Articles | Volume 17, issue 6
https://doi.org/10.5194/gmd-17-2221-2024
© Author(s) 2024. 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-17-2221-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
19 Mar 2024
Model description paper |
| 19 Mar 2024
| 19 Mar 2024
LOCATE v1.0: numerical modelling of floating marine debris dispersion in coastal regions using Parcels v2.4.2
Departament d'Enginyeria Civil i Ambiental (DECA), Laboratori d'Enginyeria Marítima (LIM), Universitat Politècnica de Catalunya – BarcelonaTech (UPC), C. Jordi Girona, 1–3, Barcelona, 08034, Catalunya, Spain
Leidy M. Castro-Rosero
Departament d'Enginyeria Civil i Ambiental (DECA), Laboratori d'Enginyeria Marítima (LIM), Universitat Politècnica de Catalunya – BarcelonaTech (UPC), C. Jordi Girona, 1–3, Barcelona, 08034, Catalunya, Spain
Facultat de Ciències de la Terra, Universitat de Barcelona, Avinguda C. de Martí i Franquès, s/n, Barcelona, 08028, Catalunya, Spain
Manuel Espino
Departament d'Enginyeria Civil i Ambiental (DECA), Laboratori d'Enginyeria Marítima (LIM), Universitat Politècnica de Catalunya – BarcelonaTech (UPC), C. Jordi Girona, 1–3, Barcelona, 08034, Catalunya, Spain
Jose M. Alsina Torrent
CORRESPONDING AUTHOR
Departament d'Enginyeria Civil i Ambiental (DECA), Laboratori d'Enginyeria Marítima (LIM), Universitat Politècnica de Catalunya – BarcelonaTech (UPC), C. Jordi Girona, 1–3, Barcelona, 08034, Catalunya, Spain
Departament d'Enginyeria Gràfica i de Disseny, Universitat Politècnica de Catalunya – BarcelonaTech (UPC), Avinguda Diagonal 647, Barcelona, 08034, Catalunya, Spain
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Xavier Sánchez-Artús, Vicente Gracia, Manuel Espino, Manel Grifoll, Gonzalo Simarro, Jorge Guillén, Marta González, and Agustín Sanchez-Arcilla
EGUsphere, https://doi.org/10.5194/egusphere-2024-3373, https://doi.org/10.5194/egusphere-2024-3373, 2024
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The study presents an operational service that forecasts flood impacts during extreme conditions at three beaches in Barcelona, Spain. The architecture is designed for efficient use on standard desktop computers, using data from the Copernicus Marine Environment Monitoring Service, task automation tools, Python scripts, and the XBeach model to deliver timely results. Extensive validation, including field campaigns and video analysis, ensures accuracy and reliability.
Jiangyue Jin, Manuel Espino, Daniel Fernández, and Albert Folch
EGUsphere, https://doi.org/10.5194/egusphere-2024-3384, https://doi.org/10.5194/egusphere-2024-3384, 2024
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Coastal zones are crucial ecological areas, yet our understanding of groundwater-ocean interactions remains limited. Ocean and groundwater models typically operate independently, with ocean models ignoring submarine groundwater discharge and groundwater models viewing the ocean as a static boundary. This separation impedes accurate simulations. By integrating these models, we can capture real-time water flow and salt movement while considering factors such as tides.
Marta F.-Pedrera Balsells, Manel Grifoll, Margarita Fernández-Tejedor, Manuel Espino, Marc Mestres, and Agustín Sánchez-Arcilla
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-322, https://doi.org/10.5194/bg-2021-322, 2021
Revised manuscript not accepted
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Phytoplankton in coastal bays is influenced by physical variables (wind or freshwater inputs) that can influence the composition of phytoplankton. A numerical model has been applied to understand this variability. The simulations show that during weak wind events there is physical separation between surface and deep layers, penalising phytoplankton growth. During intense wind, mixing of the water column occurs, increasing the phytoplankton biomass in the lower layers.
Manel Grifoll, Pablo Cerralbo, Jorge Guillén, Manuel Espino, Lars Boye Hansen, and Agustín Sánchez-Arcilla
Ocean Sci., 15, 307–319, https://doi.org/10.5194/os-15-307-2019, https://doi.org/10.5194/os-15-307-2019, 2019
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In this paper we investigate the origin of the variability in
near-bottom turbidity observations in Alfacs Bay (in the northwestern Mediterranean Sea). The observations of turbidity peaks are consistent with the seiche phenomenon. We suggest that the sequence of resuspension events plays an important role in the suspended sediment concentration, meaning that previous sediment resuspension events may influence the increase in suspended sediment in subsequent events.
Pablo Cerralbo, Marta F.-Pedrera Balsells, Marc Mestres, Margarita Fernandez, Manuel Espino, Manel Grifoll, and Agustin Sanchez-Arcilla
Ocean Sci., 15, 215–226, https://doi.org/10.5194/os-15-215-2019, https://doi.org/10.5194/os-15-215-2019, 2019
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In this contribution we investigate the hydrodynamic response in Alfacs Bay (Delta Ebro, NW Mediterranean Sea) to freshwater flows and inner bay to open sea connections. The numerical model ROMS is applied nested to Copernicus models and validated with in situ data. Considering the results, only the modification of freshwater flows is recommended due to its lower impact on the environment and associated economic costs. None of the proposed solutions solve the problem related to warm waters.
Laura Ràfols, Manel Grifoll, and Manuel Espino
Ocean Sci., 15, 1–20, https://doi.org/10.5194/os-15-1-2019, https://doi.org/10.5194/os-15-1-2019, 2019
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This study investigates the effects of the wave–current interactions in a region where episodes of strong cross-shelf wind occur. To do so, a coupled system between two numerical models has been implemented. The results do not show substantial differences in the water current patterns, but a clear effect on the water column stratification has been found. Additionally, stronger impact is observed for the wave period rather than the wave height.
Manel Grifoll, Jorge Navarro, Elena Pallares, Laura Ràfols, Manuel Espino, and Ana Palomares
Nonlin. Processes Geophys., 23, 143–158, https://doi.org/10.5194/npg-23-143-2016, https://doi.org/10.5194/npg-23-143-2016, 2016
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In this contribution the wind jet dynamics in the northern margin of the Ebro River shelf (NW Mediterranean Sea) are investigated using coupled numerical models. The study area is characterized by persistent and energetic offshore winds during autumn and winter. However, the coupling effect in the wind resource assessment may be relevant due to the cubic relation between the wind intensity and power.
