., Ebisuzaki, W., Jović, D., Woollen, J., Rogers, E., Berbery, E. H., Ek, M. B., Fan, Y., Grumbine, R., Higgins, W., Li, H., Lin, Y., Manikin, G., Parrish, D., and Shi, W.: North American Regional Reanalysis, B. Am. Meteorol. Soc., 87, 343–360, https://doi.org/10.1175/bams-87-3-343, 2006.
Monismith, S. G. and Fong, D. A.: A note on the potential transport of scalars and organisms by surface waves, Limnol. Oceanogr., 49, 1214–1217, https://doi.org/10.4319/lo.2004.49.4.1214, 2004.
North, E., Schlag, Z., Hood, R., Li, M., Zhong, L., Gross, T., and Kennedy, V.: Vertical swimming behavior influences the dispersal of simulated oyster larvae in a coupled particle-tracking and hydrodynamic model of Chesapeake Bay, Mar. Ecol. Prog. Ser., 359, 99–115, https://doi.org/10.3354/meps07317, 2008.
Pareja-Roman, L. F., Chant, R. J., and Ralston, D. K.: Effects of Locally Generated Wind Waves on the Momentum Budget and Subtidal Exchange in a Coastal Plain Estuary, J. Geophys. Res.-Oceans, 124, 1005–1028, https://doi.org/10.1029/2018JC014585, 2019.
Phillips, O. M.: The Dynamics of the Upper Ocean, 2nd edn., Cambridge University Press, ISBN 10 0521298016, ISBN 13 9780521298018, 1966.
Pratt, L. J., Rypina, I. I., Pullen, J., Levin, J., and Gordon, A. L.: Chaotic Advection in an Archipelago, J. Phys. Oceanogr., 40, 1988–2006, https://doi.org/10.1175/2010jpo4336.1, 2010.
Révelard, A., Reyes, E., Mourre, B., Hernández-Carrasco, I., Rubio, A., Lorente, P., Fernández, C. D. L., Mader, J., Álvarez-Fanjul, E., and Tintoré, J.: Sensitivity of Skill Score Metric to Validate Lagrangian Simulations in Coastal Areas: Recommendations for Search and Rescue Applications, Frontiers in Marine Science, 8, 191, https://doi.org/10.3389/fmars.2021.630388, 2021.
Ris, R. C., Holthuijsen, L. H., and Booij, N.: A third-generation wave model for coastal regions: 2. Verification, J. Geophys. Res.-Oceans, 104, 7667–7681, https://doi.org/10.1029/1998jc900123, 1999.
Röhrs, J., Christensen, K. H., Hole, L. R., Broström, G., Drivdal, M., and Sundby, S.: Observation-based evaluation of surface wave effects on currents and trajectory forecasts, Ocean Dynam., 62, 1519–1533, https://doi.org/10.1007/s10236-012-0576-y, 2012.
Rypina, I. I., Scott, S. E., Pratt, L. J., and Brown, M. G.: Investigating the connection between complexity of isolated trajectories and Lagrangian coherent structures, Nonlin. Processes Geophys., 18, 977–987, https://doi.org/10.5194/npg-18-977-2011, 2011.
Schlag, Z. R. and North, E. W.: Lagrangian TRANSport model (LTRANS v.2) User’s Guide, University of Maryland Center for Environmental Science, Horn Point Laboratory, Cambridge, MD, 183 pp., https://northweb.hpl.umces.edu/LTRANS/LTRANS-v2/LTRANSv2_UsersGuide_6Jan12.pdf (last access: 25 May 2022), 2012.
Shadden, S. C., Lekien, F., and Marsden, J. E.: Definition and properties of Lagrangian coherent structures from finite-time Lyapunov exponents in two-dimensional aperiodic flows, Physica D, 212, 271–304, https://doi.org/10.1016/j.physd.2005.10.007, 2005.
Simons, R. D., Siegel, D. A., and Brown, K. S.: Model sensitivity and robustness in the estimation of larval transport: A study of particle tracking parameters, J. Marine Syst., 119–120, 19–29, https://doi.org/10.1016/j.jmarsys.2013.03.004, 2013.
Spall, M. A. and Holland, W. R.: A Nested Primitive Equation Model for Oceanic Applications, J. Phys. Oceanogr., 21, 205–220, https://doi.org/10.1175/1520-0485(1991)021<0205:Anpemf>2.0.Co;2, 1991.
