Articles | Volume 16, issue 3
https://doi.org/10.5194/gmd-16-1163-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-1163-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
16 Feb 2023
Model evaluation paper |
| 16 Feb 2023
| 16 Feb 2023
Multidecadal and climatological surface current simulations for the southwestern Indian Ocean at 1∕50° resolution
Noam S. Vogt-Vincent
Department of Earth Sciences, South Parks Road, University of Oxford, Oxford, UK
Helen L. Johnson
CORRESPONDING AUTHOR
Department of Earth Sciences, South Parks Road, University of Oxford, Oxford, UK
Related authors
Gerald Auer, Or M. Bialik, Mary-Elizabeth Antoulas, Noam Vogt-Vincent, and Werner E. Piller
Clim. Past, 19, 2313–2340, https://doi.org/10.5194/cp-19-2313-2023, https://doi.org/10.5194/cp-19-2313-2023, 2023
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We provided novel insights into the behaviour of a major upwelling cell between 15 and 8.5 million years ago. To study changing conditions, we apply a combination of geochemical and paleoecological parameters to characterize the nutrient availability and subsequent utilization by planktonic primary producers. These changes we then juxtapose with established records of contemporary monsoon wind intensification and changing high-latitude processes to explain shifts in the plankton community.
Noam S. Vogt-Vincent, Satoshi Mitarai, and Helen L. Johnson
EGUsphere, https://doi.org/10.5194/egusphere-2023-778, https://doi.org/10.5194/egusphere-2023-778, 2023
Preprint archived
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Coral larvae can drift through ocean currents between coral reefs, establishing connectivity, which plays an important role in coral reef resilience. However, larval transport is chaotic. We simulate coral spawning events across the tropical southwest Indian Ocean for almost three decades, and find that larval transport can vary massively from day-to-day. This variability is largely random, and this introduces a lot of uncertainty in connectivity predictions.
Helene Asbjørnsen, Tor Eldevik, Johanne Skrefsrud, Helen L. Johnson, and Alejandra Sanchez-Franks
Ocean Sci., 20, 799–816, https://doi.org/10.5194/os-20-799-2024, https://doi.org/10.5194/os-20-799-2024, 2024
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The Gulf Stream system is essential for northward ocean heat transport. Here, we use observations along the path of the extended Gulf Stream system and an observationally constrained ocean model to investigate variability in the Gulf Stream system since the 1990s. We find regional differences in the variability between the subtropical, subpolar, and Nordic Seas regions, which warrants caution in using observational records at a single latitude to infer large-scale circulation change.
Yavor Kostov, Marie-José Messias, Herlé Mercier, David P. Marshall, and Helen L. Johnson
Ocean Sci., 20, 521–547, https://doi.org/10.5194/os-20-521-2024, https://doi.org/10.5194/os-20-521-2024, 2024
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We examine factors affecting variability in the volume of Labrador Sea Water (LSW), a water mass that is important for the uptake and storage of heat and carbon in the Atlantic Ocean. We find that LSW accumulated in the Labrador Sea exhibits a lagged response to remote conditions: surface wind stress, heat flux, and freshwater flux anomalies, especially along the pathways of the North Atlantic Current branches. We use our results to reconstruct and attribute historical changes in LSW volume.
Gerald Auer, Or M. Bialik, Mary-Elizabeth Antoulas, Noam Vogt-Vincent, and Werner E. Piller
Clim. Past, 19, 2313–2340, https://doi.org/10.5194/cp-19-2313-2023, https://doi.org/10.5194/cp-19-2313-2023, 2023
Short summary
Short summary
We provided novel insights into the behaviour of a major upwelling cell between 15 and 8.5 million years ago. To study changing conditions, we apply a combination of geochemical and paleoecological parameters to characterize the nutrient availability and subsequent utilization by planktonic primary producers. These changes we then juxtapose with established records of contemporary monsoon wind intensification and changing high-latitude processes to explain shifts in the plankton community.
Oliver John Tooth, Helen Louise Johnson, Chris Wilson, and Dafydd Gwyn Evans
Ocean Sci., 19, 769–791, https://doi.org/10.5194/os-19-769-2023, https://doi.org/10.5194/os-19-769-2023, 2023
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This study uses the trajectories of water parcels traced within an ocean model simulation to identify the pathways responsible for the seasonal cycle of dense water formation (overturning) in the eastern subpolar North Atlantic. We show that overturning seasonality is due to the fastest water parcels circulating within the eastern basins in less than 8.5 months. Slower pathways set the average strength of overturning in this region since water parcels cannot escape intense wintertime cooling.
Noam S. Vogt-Vincent, Satoshi Mitarai, and Helen L. Johnson
EGUsphere, https://doi.org/10.5194/egusphere-2023-778, https://doi.org/10.5194/egusphere-2023-778, 2023
Preprint archived
Short summary
Short summary
Coral larvae can drift through ocean currents between coral reefs, establishing connectivity, which plays an important role in coral reef resilience. However, larval transport is chaotic. We simulate coral spawning events across the tropical southwest Indian Ocean for almost three decades, and find that larval transport can vary massively from day-to-day. This variability is largely random, and this introduces a lot of uncertainty in connectivity predictions.