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
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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.
P. Cerralbo, M. Grifoll, J. Moré, M. Bravo, A. Sairouní Afif, and M. Espino
Adv. Sci. Res., 12, 11–21, https://doi.org/10.5194/asr-12-11-2015, https://doi.org/10.5194/asr-12-11-2015, 2015
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Wind spatial heterogeneity in a coastal area (Alfacs Bay, northwestern Mediterranean Sea) is described using a set of observations and modelling results. Observations during 2012–2013 reveal that both N–NW winds and sea breezes appear to be affected by the local orography promoting high wind variability in relatively short spatial scales. The importance of wind models’ spatial resolution is also assessed and used to describe the spatial variability of the typical winds in the region.
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Jan D. Zika and Taimoor Sohail
Geosci. Model Dev., 17, 8049–8068, https://doi.org/10.5194/gmd-17-8049-2024, https://doi.org/10.5194/gmd-17-8049-2024, 2024
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We describe a method to relate fluxes of heat and freshwater at the sea surface to the resulting distribution of seawater among categories such as warm and salty or cold and salty. The method exploits the laws that govern how heat and salt change when water mixes. The method will allow the climate community to improve estimates of how much heat the ocean is absorbing and how rainfall and evaporation are changing across the globe.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
Geosci. Model Dev., 17, 7347–7364, https://doi.org/10.5194/gmd-17-7347-2024, https://doi.org/10.5194/gmd-17-7347-2024, 2024
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Monitoring the ocean is essential for studying marine life and human impact. Our new software, PPCon, uses ocean data to predict key factors like nitrate and chlorophyll levels, which are hard to measure directly. By leveraging machine learning, PPCon offers more accurate and efficient predictions.
Jan De Rydt, Nicolas C. Jourdain, Yoshihiro Nakayama, Mathias van Caspel, Ralph Timmermann, Pierre Mathiot, Xylar S. Asay-Davis, Hélène Seroussi, Pierre Dutrieux, Ben Galton-Fenzi, David Holland, and Ronja Reese
Geosci. Model Dev., 17, 7105–7139, https://doi.org/10.5194/gmd-17-7105-2024, https://doi.org/10.5194/gmd-17-7105-2024, 2024
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Global climate models do not reliably simulate sea-level change due to ice-sheet–ocean interactions. We propose a community modelling effort to conduct a series of well-defined experiments to compare models with observations and study how models respond to a range of perturbations in climate and ice-sheet geometry. The second Marine Ice Sheet–Ocean Model Intercomparison Project will continue to lay the groundwork for including ice-sheet–ocean interactions in global-scale IPCC-class models.
Qian Wang, Yang Zhang, Fei Chai, Y. Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev., 17, 7067–7081, https://doi.org/10.5194/gmd-17-7067-2024, https://doi.org/10.5194/gmd-17-7067-2024, 2024
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We coupled an unstructured hydro-model with an advanced column sea ice model to meet the growing demand for increased resolution and complexity in unstructured sea ice models. Additionally, we present a novel tracer transport scheme for the sea ice coupled model and demonstrate that this scheme fulfills the requirements for conservation, accuracy, efficiency, and monotonicity in an idealized test. Our new coupled model also has good performance in realistic tests.
Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud
Geosci. Model Dev., 17, 6967–6986, https://doi.org/10.5194/gmd-17-6967-2024, https://doi.org/10.5194/gmd-17-6967-2024, 2024
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Mixing is a crucial aspect of the ocean, but its accurate representation in computer simulations is made challenging by errors that result in unwanted mixing, compromising simulation realism. Here we illustrate the spurious effect that tides can have on simulations of south-east Asia. Although they play an important role in determining the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. We also provide insights into how to reduce these errors.
Mohamed Ayache, Jean-Claude Dutay, Anne Mouchet, Kazuyo Tachikawa, Camille Risi, and Gilles Ramstein
Geosci. Model Dev., 17, 6627–6655, https://doi.org/10.5194/gmd-17-6627-2024, https://doi.org/10.5194/gmd-17-6627-2024, 2024
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Water isotopes (δ18O, δD) are one of the most widely used proxies in ocean climate research. Previous studies using water isotope observations and modelling have highlighted the importance of understanding spatial and temporal isotopic variability for a quantitative interpretation of these tracers. Here we present the first results of a high-resolution regional dynamical model (at 1/12° horizontal resolution) developed for the Mediterranean Sea, one of the hotspots of ongoing climate change.
Cara Nissen, Nicole S. Lovenduski, Mathew Maltrud, Alison R. Gray, Yohei Takano, Kristen Falcinelli, Jade Sauvé, and Katherine Smith
Geosci. Model Dev., 17, 6415–6435, https://doi.org/10.5194/gmd-17-6415-2024, https://doi.org/10.5194/gmd-17-6415-2024, 2024
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Autonomous profiling floats have provided unprecedented observational coverage of the global ocean, but uncertainties remain about whether their sampling frequency and density capture the true spatiotemporal variability of physical, biogeochemical, and biological properties. Here, we present the novel synthetic biogeochemical float capabilities of the Energy Exascale Earth System Model version 2 and demonstrate their utility as a test bed to address these uncertainties.
Ye Yuan, Fujiang Yu, Zhi Chen, Xueding Li, Fang Hou, Yuanyong Gao, Zhiyi Gao, and Renbo Pang
Geosci. Model Dev., 17, 6123–6136, https://doi.org/10.5194/gmd-17-6123-2024, https://doi.org/10.5194/gmd-17-6123-2024, 2024
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Accurate and timely forecasting of ocean waves is of great importance to the safety of marine transportation and offshore engineering. In this study, GPU-accelerated computing is introduced in WAve Modeling Cycle 6 (WAM6). With this effort, global high-resolution wave simulations can now run on GPUs up to tens of times faster than the currently available models can on a CPU node with results that are just as accurate.