Thomson, J., Schwendeman, M. S., Zippel, S. F., Moghimi, S., Gemmrich, J., and Rogers, W. E.: Wave-Breaking Turbulence in the Ocean Surface Layer, J. Phys. Oceanogr., 46, 1857–1870, https://doi.org/10.1175/jpo-d-15-0130.1, 2016.
Tolman, H. L.: User manual and system documentation of WAVEWATCH III ™ version 3.14, Technical note, MMAB Contribution, 276, https://polar.ncep.noaa.gov/mmab/papers/tn276/MMAB_276.pdf (last access: 25 May 2022), 2009.
Umlauf, L. and Burchard, H.: A generic length-scale equation for geophysical turbulence models, J. Mar. Res., 61, 235–265, https://doi.org/10.1357/002224003322005087, 2003.
van den Bremer, T. S. and Breivik, Ø.: Stokes drift, Philos. T. R. Soc. A, 376, 20170104, https://doi.org/10.1098/rsta.2017.0104, 2018.
van Sebille, E., Griffies, S. M., Abernathey, R., Adams, T. P., Berloff, P., Biastoch, A., Blanke, B., Chassignet, E. P., Cheng, Y., Cotter, C. J., Deleersnijder, E., Döös, K., Drake, H. F., Drijfhout, S., Gary, S. F., Heemink, A. W., Kjellsson, J., Koszalka, I. M., Lange, M., Lique, C., MacGilchrist, G. A., Marsh, R., Mayorga Adame, C. G., McAdam, R., Nencioli, F., Paris, C. B., Piggott, M. D., Polton, J. A., Rühs, S., Shah, S. H. A. M., Thomas, M. D., Wang, J., Wolfram, P. J., Zanna, L., and Zika, J. D.: Lagrangian ocean analysis: Fundamentals and practices, Ocean Model., 121, 49–75, https://doi.org/10.1016/j.ocemod.2017.11.008, 2018.
Vennell, R., Scheel, M., Weppe, S., Knight, B., and Smeaton, M.: Fast lagrangian particle tracking in unstructured ocean model grids, Ocean Dynam., 71, 423–437, https://doi.org/10.1007/s10236-020-01436-7, 2021.
Visser, A.: Using random walk models to simulate the vertical distribution of particles in a turbulent water column, Mar. Ecol. Prog. Ser., 158, 275–281, https://doi.org/10.3354/meps158275, 1997.
Wagner, P., Rühs, S., Schwarzkopf, F. U., Koszalka, I. M., and Biastoch, A.: Can Lagrangian Tracking Simulate Tracer Spreading in a High-Resolution Ocean General Circulation Model?, J. Phys. Oceanogr., 49, 1141–1157, https://doi.org/10.1175/jpo-d-18-0152.1, 2019.
Warner, J. C., Defne, Z., Haas, K., and Arango, H. G.: A wetting and drying scheme for ROMS, Comput. Geosci., 58, 54–61, https://doi.org/10.1016/j.cageo.2013.05.004, 2013.
Warner, J. C., Schwab, W. C., List, J. H., Safak, I., Liste, M., and Baldwin, W.: Inner-shelf ocean dynamics and seafloor morphologic changes during Hurricane Sandy, Cont. Shelf Res., 138, 1–18, https://doi.org/10.1016/j.csr.2017.02.003, 2017.
Wilkin, J. and Levin, J.: Outputs from a Regional Ocean Modeling System (ROMS) data assimilative reanalysis (version DopAnV2R3-ini2007) of ocean circulation in the Mid-Atlantic Bight and Gulf of Maine for 2007–2020, SEANOE [data set], https://doi.org/10.17882/86286, 2021.
Wilkin, J., Levin, J., Lopez, A., Hunter, E., Zavala-Garay, J., and Arango, H.: Coastal Ocean Forecast System for the US Mid‐Atlantic Bight and Gulf of Maine, New Frontiers in Operational Oceanography, 593–624, https://diginole.lib.fsu.edu/islandora/object/fsu:602474 (last access: 30 May 2022), 2018.
Xue, H., Incze, L., Xu, D., Wolff, N., and Pettigrew, N.: Connectivity of lobster populations in the coastal Gulf of Maine, Ecol. Model., 210, 193–211, https://doi.org/10.1016/j.ecolmodel.2007.07.024, 2008.
Yeung, P. K.: Lagrangian investigations of turbulence, Annu. Rev. Fluid Mech., 34, 115–142, https://doi.org/10.1146/annurev.fluid.34.082101.170725, 2002.
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.
ROMSPath is an offline particle tracking model tailored for use with output from Regional Ocean...