Related subject area
Oceanography
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StraitFlux – precise computations of water strait fluxes on various modeling grids
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Intercomparisons of Tracker v1.1 and four other ocean particle-tracking software packages in the Regional Ocean Modeling System
CAR36, a regional high-resolution ocean forecasting system for improving drift and beaching of Sargassum in the Caribbean archipelago
Implementation of additional spectral wave field exchanges in a three-dimensional wave–current coupled WAVEWATCH-III (version 6.07) and CROCO (version 1.2) configuration: assessment of their implications for macro-tidal coastal hydrodynamics
Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system
LOCATE v1.0: numerical modelling of floating marine debris dispersion in coastal regions using Parcels v2.4.2
New insights into the South China Sea throughflow and water budget seasonal cycle: evaluation and analysis of a high-resolution configuration of the ocean model SYMPHONIE version 2.4
MQGeometry-1.0: a multi-layer quasi-geostrophic solver on non-rectangular geometries
Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on El Niño–Southern Oscillation forecasts
Towards a real-time modeling of global ocean waves by the fully GPU-accelerated spectral wave model WAM6-GPU
Great Lakes wave forecast system on high-resolution unstructured meshes
Development of a Novel Storm Surge Inundation Model Framework for Efficient Prediction
Skin Sea Surface Temperature schemes in coupled ocean-atmosphere modeling: the impact of chlorophyll-interactive e-folding depth
Impact of increased resolution on Arctic Ocean simulations in Ocean Model Intercomparison Project phase 2 (OMIP-2)
A high-resolution physical–biogeochemical model for marine resource applications in the northwest Atlantic (MOM6-COBALT-NWA12 v1.0)
A flexible z-layers approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)
Implementation and assessment of a model including mixotrophs and the carbonate cycle (Eco3M_MIX-CarbOx v1.0) in a highly dynamic Mediterranean coastal environment (Bay of Marseille, France) – Part 1: Evolution of ecosystem composition under limited light and nutrient conditions
Ocean wave tracing v.1: a numerical solver of the wave ray equations for ocean waves on variable currents at arbitrary depths
Design and evaluation of an efficient high-precision ocean surface wave model with a multiscale grid system (MSG_Wav1.0)
Evaluation of the CMCC global eddying ocean model for the Ocean Model Intercomparison Project (OMIP2)
Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard
Open-ocean tides simulated by ICON-O, version icon-2.6.6
Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll
Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var
Using the COAsT Python package to develop a standardised validation workflow for ocean physics models
Improving Antarctic Bottom Water precursors in NEMO for climate applications
Formulation, optimization, and sensitivity of NitrOMZv1.0, a biogeochemical model of the nitrogen cycle in oceanic oxygen minimum zones
Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu
Adding sea ice effects to a global operational model (NEMO v3.6) for forecasting total water level: approach and impact
Enhanced ocean wave modeling by including effect of breaking under both deep- and shallow-water conditions
An internal solitary wave forecasting model in the northern South China Sea (ISWFM-NSCS)
The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methylmercury in fish
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Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
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We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024, https://doi.org/10.5194/gmd-17-4603-2024, 2024
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Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data are complicated by the distortion of the used modelling grids and the large number of different grid types. We present two new methods that allow the calculation of oceanic fluxes of volume, heat, salinity, and ice through almost arbitrary sections for various models and reanalyses that are independent of the used modelling grids.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024, https://doi.org/10.5194/gmd-17-4095-2024, 2024
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Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356, https://doi.org/10.5194/gmd-17-3341-2024, https://doi.org/10.5194/gmd-17-3341-2024, 2024
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The new offline particle tracking package, Tracker v1.1, is introduced to the Regional Ocean Modeling System, featuring an efficient nearest-neighbor algorithm to enhance particle-tracking speed. Its performance was evaluated against four other tracking packages and passive dye. Despite unique features, all packages yield comparable results. Running multiple packages within the same circulation model allows comparison of their performance and ease of use.
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173, https://doi.org/10.5194/gmd-17-3157-2024, https://doi.org/10.5194/gmd-17-3157-2024, 2024
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In order to improve Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher-resolution ocean currents. To this goal a 3 km resolution regional ocean model has been developed. Its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation was found to be quite realistic.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
Geosci. Model Dev., 17, 2829–2853, https://doi.org/10.5194/gmd-17-2829-2024, https://doi.org/10.5194/gmd-17-2829-2024, 2024
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Here a new method of modelling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean currents and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave–current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
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Ocean forecasting relies on the combination of numerical models and ocean observations through data assimilation (DA). Here we assess the performance of two DA systems in a dynamic western boundary current, the East Australian Current, across a common modelling and observational framework. We show that the more advanced, time-dependent method outperforms the time-independent method for forecast horizons of 5 d. This advocates the use of advanced methods for highly variable oceanic regions.
Ivan Hernandez, Leidy M. Castro-Rosero, Manuel Espino, and Jose M. Alsina Torrent
Geosci. Model Dev., 17, 2221–2245, https://doi.org/10.5194/gmd-17-2221-2024, https://doi.org/10.5194/gmd-17-2221-2024, 2024
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The LOCATE numerical model was developed to conduct Lagrangian simulations of the transport and dispersion of marine debris at coastal scales. High-resolution hydrodynamic data and a beaching module that used particle distance to the shore for land–water boundary detection were used on a realistic debris discharge scenario comparing hydrodynamic data at various resolutions. Coastal processes and complex geometric structures were resolved when using nested grids and distance-to-shore beaching.