Krysten Rutherford, Laura Bianucci, and William Floyd
Geosci. Model Dev., 17, 6083–6104, https://doi.org/10.5194/gmd-17-6083-2024, https://doi.org/10.5194/gmd-17-6083-2024, 2024
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Nearshore ocean models often lack complete information about freshwater fluxes due to numerous ungauged rivers and streams. We tested a simple rain-based hydrological model as inputs into an ocean model of Quatsino Sound, Canada, with the aim of improving the representation of the land–ocean connection in the nearshore model. Through multiple tests, we found that the performance of the ocean model improved when providing 60 % or more of the freshwater inputs from the simple runoff model.
Neill Mackay, Taimoor Sohail, Jan David Zika, Richard G. Williams, Oliver Andrews, and Andrew James Watson
Geosci. Model Dev., 17, 5987–6005, https://doi.org/10.5194/gmd-17-5987-2024, https://doi.org/10.5194/gmd-17-5987-2024, 2024
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The ocean absorbs carbon dioxide from the atmosphere, mitigating climate change, but estimates of the uptake do not always agree. There is a need to reconcile these differing estimates and to improve our understanding of ocean carbon uptake. We present a new method for estimating ocean carbon uptake and test it with model data. The method effectively diagnoses the ocean carbon uptake from limited data and therefore shows promise for reconciling different observational estimates.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 17, 5851–5882, https://doi.org/10.5194/gmd-17-5851-2024, https://doi.org/10.5194/gmd-17-5851-2024, 2024
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The carbonate system is typically studied using measurements, but modeling can contribute valuable insights. Using a biogeochemical model, we propose a new representation of total alkalinity, dissolved inorganic carbon, pCO2, and pH in a highly dynamic Mediterranean coastal area, the Bay of Marseille, a useful addition to measurements. Through a detailed analysis of pCO2 and air–sea CO2 fluxes, we show that variations are strongly impacted by the hydrodynamic processes that affect the bay.
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
EGUsphere, https://doi.org/10.5194/egusphere-2024-1372, https://doi.org/10.5194/egusphere-2024-1372, 2024
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We developed a modelling system of the northwest Atlantic Ocean that simulates the currents, temperature, salinity, and parts of the biochemical cycle of the ocean, as well as sea ice. The system combines advanced, open-source models and can be used to study, for example, the oceans’ capture of atmospheric carbon dioxide which is a key process in the global climate. The system produces realistic results, and we use it to investigate the roles of tides and sea ice in the northwest Atlantic Ocean.
Xuanxuan Gao, Shuiqing Li, Dongxue Mo, Yahao Liu, and Po Hu
Geosci. Model Dev., 17, 5497–5509, https://doi.org/10.5194/gmd-17-5497-2024, https://doi.org/10.5194/gmd-17-5497-2024, 2024
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Storm surges generate coastal inundation and expose populations and properties to danger. We developed a novel storm surge inundation model for efficient prediction. Estimates compare well with in situ measurements and results from a numerical model. The new model is a significant improvement on existing numerical models, with much higher computational efficiency and stability, which allows timely disaster prevention and mitigation.
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024, https://doi.org/10.5194/gmd-17-5145-2024, 2024
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This study explores methods to reconstruct diurnal variations in skin sea surface temperature in a model of the Mediterranean Sea. Our new approach, considering chlorophyll concentration, enhances spatial and temporal variations in the warm layer. Comparative analysis shows context-dependent improvements. The proposed "chlorophyll-interactive" method brings the surface net total heat flux closer to zero annually, despite a net heat loss from the ocean to the atmosphere.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
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We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024, https://doi.org/10.5194/gmd-17-4603-2024, 2024
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Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data are complicated by the distortion of the used modelling grids and the large number of different grid types. We present two new methods that allow the calculation of oceanic fluxes of volume, heat, salinity, and ice through almost arbitrary sections for various models and reanalyses that are independent of the used modelling grids.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024, https://doi.org/10.5194/gmd-17-4095-2024, 2024
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Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356, https://doi.org/10.5194/gmd-17-3341-2024, https://doi.org/10.5194/gmd-17-3341-2024, 2024
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The new offline particle tracking package, Tracker v1.1, is introduced to the Regional Ocean Modeling System, featuring an efficient nearest-neighbor algorithm to enhance particle-tracking speed. Its performance was evaluated against four other tracking packages and passive dye. Despite unique features, all packages yield comparable results. Running multiple packages within the same circulation model allows comparison of their performance and ease of use.
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173, https://doi.org/10.5194/gmd-17-3157-2024, https://doi.org/10.5194/gmd-17-3157-2024, 2024
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In order to improve Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher-resolution ocean currents. To this goal a 3 km resolution regional ocean model has been developed. Its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation was found to be quite realistic.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
Geosci. Model Dev., 17, 2829–2853, https://doi.org/10.5194/gmd-17-2829-2024, https://doi.org/10.5194/gmd-17-2829-2024, 2024
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Here a new method of modelling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean currents and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave–current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
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Ocean forecasting relies on the combination of numerical models and ocean observations through data assimilation (DA). Here we assess the performance of two DA systems in a dynamic western boundary current, the East Australian Current, across a common modelling and observational framework. We show that the more advanced, time-dependent method outperforms the time-independent method for forecast horizons of 5 d. This advocates the use of advanced methods for highly variable oceanic regions.
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
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A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
Geosci. Model Dev., 17, 1749–1764, https://doi.org/10.5194/gmd-17-1749-2024, https://doi.org/10.5194/gmd-17-1749-2024, 2024
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We present a new way of solving the quasi-geostrophic (QG) equations, a simple set of equations describing ocean dynamics. Our method is solely based on the numerical methods used to solve the equations and requires no parameter tuning. Moreover, it can handle non-rectangular geometries, opening the way to study QG equations on realistic domains. We release a PyTorch implementation to ease future machine-learning developments on top of the presented method.
Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song
Geosci. Model Dev., 17, 1651–1665, https://doi.org/10.5194/gmd-17-1651-2024, https://doi.org/10.5194/gmd-17-1651-2024, 2024
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Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.
Eui-Jong Kang, Byung-Ju Sohn, Sang-Woo Kim, Wonho Kim, Young-Cheol Kwon, Seung-Bum Kim, Hyoung-Wook Chun, and Chao Liu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-23, https://doi.org/10.5194/gmd-2024-23, 2024
Revised manuscript accepted for GMD
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The recently available ERA5 hourly ocean skin temperature (Tint) data is expected to be valuable for various science studies. However, when analyzing the hourly variations of Tint, questions arise about its reliability, the deficiency of which may be related to errors in the ocean mixed layer (OML) model. To address this, we reexamined and corrected significant errors in the OML model. Validation of the simulated SST using the revised OML model against observations demonstrated good agreement.
Ali Abdolali, Saeideh Banihashemi, Jose Henrique Alves, Aron Roland, Tyler J. Hesser, Mary Anderson Bryant, and Jane McKee Smith
Geosci. Model Dev., 17, 1023–1039, https://doi.org/10.5194/gmd-17-1023-2024, https://doi.org/10.5194/gmd-17-1023-2024, 2024
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This article presents an overview of the development and implementation of Great Lake Wave Unstructured (GLWUv2.0), including the core model and workflow design and development. The validation was conducted against in situ data for the re-forecasted duration for summer and wintertime (ice season). The article describes the limitations and challenges encountered in the operational environment and the path forward for the next generation of wave forecast systems in enclosed basins like the GL.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
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Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-244, https://doi.org/10.5194/gmd-2023-244, 2024
Revised manuscript accepted for GMD
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We have introduced an "accelerated forcing" approach to address the discrepancy in timescales between ice sheet and ocean models in coupled modelling, by reducing the ocean model simulation duration. We evaluate the approach's applicability and limitations based on idealized coupled models. Our results suggest that, when used carefully, the approach can be a useful tool in coupled ice sheet-ocean modelling, especially relevant to studies on sea level rise projections.
Andrew C. Ross, Charles A. Stock, Alistair Adcroft, Enrique Curchitser, Robert Hallberg, Matthew J. Harrison, Katherine Hedstrom, Niki Zadeh, Michael Alexander, Wenhao Chen, Elizabeth J. Drenkard, Hubert du Pontavice, Raphael Dussin, Fabian Gomez, Jasmin G. John, Dujuan Kang, Diane Lavoie, Laure Resplandy, Alizée Roobaert, Vincent Saba, Sang-Ik Shin, Samantha Siedlecki, and James Simkins
Geosci. Model Dev., 16, 6943–6985, https://doi.org/10.5194/gmd-16-6943-2023, https://doi.org/10.5194/gmd-16-6943-2023, 2023
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We evaluate a model for northwest Atlantic Ocean dynamics and biogeochemistry that balances high resolution with computational economy by building on the new regional features in the MOM6 ocean model and COBALT biogeochemical model. We test the model's ability to simulate impactful historical variability and find that the model simulates the mean state and variability of most features well, which suggests the model can provide information to inform living-marine-resource applications.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
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We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, France Van Wambeke, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 16, 6701–6739, https://doi.org/10.5194/gmd-16-6701-2023, https://doi.org/10.5194/gmd-16-6701-2023, 2023
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While several studies have shown that mixotrophs play a crucial role in the carbon cycle, the impact of environmental forcings on their dynamics remains poorly investigated. Using a biogeochemical model that considers mixotrophs, we study the impact of light and nutrient concentration on the ecosystem composition in a highly dynamic Mediterranean coastal area: the Bay of Marseille. We show that mixotrophs cope better with oligotrophic conditions compared to strict auto- and heterotrophs.
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, and Øyvind Breivik
Geosci. Model Dev., 16, 6515–6530, https://doi.org/10.5194/gmd-16-6515-2023, https://doi.org/10.5194/gmd-16-6515-2023, 2023
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Surface waves that propagate in oceanic or coastal environments get influenced by their surroundings. Changes in the ambient current or the depth profile affect the wave propagation path, and the change in wave direction is called refraction. Some analytical solutions to the governing equations exist under ideal conditions, but for realistic situations, the equations must be solved numerically. Here we present such a numerical solver under an open-source license.
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev., 16, 6393–6412, https://doi.org/10.5194/gmd-16-6393-2023, https://doi.org/10.5194/gmd-16-6393-2023, 2023
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Ocean surface waves play an important role in the air–sea interface but are rarely activated in high-resolution Earth system simulations due to their expensive computational costs. To alleviate this situation, this paper designs a new wave modeling framework with a multiscale grid system. Evaluations of a series of numerical experiments show that it has good feasibility and applicability in the WAVEWATCH III model, WW3, and can achieve the goals of efficient and high-precision wave simulation.
Doroteaciro Iovino, Pier Giuseppe Fogli, and Simona Masina
Geosci. Model Dev., 16, 6127–6159, https://doi.org/10.5194/gmd-16-6127-2023, https://doi.org/10.5194/gmd-16-6127-2023, 2023
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This paper describes the model performance of three global ocean–sea ice configurations, from non-eddying (1°) to eddy-rich (1/16°) resolutions. Model simulations are obtained following the Ocean Model Intercomparison Project phase 2 (OMIP2) protocol. We compare key global climate variables across the three models and against observations, emphasizing the relative advantages and disadvantages of running forced ocean–sea ice models at higher resolution.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
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A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, and Vikram Singh
Geosci. Model Dev., 16, 5179–5196, https://doi.org/10.5194/gmd-16-5179-2023, https://doi.org/10.5194/gmd-16-5179-2023, 2023
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The new ocean general circulation model ICON-O is developed for running experiments at kilometer scales and beyond. One targeted application is to simulate internal tides crucial for ocean mixing. To ensure their realism, which is difficult to assess, we evaluate the barotropic tides that generate internal tides. We show that ICON-O is able to realistically simulate the major aspects of the observed barotropic tides and discuss the aspects that impact the quality of the simulated tides.
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
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While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover'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.
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
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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
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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
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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
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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
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In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS. We then performed a case study using the newly implemented model to study 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
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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
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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
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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
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MERCY is a 3D model to study mercury (Hg) cycling in the ocean. Hg is a highly harmful pollutant regulated by the UN Minamata Convention on Mercury due to widespread human emissions. These emissions eventually reach the oceans, where Hg transforms into the even more toxic and bioaccumulative pollutant methylmercury. MERCY predicts the fate of Hg in the ocean and its buildup in the food chain. It is the first model to consider Hg accumulation in fish, a major source of Hg exposure for humans.