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
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A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
Geosci. Model Dev., 17, 1749–1764, https://doi.org/10.5194/gmd-17-1749-2024, https://doi.org/10.5194/gmd-17-1749-2024, 2024
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We present a new way of solving the quasi-geostrophic (QG) equations, a simple set of equations describing ocean dynamics. Our method is solely based on the numerical methods used to solve the equations and requires no parameter tuning. Moreover, it can handle non-rectangular geometries, opening the way to study QG equations on realistic domains. We release a PyTorch implementation to ease future machine-learning developments on top of the presented method.
Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song
Geosci. Model Dev., 17, 1651–1665, https://doi.org/10.5194/gmd-17-1651-2024, https://doi.org/10.5194/gmd-17-1651-2024, 2024
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Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.
Ye Yuan, Fujiang Yu, Zhi Chen, Xueding Li, Fang Hou, Yuanyong Gao, Zhiyi Gao, and Renbo Pang
EGUsphere, https://doi.org/10.5194/egusphere-2024-169, https://doi.org/10.5194/egusphere-2024-169, 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, Graphics Processing Unit (GPU)-accelerated computing is introduced in the WAM (Cycle 6). With this effort, global high-resolution wave simulations now can run on GPUs up to tens of times faster than currently available models on a CPU node with just as accurate results.
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.
Xuanxuan Gao, Shuiqing Li, Dongxue Mo, Yahao Liu, and Po Hu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-12, https://doi.org/10.5194/gmd-2024-12, 2024
Revised manuscript accepted for GMD
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Storm surges generate coastal inundation and expose populations and properties in 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 significantly improves over the 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. Discuss., https://doi.org/10.5194/gmd-2024-13, https://doi.org/10.5194/gmd-2024-13, 2024
Revised manuscript accepted for GMD
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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.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
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Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Andrew C. Ross, Charles A. Stock, Alistair Adcroft, Enrique Curchitser, Robert Hallberg, Matthew J. Harrison, Katherine Hedstrom, Niki Zadeh, Michael Alexander, Wenhao Chen, Elizabeth J. Drenkard, Hubert du Pontavice, Raphael Dussin, Fabian Gomez, Jasmin G. John, Dujuan Kang, Diane Lavoie, Laure Resplandy, Alizée Roobaert, Vincent Saba, Sang-Ik Shin, Samantha Siedlecki, and James Simkins
Geosci. Model Dev., 16, 6943–6985, https://doi.org/10.5194/gmd-16-6943-2023, https://doi.org/10.5194/gmd-16-6943-2023, 2023
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We evaluate a model for northwest Atlantic Ocean dynamics and biogeochemistry that balances high resolution with computational economy by building on the new regional features in the MOM6 ocean model and COBALT biogeochemical model. We test the model's ability to simulate impactful historical variability and find that the model simulates the mean state and variability of most features well, which suggests the model can provide information to inform living-marine-resource applications.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
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We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, France Van Wambeke, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 16, 6701–6739, https://doi.org/10.5194/gmd-16-6701-2023, https://doi.org/10.5194/gmd-16-6701-2023, 2023
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While several studies have shown that mixotrophs play a crucial role in the carbon cycle, the impact of environmental forcings on their dynamics remains poorly investigated. Using a biogeochemical model that considers mixotrophs, we study the impact of light and nutrient concentration on the ecosystem composition in a highly dynamic Mediterranean coastal area: the Bay of Marseille. We show that mixotrophs cope better with oligotrophic conditions compared to strict auto- and heterotrophs.
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, and Øyvind Breivik
Geosci. Model Dev., 16, 6515–6530, https://doi.org/10.5194/gmd-16-6515-2023, https://doi.org/10.5194/gmd-16-6515-2023, 2023
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Surface waves that propagate in oceanic or coastal environments get influenced by their surroundings. Changes in the ambient current or the depth profile affect the wave propagation path, and the change in wave direction is called refraction. Some analytical solutions to the governing equations exist under ideal conditions, but for realistic situations, the equations must be solved numerically. Here we present such a numerical solver under an open-source license.
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev., 16, 6393–6412, https://doi.org/10.5194/gmd-16-6393-2023, https://doi.org/10.5194/gmd-16-6393-2023, 2023
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Ocean surface waves play an important role in the air–sea interface but are rarely activated in high-resolution Earth system simulations due to their expensive computational costs. To alleviate this situation, this paper designs a new wave modeling framework with a multiscale grid system. Evaluations of a series of numerical experiments show that it has good feasibility and applicability in the WAVEWATCH III model, WW3, and can achieve the goals of efficient and high-precision wave simulation.