Y. Joseph Zhang, Tomas Fernandez-Montblanc, William Pringle, Hao-Cheng Yu, Linlin Cui, and Saeed Moghimi
Geosci. Model Dev., 16, 2565–2581, https://doi.org/10.5194/gmd-16-2565-2023, https://doi.org/10.5194/gmd-16-2565-2023, 2023
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Simulating global ocean from deep basins to coastal areas is a daunting task but is important for disaster mitigation efforts. We present a new 3D global ocean model on flexible mesh to study both tidal and nontidal processes and total water prediction. We demonstrate the potential for
seamlesssimulation, on a single mesh, from the global ocean to a few estuaries along the US West Coast. The model can serve as the backbone of a global tide surge and compound flooding forecasting framework.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
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Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Manuel Aghito, Loris Calgaro, Knut-Frode Dagestad, Christian Ferrarin, Antonio Marcomini, Øyvind Breivik, and Lars Robert Hole
Geosci. Model Dev., 16, 2477–2494, https://doi.org/10.5194/gmd-16-2477-2023, https://doi.org/10.5194/gmd-16-2477-2023, 2023
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The newly developed ChemicalDrift model can simulate the transport and fate of chemicals in the ocean and in coastal regions. The model combines ocean physics, including transport due to currents, turbulence due to surface winds and the sinking of particles to the sea floor, with ocean chemistry, such as the partitioning, the degradation and the evaporation of chemicals. The model will be utilized for risk assessment of ocean and sea-floor contamination from pollutants emitted from shipping.
Nieves G. Valiente, Andrew Saulter, Breogan Gomez, Christopher Bunney, Jian-Guo Li, Tamzin Palmer, and Christine Pequignet
Geosci. Model Dev., 16, 2515–2538, https://doi.org/10.5194/gmd-16-2515-2023, https://doi.org/10.5194/gmd-16-2515-2023, 2023
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We document the Met Office operational global and regional wave models which provide wave forecasts up to 7 d ahead. Our models present coarser resolution offshore to higher resolution near the coastline. The increased resolution led to replication of the extremes but to some overestimation during modal conditions. If currents are included, wave directions and long period swells near the coast are significantly improved. New developments focus on the optimisation of the models with resolution.
Cited articles
Allard, R., Rogers, E., and Carroll, S. N.: User's Manual for the Simulating WAves Nearshore Model (SWAN), https://doi.org/10.21236/ADA409177, 2002. a
Alsina, J. M., Jongedijk, C. E., and van Sebille, E.: Laboratory Measurements of the Wave-Induced Motion of Plastic Particles: Influence of Wave Period, Plastic Size and Plastic Density, J. Geophys. Res.-Oceans, 125, e2020JC016294, https://doi.org/10.1029/2020JC016294, 2020. a
Alvarez Fanjul, E., García Sotillo, M., Pérez Gómez, B., García Valdecasas, J., Pérez Rubio, S., Lorente, P., Rodríguez Dapena, Á., Martínez Marco, I., Luna, Y., Padorno, E., Santos Atienza, I., Díaz Hernandez, G., López Lara, J., Medina, R., Grifoll, M., Espino, M., Mestres, M., Cerralbo, P., and Sánchez Arcilla, A.: Operational Oceanography at the Service of the Ports, in: New Frontiers in Operational Oceanography, GODAE OceanView, https://doi.org/10.17125/gov2018.ch27, 2018. a
Bezerra, M. O., Diez, M., Medeiros, C., Rodriguez, A., Bahia, E., Sanchez-Arcilla, A., and Redondo, J. M.: Study on the influence of waves on coastal diffusion using image analysis, Appl. Sci. Res., 59, 191–204, https://doi.org/10.1023/a:1001131304881, 1997. a
Bosi, S., Broström, G., and Roquet, F.: The Role of Stokes Drift in the Dispersal of North Atlantic Surface Marine Debris, Front. Mar. Sci., 8, 697430, https://doi.org/10.3389/fmars.2021.697430, 2021. a
Browne, M. A., Chapman, M. G., Thompson, R. C., Amaral Zettler, L. A., Jambeck, J., and Mallos, N. J.: Spatial and Temporal Patterns of Stranded Intertidal Marine Debris: Is There a Picture of Global Change?, Environ. Sci. Technol., 49, 7082–7094, https://doi.org/10.1021/es5060572, 2015. a
Cardoso, C. and Caldeira, R. M.: Modeling the Exposure of the Macaronesia Islands (NE Atlantic) to Marine Plastic Pollution, Front. Mar. Sci., 8, 653502, https://doi.org/10.3389/fmars.2021.653502, 2021. a
Castro-Rosero, L. M., Hernandez, I., Alsina, J. M., and Espino, M.: Transport and accumulation of floating marine litter in the Black Sea: insights from numerical modeling, Front. Mar. Sci., 10, 1–19, https://doi.org/10.3389/fmars.2023.1213333, 2023. a, b
Chassignet, E. P., Xu, X., and Zavala-Romero, O.: Tracking Marine Litter With a Global Ocean Model: Where Does It Go? Where Does It Come From?, Front. Mar. Sci., 8, 1–15, https://doi.org/10.3389/fmars.2021.667591, 2021. a, b, c, d
Chubarenko, I., Bagaev, A., Zobkov, M., and Esiukova, E.: On some physical and dynamical properties of microplastic particles in marine environment, Marine Pollut. Bull., 108, 105–112, https://doi.org/10.1016/j.marpolbul.2016.04.048, 2016. a
CMEMS: Copernicus Marine Service, Atlantic-Iberian Biscay Irish-Ocean Physics Reanalysis, IBI_MULTIYEAR_PHY_005_002, https://doi.org/10.48670/moi-00028, 2023. a, b
Critchell, K. and Lambrechts, J.: Modelling accumulation of marine plastics in the coastal zone; what are the dominant physical processes?, Estuar. Coast. Shelf S., 171, 111–122, https://doi.org/10.1016/j.ecss.2016.01.036, 2016. a, b
Critchell, K., Grech, A., Schlaefer, J., Andutta, F. P., Lambrechts, J., Wolanski, E., and Hamann, M.: Modelling the fate of marine debris along a complex shoreline: Lessons from the Great Barrier Reef, Estuar. Coast. Shelf S., 167, 414–426, https://doi.org/10.1016/j.ecss.2015.10.018, 2015. a, b
Dauhajre, D. P., McWilliams, J. C., and Renault, L.: Nearshore Lagrangian Connectivity: Submesoscale Influence and Resolution Sensitivity, J. Geophys. Res.-Oceans, 124, 5180–5204, https://doi.org/10.1029/2019JC014943, 2019. a
Delandmeter, P. and van Sebille, E.: The Parcels v2.0 Lagrangian framework: new field interpolation schemes, Geosci. Model Dev., 12, 3571–3584, https://doi.org/10.5194/gmd-12-3571-2019, 2019. a, b, c
Dobler, D., Huck, T., Maes, C., Grima, N., Blanke, B., Martinez, E., and Ardhuin, F.: Large impact of Stokes drift on the fate of surface floating debris in the South Indian Basin, Marine Pollut. Bull., 148, 202–209, https://doi.org/10.1016/j.marpolbul.2019.07.057, 2019. a
Eriksen, M., Lebreton, L. C., Carson, H. S., Thiel, M., Moore, C. J., Borerro, J. C., Galgani, F., Ryan, P. G., and Reisser, J.: Plastic Pollution in the World's Oceans: More than 5 Trillion Plastic Pieces Weighing over 250 000 Tons Afloat at Sea, PLoS ONE, 9, 1–15, https://doi.org/10.1371/journal.pone.0111913, 2014. a
Galgani, F., Hanke, G., and Maes, T.: Global Distribution, Composition and Abundance of Marine Litter, in: Marine Anthropogenic Litter, edited by: Bergmann, M., Gutow, L., and Klages, M., Springer International Publishing, Cham, 29–56, https://doi.org/10.1007/978-3-319-16510-3_2, 2015. a
García-León, M., Sotillo, M. G., Mestres, M., Espino, M., and Fanjul, E. Á.: Improving Operational Ocean Models for the Spanish Port Authorities: Assessment of the SAMOA Coastal Forecasting Service Upgrades, Journal of Marine Science and Engineering, 10, 149, https://doi.org/10.3390/jmse10020149, 2022. a, b, c, d, e
Gurvan, M., Bourdallé-Badie, R., Bouttier, P.-A., Bricaud, C., Bruciaferri, D., Calvert, D., Chanut, J., Clementi, E., Coward, A., Delrosso, D., Ethé, C., Flavoni, S., Graham, T., Harle, J., Iovino, D., Lea, D., Lévy, C., Lovato, T., Martin, N., Masson, S., Mocavero, S., Paul, J., Rousset, C., Storkey, D., Storto, A., and Vancoppenolle, M.: NEMO Ocean Engine, Zenodo, https://doi.org/10.5281/zenodo.1472492, 2017. a
Hernandez, I., Castro-Rosero, L. M., Espino, M., and Alsina Torrent, J. M.: LOCATE v1.0: Numerical Modelling of Floating Marine Debris Dispersion in Coastal Regions Using Nested Hydrodynamic Grids and Parcels v2.4.2, Zenodo [code], https://doi.org/10.5281/zenodo.8345027, 2023. a, b
Hinata, H. and Kataoka, T.: A belt transect setting strategy for mark-recapture experiments to evaluate the 1D diffusion coefficient of beached litter in the cross-shore direction, Marine Pollut. Bull., 109, 490–494, https://doi.org/10.1016/j.marpolbul.2016.05.016, 2016. a
Hinata, H., Mori, K., Ohno, K., Miyao, Y., and Kataoka, T.: An estimation of the average residence times and onshore-offshore diffusivities of beached microplastics based on the population decay of tagged meso- and macrolitter, Marine Pollut. Bull., 122, 17–26, https://doi.org/10.1016/j.marpolbul.2017.05.012, 2017. a, b, c, d, e
ICGC: Línia de Costa, Institut Cartogràfic i Geològic de Catalunya, Departament d'Acció Climàtica, Alimentació i Agenda Rural, https://agricultura.gencat.cat/ca/serveis/cartografia-sig/bases-cartografiques/cartografia-referencia/linia-costa/ (last access: June 2020), 2020. a
Isobe, A., Kubo, K., Tamura, Y., Kako, S., Nakashima, E., and Fujii, N.: Selective transport of microplastics and mesoplastics by drifting in coastal waters, Marine Pollut. Bull., 89, 324–330, https://doi.org/10.1016/j.marpolbul.2014.09.041, 2014. a
Kaandorp, M. L., Dijkstra, H. A., and Van Sebille, E.: Closing the Mediterranean Marine Floating Plastic Mass Budget: Inverse Modeling of Sources and Sinks, Environ. Sci. Technol., 54, 11980–11989, https://doi.org/10.1021/acs.est.0c01984, 2020. a, b
Kaandorp, M. L. A., Ypma, S. L., Boonstra, M., Dijkstra, H. A., and van Sebille, E.: Using machine learning and beach cleanup data to explain litter quantities along the Dutch North Sea coast, Ocean Sci., 18, 269–293, https://doi.org/10.5194/os-18-269-2022, 2022. a
Kaandorp, M. L. A., Lobelle, D., Kehl, C., Dijkstra, H. A., and Van Sebille, E.: Global mass of buoyant marine plastics dominated by large long-lived debris, Nat. Geosci., 16, 689–694, https://doi.org/10.1038/s41561-023-01216-0, 2023. a
Kataoka, T. and Hinata, H.: Evaluation of beach cleanup effects using linear system analysis, Marine Pollut. Bull., 91, 73–81, https://doi.org/10.1016/j.marpolbul.2014.12.026, 2015. a
Koelmans, A. A., Kooi, M., Law, K. L., and van Sebille, E.: All is not lost: Deriving a top-down mass budget of plastic at sea, Environ. Res. Lett., 12, 114028, https://doi.org/10.1088/1748-9326/aa9500, 2017. a
Law, K. L., Morét-Ferguson, S., Maximenko, N. A., Proskurowski, G., Peacock, E. E., Hafner, J., and Reddy, C. M.: Plastic Accumulation in the North Atlantic Subtropical Gyre, Science, 329, 1185–1188, https://doi.org/10.1126/science.1192321, 2010. a