Doroteaciro Iovino, Pier Giuseppe Fogli, and Simona Masina
Geosci. Model Dev., 16, 6127–6159, https://doi.org/10.5194/gmd-16-6127-2023, https://doi.org/10.5194/gmd-16-6127-2023, 2023
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This paper describes the model performance of three global ocean–sea ice configurations, from non-eddying (1°) to eddy-rich (1/16°) resolutions. Model simulations are obtained following the Ocean Model Intercomparison Project phase 2 (OMIP2) protocol. We compare key global climate variables across the three models and against observations, emphasizing the relative advantages and disadvantages of running forced ocean–sea ice models at higher resolution.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
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A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, and Vikram Singh
Geosci. Model Dev., 16, 5179–5196, https://doi.org/10.5194/gmd-16-5179-2023, https://doi.org/10.5194/gmd-16-5179-2023, 2023
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The new ocean general circulation model ICON-O is developed for running experiments at kilometer scales and beyond. One targeted application is to simulate internal tides crucial for ocean mixing. To ensure their realism, which is difficult to assess, we evaluate the barotropic tides that generate internal tides. We show that ICON-O is able to realistically simulate the major aspects of the observed barotropic tides and discuss the aspects that impact the quality of the simulated tides.
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.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-34, https://doi.org/10.5194/gmd-2023-34, 2023
Preprint under review for GMD
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Carbonate system is typically studied using measurements, yet modelling 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 their variations are strongly impacted by the hydrodynamic processes that affect the bay.
Maxime Beauchamp, Quentin Febvre, Hugo Georgenthum, and Ronan Fablet
Geosci. Model Dev., 16, 2119–2147, https://doi.org/10.5194/gmd-16-2119-2023, https://doi.org/10.5194/gmd-16-2119-2023, 2023
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4DVarNet is a learning-based method based on traditional data assimilation (DA). This new class of algorithms can be used to provide efficient reconstructions of a dynamical system based on single observations. We provide a 4DVarNet application to sea surface height reconstructions based on nadir and future Surface Water and Ocean and Topography data. It outperforms other methods, from optimal interpolation to sophisticated DA algorithms. This work is part of on-going AI Chair Oceanix projects.
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev., 16, 1755–1777, https://doi.org/10.5194/gmd-16-1755-2023, https://doi.org/10.5194/gmd-16-1755-2023, 2023
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A new global surface-wave–tide–circulation coupled ocean model (FIO-COM32) with a resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are shown to be important contributors to the significant improvements in FIO-COM32 simulations. It is time to merge these separated model components (surface waves, tidal currents and ocean circulation) and start a new generation of ocean model development.
Jeff Polton, James Harle, Jason Holt, Anna Katavouta, Dale Partridge, Jenny Jardine, Sarah Wakelin, Julia Rulent, Anthony Wise, Katherine Hutchinson, David Byrne, Diego Bruciaferri, Enda O'Dea, Michela De Dominicis, Pierre Mathiot, Andrew Coward, Andrew Yool, Julien Palmiéri, Gennadi Lessin, Claudia Gabriela Mayorga-Adame, Valérie Le Guennec, Alex Arnold, and Clément Rousset
Geosci. Model Dev., 16, 1481–1510, https://doi.org/10.5194/gmd-16-1481-2023, https://doi.org/10.5194/gmd-16-1481-2023, 2023
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The aim is to increase the capacity of the modelling community to respond to societally important questions that require ocean modelling. The concept of reproducibility for regional ocean modelling is developed: advocating methods for reproducible workflows and standardised methods of assessment. Then, targeting the NEMO framework, we give practical advice and worked examples, highlighting key considerations that will the expedite development cycle and upskill the user community.
Nairita Pal, Kristin N. Barton, Mark R. Petersen, Steven R. Brus, Darren Engwirda, Brian K. Arbic, Andrew F. Roberts, Joannes J. Westerink, and Damrongsak Wirasaet
Geosci. Model Dev., 16, 1297–1314, https://doi.org/10.5194/gmd-16-1297-2023, https://doi.org/10.5194/gmd-16-1297-2023, 2023
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Understanding tides is essential to accurately predict ocean currents. Over the next several decades coastal processes such as flooding and erosion will be severely impacted due to climate change. Tides affect currents along the coastal regions the most. In this paper we show the results of implementing tides in a global ocean model known as MPAS–Ocean. We also show how Antarctic ice shelf cavities affect global tides. Our work points towards future research with tide–ice interactions.
Sébastien Petton, Valérie Garnier, Matthieu Caillaud, Laurent Debreu, and Franck Dumas
Geosci. Model Dev., 16, 1191–1211, https://doi.org/10.5194/gmd-16-1191-2023, https://doi.org/10.5194/gmd-16-1191-2023, 2023
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The nesting AGRIF library is implemented in the MARS3D hydrodynamic model, a semi-implicit, free-surface numerical model which uses a time scheme as an alternating-direction implicit (ADI) algorithm. Two applications at the regional and coastal scale are introduced. We compare the two-nesting approach to the classic offline one-way approach, based on an in situ dataset. This method is an efficient means to significantly improve the physical hydrodynamics and unravel ecological challenges.