Lebreton, L., Egger, M., and Slat, B.: A global mass budget for positively buoyant macroplastic debris in the ocean, Sci. Rep.-UK, 9, 1–10, https://doi.org/10.1038/s41598-019-49413-5, 2019. a, b, c, d
Lebreton, L. C., Greer, S. D., and Borrero, J. C.: Numerical modelling of floating debris in the world's oceans, Marine Pollut. Bull., 64, 653–661, https://doi.org/10.1016/j.marpolbul.2011.10.027, 2012. a, b, c
Lebreton, L. C., Van Der Zwet, J., Damsteeg, J. W., Slat, B., Andrady, A., and Reisser, J.: River plastic emissions to the world's oceans, Nat. Commun., 8, 1–10, https://doi.org/10.1038/ncomms15611, 2017. a
Liu, Y. and Weisberg, R. H.: Evaluation of trajectory modeling in different dynamic regions using normalized cumulative Lagrangian separation, J. Geophys. Res.-Oceans, 116, 1–13, https://doi.org/10.1029/2010JC006837, 2011. a, b
Liubartseva, S., Coppini, G., Lecci, R., and Clementi, E.: Tracking plastics in the Mediterranean: 2D Lagrangian model, Marine Pollut. Bull., 129, 151–162, https://doi.org/10.1016/j.marpolbul.2018.02.019, 2018. a, b, c
Macias, D., Cózar, A., Garcia-Gorriz, E., González-Fernández, D., and Stips, A.: Surface water circulation develops seasonally changing patterns of floating litter accumulation in the Mediterranean Sea. A modelling approach, Marine Pollut. Bull., 149, 110619, https://doi.org/10.1016/j.marpolbul.2019.110619, 2019. a, b, c
Macias, D., Stips, A., and Hanke, G.: Model based estimate of transboundary litter pollution on Mediterranean coasts, Marine Pollut. Bull., 175, 113121, https://doi.org/10.1016/j.marpolbul.2021.113121, 2022. a, b
Mansui, J., Molcard, A., and Ourmières, Y.: Modelling the transport and accumulation of floating marine debris in the Mediterranean basin, Marine Pollut. Bull., 91, 249–257, https://doi.org/10.1016/j.marpolbul.2014.11.037, 2015. a, b, c
Mansui, J., Darmon, G., Ballerini, T., van Canneyt, O., Ourmieres, Y., and Miaud, C.: Predicting marine litter accumulation patterns in the Mediterranean basin: Spatio-temporal variability and comparison with empirical data, Prog. Oceanogr., 182, 102268, https://doi.org/10.1016/j.pocean.2020.102268, 2020. a
Maximenko, N., Hafner, J., and Niiler, P.: Pathways of marine debris derived from trajectories of Lagrangian drifters, Marine Pollut. Bull., 65, 51–62, https://doi.org/10.1016/j.marpolbul.2011.04.016, 2012. a, b
Morales-Caselles, C., Viejo, J., Martí, E., González-Fernández, D., Pragnell-Raasch, H., González-Gordillo, J. I., Montero, E., Arroyo, G. M., Hanke, G., Salvo, V. S., Basurko, O. C., Mallos, N., Lebreton, L., Echevarría, F., van Emmerik, T., Duarte, C. M., Gálvez, J. A., van Sebille, E., Galgani, F., García, C. M., Ross, P. S., Bartual, A., Ioakeimidis, C., Markalain, G., Isobe, A., and Cózar, A.: An inshore–offshore sorting system revealed from global classification of ocean litter, Nat. Sustain., 4, 484–493, https://doi.org/10.1038/s41893-021-00720-8, 2021. a
Neumann, D., Callies, U., and Matthies, M.: Marine litter ensemble transport simulations in the southern North Sea, Marine Pollut. Bull., 86, 219–228, https://doi.org/10.1016/j.marpolbul.2014.07.016, 2014. a
OGS: Argo Italy, National Institute of Oceanography and Applied Geophysics, http://argo.ogs.it/#/data (last access: March 2023), 2023. a
Okubo, A.: Oceanic diffusion diagrams, Deep-Sea Res. Pt. I, 18, 789–802, https://doi.org/10.1016/0011-7471(71)90046-5, 1971. a, b
Onink, V., Wichmann, D., Delandmeter, P., and van Sebille, E.: The Role of Ekman Currents, Geostrophy, and Stokes Drift in the Accumulation of Floating Microplastic, J. Geophys. Res.-Oceans, 124, 1474–1490, https://doi.org/10.1029/2018JC014547, 2019. a
Onink, V., Kaandorp, M. L., Van Sebille, E., and Laufkötter, C.: Influence of Particle Size and Fragmentation on Large-Scale Microplastic Transport in the Mediterranean Sea, Environ. Sci. Technol., 56, 15528–15540, https://doi.org/10.1021/acs.est.2c03363, 2022. a
OPeNDAP: PdE OPeNDAP Catalog, https://opendap.puertos.es/thredds/catalog.html (last access: July 2023), 2022. a
Politikos, D. V., Ioakeimidis, C., Papatheodorou, G., and Tsiaras, K.: Modeling the fate and distribution of floating litter particles in the Aegean Sea (E. Mediterranean), Front. Mar. Sci., 4, 1–18, https://doi.org/10.3389/fmars.2017.00191, 2017. a, b, c
Politikos, D. V., Tsiaras, K., Papatheodorou, G., and Anastasopoulou, A.: Modeling of floating marine litter originated from the Eastern Ionian Sea: Transport, residence time and connectivity, Marine Pollut. Bull., 150, 110727, https://doi.org/10.1016/j.marpolbul.2019.110727, 2020. a, b, c
Rech, S., Macaya-Caquilpán, V., Pantoja, J., Rivadeneira, M., Jofre Madariaga, D., and Thiel, M.: Rivers as a source of marine litter – A study from the SE Pacific, Marine Pollut. Bull., 82, 66–75, https://doi.org/10.1016/j.marpolbul.2014.03.019, 2014. a
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, Front. Mar. Sci., 8, 630388, https://doi.org/10.3389/fmars.2021.630388, 2021. a, b
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. a
ROMS: Regional Ocean Model System, https://www.myroms.org/ (last access: July 2023), 2022. a
Rosas, E., Martins, F., and Janeiro, J.: Marine litter on the coast of the algarve: Main sources and distribution using a modeling approach, J. Mar. Sci. Eng., 9, 412, https://doi.org/10.3390/jmse9040412, 2021. a, b, c