Pengyang Song, Dmitry Sidorenko, Patrick Scholz, Maik Thomas, and Gerrit Lohmann
Geosci. Model Dev., 16, 383–405, https://doi.org/10.5194/gmd-16-383-2023, https://doi.org/10.5194/gmd-16-383-2023, 2023
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Tides have essential effects on the ocean and climate. Most previous research applies parameterised tidal mixing to discuss their effects in models. By comparing the effect of a tidal mixing parameterisation and tidal forcing on the ocean state, we assess the advantages and disadvantages of the two methods. Our results show that tidal mixing in the North Pacific Ocean strongly affects the global thermohaline circulation. We also list some effects that are not considered in the parameterisation.
Marko Rus, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev., 16, 271–288, https://doi.org/10.5194/gmd-16-271-2023, https://doi.org/10.5194/gmd-16-271-2023, 2023
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We propose a new fast and reliable deep-learning architecture HIDRA2 for sea level and storm surge modeling. HIDRA2 features new feature encoders and a fusion-regression block. We test HIDRA2 on Adriatic storm surges, which depend on an interaction between tides and seiches. We demonstrate that HIDRA2 learns to effectively mimic the timing and amplitude of Adriatic seiches. This is essential for reliable HIDRA2 predictions of total storm surge sea levels.
Joao Marcos Azevedo Correia de Souza, Sutara H. Suanda, Phellipe P. Couto, Robert O. Smith, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 211–231, https://doi.org/10.5194/gmd-16-211-2023, https://doi.org/10.5194/gmd-16-211-2023, 2023
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The current paper describes the configuration and evaluation of the Moana Ocean Hindcast, a > 25-year simulation of the ocean state around New Zealand using the Regional Ocean Modeling System v3.9. This is the first open-access, long-term, continuous, realistic ocean simulation for this region and provides information for improving the understanding of the ocean processes that affect the New Zealand exclusive economic zone.
Hao Huang, Pengyang Song, Shi Qiu, Jiaqi Guo, and Xueen Chen
Geosci. Model Dev., 16, 109–133, https://doi.org/10.5194/gmd-16-109-2023, https://doi.org/10.5194/gmd-16-109-2023, 2023
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The Oceanic Regional Circulation and Tide Model (ORCTM) is developed to reproduce internal solitary wave dynamics. The three-dimensional nonlinear momentum equations are involved with the nonhydrostatic pressure obtained via solving the Poisson equation. The validation experimental results agree with the internal wave theories and observations, demonstrating that the ORCTM can successfully describe the life cycle of nonlinear internal solitary waves under different oceanic environments.
David E. Gwyther, Shane R. Keating, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 157–178, https://doi.org/10.5194/gmd-16-157-2023, https://doi.org/10.5194/gmd-16-157-2023, 2023
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Ocean eddies are important for weather, climate, biology, navigation, and search and rescue. Since eddies change rapidly, models that incorporate or assimilate observations are required to produce accurate eddy timings and locations, yet the model accuracy is rarely assessed below the surface. We use a unique type of ocean model experiment to assess three-dimensional eddy structure in the East Australian Current and explore two pathways in which this subsurface structure is being degraded.
Shun Ohishi, Takemasa Miyoshi, and Misako Kachi
Geosci. Model Dev., 15, 9057–9073, https://doi.org/10.5194/gmd-15-9057-2022, https://doi.org/10.5194/gmd-15-9057-2022, 2022
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An adaptive observation error inflation (AOEI) method was proposed for atmospheric data assimilation to mitigate erroneous analysis updates caused by large observation-minus-forecast differences for satellite brightness temperature around clear- and cloudy-sky boundaries. This study implemented the AOEI with an ocean data assimilation system, leading to an improvement of analysis accuracy and dynamical balance around the frontal regions with large meridional temperature differences.
Cited articles
Auclair, F., Benshila, R., Bordois, L., Boutet, M., Brémond, M., Caillaud, M., Cambon, G., Capet, X., Debreu, L., Ducousso, N., Dufois, F., Dumas, F., Ethé, C., Gula, J., Hourdin, C., Illig, S., Jullien, S., Le Corre, M., Le Gac, S., Le Gentil, S., Lemarié, F., Marchesiello, P., Mazoyer, C., Morvan, G., Nguyen, C., Penven, P., Person, R., Pianezze, J., Pous, S., Renault, L., Roblou, L., Sepulveda, A., and Theetten, S.: Coastal and Regional Ocean COmmunity model (1.1), Zenodo [code], https://doi.org/10.5281/zenodo.7415133, 2019. a, b
Beal, L. M., Vialard, J., and Roxy, M. K.: Full Report. IndOOS-2: A roadmap to
sustained observations of the Indian Ocean for 2020–2030,
http://www.clivar.org/sites/default/files/documents/IndOOS_report_small.pdf (last access: 14 February 2023),
2019. a
Connolly, S. R. and Baird, A. H.: Estimating dispersal potential for marine
larvae: Dynamic models applied to scleractinian corals, Ecology, 91,
3572–3583, https://doi.org/10.1890/10-0143.1, 2010. a
Dai, A. and Trenberth, K. E.: Estimates of freshwater discharge from
continents: Latitudinal and seasonal variations, J.
Hydrometeorol., 3, 660–687,
https://doi.org/10.1175/1525-7541(2002)003<0660:EOFDFC>2.0.CO;2, 2002. a, b
Dask Development Team: Dask: Library for dynamic task scheduling,
https://dask.org (last access: 14 February 2023), 2016. a
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, b
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
Dunne, R.: Tides and sea level in the Chagos Archipelago, Tech. Rep.
September,
https://sites.google.com/site/thechagosarchipelago2/chagos-science/sea-level/tides-sea-level-2021 (last access: 14 February 2023),
2021. a
Edmunds, P. J., McIlroy, S. E., Adjeroud, M., Ang, P., Bergman, J. L.,
Carpenter, R. C., Coffroth, M. A., Fujimura, A. G., Hench, J. L., Holbrook,
S. J., Leichter, J. J., Muko, S., Nakajima, Y., Nakamura, M., Paris, C. B.,
Schmitt, R. J., Sutthacheep, M., Toonen, R. J., Sakai, K., Suzuki, G.,
Washburn, L., Wyatt, A. S. J., and Mitarai, S.: Critical Information Gaps
Impeding Understanding of the Role of Larval Connectivity Among Coral Reef
Islands in an Era of Global Change, Front. Marine Sci., 5, 1–16,
https://doi.org/10.3389/fmars.2018.00290, 2018. a
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. a, b
GEBCO Compilation Group: GEBCO 2019 Grid, National Oceanography Centre,
https://doi.org/10.5285/836f016a-33be-6ddc-e053-6c86abc0788e, 2019. a
Good, S., Fiedler, E., Mao, C., Martin, M. J., Maycock, A., Reid, R.,
Roberts-Jones, J., Searle, T., Waters, J., While, J., and Worsfold, M.: The
current configuration of the OSTIA system for operational production of
foundation sea surface temperature and ice concentration analyses, Remote
Sens., 12, 1–20, https://doi.org/10.3390/rs12040720, 2020. a
Grimaldi, C. M., Lowe, R. J., Benthuysen, J. A., Cuttler, M. V. W., Green, R. H., Radford, B., Ryan, N., and Gilmour, J.: Hydrodynamic drivers of fine-scale connectivity within a coral reef atoll, Limnol.
Oceanogr., 67, 2204–2217, https://doi.org/10.1002/lno.12198, 2022. a, b
Guinehut, S., Dhomps, A.-L., Larnicol, G., and Le Traon, P.-Y.: High resolution 3-D temperature and salinity fields derived from in situ and satellite observations, Ocean Sci., 8, 845–857, https://doi.org/10.5194/os-8-845-2012, 2012. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay,
P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5
global reanalysis, Q. J. Roy. Meteor. Soc.,
146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a, b
Hoyer, S. and Hamman, J.: xarray: N-D labeled Arrays and Datasets in Python,
J. Open Research Softw., 5, 10, https://doi.org/10.5334/jors.148, 2017. a
Hunter, J. D.: Matplotlib: A 2D Graphics Environment, Comput. Sci. Eng., 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Jackett, D. R. and Mcdougall, T. J.: Minimal Adjustment of Hydrographic
Profiles to Achieve Static Stability, J. Atmos. Ocean. Tech., 12, 381–389,
https://doi.org/10.1175/1520-0426(1995)012<0381:MAOHPT>2.0.CO;2, 1995. a
Jones, W. and Launder, B.: The prediction of laminarization with a
two-equation model of turbulence, Int. J. Heat Mass
Transf., 15, 301–314, https://doi.org/10.1016/0017-9310(72)90076-2, 1972. a
Jullien, S., Caillaud, M., Benshila, R., Bordois, L., Cambon, G., Dumas, F., Le Gentil, S., Lemarié, F., Marchesiello, P., Theetten, S., Dufois, F., Le Corre, M., Morvan, G., Le Gac, S., Gula, J., and Pianezze, J.: CROCO Technical and Numerical Documentation (1.3), Zenodo [code], https://doi.org/10.5281/zenodo.7400922, 2022. a, b
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. a, b
Laurindo, L. C., Mariano, A. J., and Lumpkin, R.: An improved near-surface
velocity climatology for the global ocean from drifter observations,
Deep-Sea Res. Pt. I, 124, 73–92,
https://doi.org/10.1016/j.dsr.2017.04.009, 2017. a
Lellouche, J.-M., Greiner, E., Bourdallé Badie, R., Garric, G., Melet,
A., Drévillon, M., Bricaud, C., Hamon, M., Le Galloudec, O., Regnier,
C., Candela, T., Testut, C.-E., Gasparin, F., Ruggiero, G., Benkiran, M.,
Drillet, Y., and Le Traon, P.-Y.: The Copernicus Global 1/12∘
Oceanic and Sea Ice GLORYS12 Reanalysis, Front. Earth Sci., 9,
1–27, https://doi.org/10.3389/feart.2021.698876, 2021. a, b, c