Ross, O. N. and Sharples, J.: Recipe for 1-D Lagrangian particle tracking models in space-varying diffusivity, Limnol. Oceanogr.-Meth., 2, 289–302, https://doi.org/10.4319/lom.2004.2.289, 2004. a
Ruiz, I., Ana J., A., Basurko, O. C., and Rubio, A.: Modelling the distribution of fishing-related floating marine litter within the Bay of Biscay and its marine protected areas, Environ. Pollut., 292, 118216, https://doi.org/10.1016/j.envpol.2021.118216, 2022. a, b
Sanchez-Vidal, A., Uviedo, O., Higueras, S., Ballesteros, M., Curto, X., de Haan, W. P., Bonfill, E., Canals, M., Canales, I., Calafat, A., Comaposada, A., Del Río, P., Ferrer, X., Fos, H., Lastras, G., Llorente, M., Martínez, F., Ramírez, M., and Pedrero, G.: Paddle surfing for science on microplastic pollution: a successful citizen science initiative, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10579, https://doi.org/10.5194/egusphere-egu21-10579, 2021. a
Schirinzi, G. F., Köck-Schulmeyer, M., Cabrera, M., González-Fernández, D., Hanke, G., Farré, M., and Barceló, D.: Riverine anthropogenic litter load to the Mediterranean Sea near the metropolitan area of Barcelona, Spain, Sci. Total Environ., 714, 136807, https://doi.org/10.1016/j.scitotenv.2020.136807, 2020. a
Seo, S. and Park, Y. G.: Destination of floating plastic debris released from ten major rivers around the Korean Peninsula, Environ. Int., 138, 105655, https://doi.org/10.1016/j.envint.2020.105655, 2020. a
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. a
Sotillo, M. G., Cailleau, S., Lorente, P., Levier, B., Aznar, R., Reffray, G., Amo-Baladrón, A., Chanut, J., Benkiran, M., and Alvarez-Fanjul, E.: The myocean IBI ocean forecast and reanalysis systems: Operational products and roadmap to the future copernicus service, J. Oper. Oceanogr., 8, 63–79, https://doi.org/10.1080/1755876X.2015.1014663, 2015. a, b, c, d, e
Sotillo, M. G., Mourre, B., Mestres, M., Lorente, P., Aznar, R., García-León, M., Liste, M., Santana, A., Espino, M., and Álvarez, E.: Evaluation of the Operational CMEMS and Coastal Downstream Ocean Forecasting Services During the Storm Gloria (January 2020), Front. Mar. Sci., 8, 1–27, https://doi.org/10.3389/fmars.2021.644525, 2021. a, b, c, d, e, f
Stokes, G. G.: On the Theory of Oscillatory Waves, Cambridge Library Collection – Mathematics, vol. 1, Cambridge University Press, 197–229, https://doi.org/10.1017/CBO9780511702242.013, 1880. a
van der Mheen, M., van Sebille, E., and Pattiaratchi, C.: Beaching patterns of plastic debris along the Indian Ocean rim, Ocean Sci., 16, 1317–1336, https://doi.org/10.5194/os-16-1317-2020, 2020. a
van Sebille, E., England, M. H., and Froyland, G.: Origin, dynamics and evolution of ocean garbage patches from observed surface drifters, Environ. Res. Lett., 7, 044040, https://doi.org/10.1088/1748-9326/7/4/044040, 2012. a
van Sebille, E., Wilcox, C., Lebreton, L., Maximenko, N., Hardesty, B. D., Van Franeker, J. A., Eriksen, M., Siegel, D., Galgani, F., and Law, K. L.: A global inventory of small floating plastic debris, Environ. Res. Lett., 10, 124006, https://doi.org/10.1088/1748-9326/10/12/124006, 2015. a
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., 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. a, b
van Sebille, E., Aliani, S., Law, K. L., Maximenko, N., Alsina, J. M., Bagaev, A., Bergmann, M., Chapron, B., Chubarenko, I., Cózar, A., Delandmeter, P., Egger, M., Fox-Kemper, B., Garaba, S. P., Goddijn-Murphy, L., Hardesty, B. D., Hoffman, M. J., Isobe, A., Jongedijk, C. E., Kaandorp, M. L. A., Khatmullina, L., Koelmans, A. A., Kukulka, T., Laufkötter, C., Lebreton, L., Lobelle, D., Maes, C., Martinez-Vicente, V., Morales Maqueda, M. A., Poulain-Zarcos, M., Rodríguez, E., Ryan, P. G., Shanks, A. L., Shim, W. J., Suaria, G., Thiel, M., van den Bremer, T. S., and Wichmann, D.: The physical oceanography of the transport of floating marine debris, Environ. Res. Lett., 15, 023003, https://doi.org/10.1088/1748-9326/ab6d7d, 2020. a, b, c
Van Sebille, E., Kehl, C., Lange, M., and Delandmeter, P.: Parcels, Zenodo [code], https://doi.org/10.5281/zenodo.8010997, 2023. a
Vogt-Vincent, N. S., Burt, A. J., Kaplan, D. M., Mitarai, S., Turnbull, L. A., and Johnson, H. L.: Sources of marine debris for Seychelles and other remote islands in the western Indian Ocean, Marine Pollut. Bull., 187, 114497, https://doi.org/10.1016/j.marpolbul.2022.114497, 2023. a
Yoon, J. H., Kawano, S., and Igawa, S.: Modeling of marine litter drift and beaching in the Japan Sea, Marine Pollut. Bull., 60, 448–463, https://doi.org/10.1016/j.marpolbul.2009.09.033, 2010. a, b, c
Zambianchi, E., Trani, M., and Falco, P.: Lagrangian transport of marine litter in the Mediterranean Sea, Front. Environ. Sci., 5, 1–15, https://doi.org/10.3389/fenvs.2017.00005, 2017. a, b, c
Zhang, H.: Transport of microplastics in coastal seas, Estuar. Coast. Shelf S., 199, 74–86, https://doi.org/10.1016/j.ecss.2017.09.032, 2017. a
Zhang, Z., Wu, H., Peng, G., Xu, P., and Li, D.: Coastal ocean dynamics reduce the export of microplastics to the open ocean, Sci. Total Environ., 713, 136634, https://doi.org/10.1016/j.scitotenv.2020.136634, 2020. a
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.
The LOCATE numerical model was developed to conduct Lagrangian simulations of the transport and...