Li, J., Knapp, D. E., Fabina, N. S., Kennedy, E. V., Larsen, K., Lyons, M. B.,
Murray, N. J., Phinn, S. R., Roelfsema, C. M., and Asner, G. P.: A global
coral reef probability map generated using convolutional neural networks,
Coral Reefs, 39, 1805–1815, https://doi.org/10.1007/s00338-020-02005-6, 2020. a
Lowry, R., Pugh, D., and Wijeratne, E.: Observations of Seiching and Tides
Around the Islands of Mauritius and Rodrigues, Western Indian Ocean J. Marine Sci., 7, 15–28, https://doi.org/10.4314/wiojms.v7i1.48251, 2008. a
Lumpkin, R. and Centurioni, L.: Global Drifter Program quality-controlled
6-hour interpolated data from ocean surface drifting buoys., Tech. rep.,
NOAA National Centers for Environmental Information,
https://doi.org/10.25921/7ntx-z961, 2019. a
Mayer, L., Jakobsson, M., Allen, G., Dorschel, B., Falconer, R., Ferrini, V., Lamarche, G., Snaith, H., and Weatherall, P.: The Nippon Foundation–GEBCO Seabed 2030 Project: The Quest to See the World's Oceans Completely Mapped by 2030, Geosciences, 8, 63, https://doi.org/10.3390/geosciences8020063, 2018. a
Mayorga-Adame, C. G., Ted Strub, P., Batchelder, H. P., and Spitz, Y. H.:
Characterizing the circulation off the Kenyan-Tanzanian coast using an ocean
model, J. Geophys. Res.-Oceans, 121, 1377–1399,
https://doi.org/10.1002/2015JC010860, 2016. a
Mayorga-Adame, C. G., Batchelder, H. P., and Spitz, Y. H.: Modeling larval
connectivity of coral reef organisms in the Kenya-Tanzania region, Front. Marine Sci., 4, 92, https://doi.org/10.3389/fmars.2017.00092, 2017. a
McPhaden, M. J., Meyers, G., Ando, K., Masumoto, Y., Murty, V. S.,
Ravichandran, M., Syamsudin, F., Vialard, J., Yu, L., and Yu, W.: RAMA: The
research moored array for African-Asian-Australian monsoon analysis and
prediction, B. Am. Meteorol. Soc., 90, 459–480,
https://doi.org/10.1175/2008BAMS2608.1, 2009. a
Miramontes, E., Penven, P., Fierens, R., Droz, L., Toucanne, S., Jorry, S. J.,
Jouet, G., Pastor, L., Silva Jacinto, R., Gaillot, A., Giraudeau, J., and
Raisson, F.: The influence of bottom currents on the Zambezi Valley
morphology (Mozambique Channel, SW Indian Ocean): In situ current
observations and hydrodynamic modelling, Marine Geol., 410, 42–55,
https://doi.org/10.1016/j.margeo.2019.01.002, 2019. a
Monismith, S. G., Barkdull, M. K., Nunome, Y., and Mitarai, S.: Transport
Between Palau and the Eastern Coral Triangle: Larval Connectivity or Near
Misses, Geophys. Res. Lett., 45, 4974–4981,
https://doi.org/10.1029/2018GL077493, 2018. a
Painter, S. C.: The biogeochemistry and oceanography of the East African
Coastal Current, Prog. Oceanogr., 186, 102374,
https://doi.org/10.1016/j.pocean.2020.102374, 2020. a
Poje, A. C., Haza, A. C., Özgökmen, T. M., Magaldi, M. G., and
Garraffo, Z. D.: Resolution dependent relative dispersion statistics in a
hierarchy of ocean models, Ocean Model., 31, 36–50,
https://doi.org/10.1016/j.ocemod.2009.09.002, 2010. a
Pugh, D.: Sea levels at Aldabra Atoll, Mombasa and Mahé, western
equatorial Indian Ocean, related to tides, meteorology and ocean
circulation, Deep-Sea Res. Pt. A, 26,
237–258, https://doi.org/10.1016/0198-0149(79)90022-0, 1979. a
Ridderinkhof, H., Van Der Werf, P. M., Ullgren, J. E., Van Aken, H. M.,
Van Leeuwen, P. J., and De Ruijter, W. P.: Seasonal and interannual
variability in the Mozambique Channel from moored current observations,
J. Geophys. Res.-Oceans, 115, C6, https://doi.org/10.1029/2009JC005619,
2010. a
Rio, M. H., Mulet, S., and Picot, N.: Beyond GOCE for the ocean circulation
estimate: Synergetic use of altimetry, gravimetry, and in situ data provides
new insight into geostrophic and Ekman currents, Geophys. Res.
Lett., 41, 8918–8925, https://doi.org/10.1002/2014GL061773, 2014. a, b
Schott, F. A. and McCreary, J. P.: The monsoon circulation of the Indian
Ocean, Prog. Oceanogr., 51, 1–123,
https://doi.org/10.1016/S0079-6611(01)00083-0, 2001. a
Schott, F. A., Xie, S. P., and McCreary, J. P.: Indian ocean circulation and
climate variability, Rev. Geophys., 47, 1–46,
https://doi.org/10.1029/2007RG000245, 2009. a
Schulzweida, U.: CDO User Guide, Zenodo [code], https://doi.org/10.5281/zenodo.7112925, 2022. a
Shao-Jun, Z., Yu-Hong, Z., Wei, Z., Jia-Xun, L., and Yan, D.: Typical Surface
Seasonal Circulation in the Indian Ocean Derived from Argos Floats,
Atmos. Ocean. Sci. Lett., 5, 329–333,
https://doi.org/10.1080/16742834.2012.11447015, 2012. a
Shchepetkin, A. F. and McWilliams, J. C.: A method for computing horizontal
pressure-gradient force in an oceanic model with a nonaligned vertical
coordinate, J. Geophys. Res.-Oceans, 108, 1–34,
https://doi.org/10.1029/2001jc001047, 2003. 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
Smagorinsky, J.: GENERAL CIRCULATION EXPERIMENTS WITH THE PRIMITIVE
EQUATIONS, Mon. Weather Rev., 91, 99–164,
https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2, 1963. a
Swallow, J., Fieux, M., and Schott, F.: The boundary currents east and north
of Madagascar: 1. Geostrophic currents and transports, J. Geophys. Res., 93, 4951, https://doi.org/10.1029/jc093ic05p04951, 1988. a
Swallow, J. C., Schott, F., and Fieux, M.: Structure and transport of the East
African Coastal Current, J. Geophys. Res., 96, 22245,
https://doi.org/10.1029/91jc01942, 1991. a
Thompson, D. M., Kleypas, J., Castruccio, F., Curchitser, E. N., Pinsky, M. L.,
Jönsson, B., and Watson, J. R.: Variability in oceanographic barriers
to coral larval dispersal: Do currents shape biodiversity?, Prog. Oceanogr., 165, 110–122, https://doi.org/10.1016/j.pocean.2018.05.007, 2018. a
Tozer, B., Sandwell, D. T., Smith, W. H., Olson, C., Beale, J. R., and Wessel,
P.: Global Bathymetry and Topography at 15 Arc Sec: SRTM15+, Earth
Space Sci., 6, 1847–1864, https://doi.org/10.1029/2019EA000658, 2019. a, b
van der Velden, E.: CMasher: Scientific colormaps for making accessible,
informative and `cmashing' plots, J. Open Source Softw., 5, 2004,
https://doi.org/10.21105/joss.02004, 2020. 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, 121, 49–75,
https://doi.org/10.1016/j.ocemod.2017.11.008, 2018. a
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T.,
Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J.,
van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N.,
Nelson, A. R., Jones, E., Kern, R., Larson, E., Carey, C., Polat, I., Feng,
Y., Moore, E. W., VanderPlas, J., Laxalde, D., Perktold, J., Cimrman, R.,
Henriksen, I., Quintero, E. A., Harris, C. R., Archibald, A. M., Ribeiro,
A. H., Pedregosa, F., van Mulbregt, P., Vijaykumar, A., Bardelli, A. P.,
Rothberg, A., Hilboll, A., Kloeckner, A., Scopatz, A., Lee, A., Rokem, A.,
Woods, C. N., Fulton, C., Masson, C., Häggström, C., Fitzgerald,
C., Nicholson, D. A., Hagen, D. R., Pasechnik, D. V., Olivetti, E., Martin,
E., Wieser, E., Silva, F., Lenders, F., Wilhelm, F., Young, G., Price, G. A.,
Ingold, G. L., Allen, G. E., Lee, G. R., Audren, H., Probst, I., Dietrich,
J. P., Silterra, J., Webber, J. T., Slavič, J., Nothman, J., Buchner,
J., Kulick, J., Schönberger, J. L., de Miranda Cardoso, J. V., Reimer,
J., Harrington, J., Rodríguez, J. L. C., Nunez-Iglesias, J., Kuczynski,
J., Tritz, K., Thoma, M., Newville, M., Kümmerer, M., Bolingbroke, M.,
Tartre, M., Pak, M., Smith, N. J., Nowaczyk, N., Shebanov, N., Pavlyk, O.,
Brodtkorb, P. A., Lee, P., McGibbon, R. T., Feldbauer, R., Lewis, S., Tygier,
S., Sievert, S., Vigna, S., Peterson, S., More, S., Pudlik, T., Oshima, T.,
Pingel, T. J., Robitaille, T. P., Spura, T., Jones, T. R., Cera, T., Leslie,
T., Zito, T., Krauss, T., Upadhyay, U., Halchenko, Y. O., and
Vázquez-Baeza, Y.: SciPy 1.0: fundamental algorithms for scientific
computing in Python, Nature Methods, 17, 261–272,
https://doi.org/10.1038/s41592-019-0686-2, 2020. a
Vogt-Vincent, N.: WINDS validation scripts and run files, Zenodo [code],
https://doi.org/10.5281/zenodo.7548260, 2023a. a
Vogt-Vincent, N.: Supplementary Video 1: One year of SST from WINDS-C, https://youtu.be/txwekFS_G5Q (last access: 14 February 2023), Youtube [video], 2023b. a
Vogt-Vincent, N. and Johnson, H.: WINDS-C: A
Vogt-Vincent, N. and Johnson, H.: WINDS-M: A
Voldsund, A., Aguiar-González, B., Gammelsrød, T., Krakstad, J. O.,
and Ullgren, J.: Observations of the east Madagascar current system:
Dynamics and volume transports, J. Marine Res., 75, 531–555,
https://doi.org/10.1357/002224017821836725, 2017. a
Wessel, P. and Smith, W. H. F.: A global, self-consistent, hierarchical,
high-resolution shoreline database, J. Geophys. Res.-Sol.
Ea., 101, 8741–8743, https://doi.org/10.1029/96jb00104, 1996. a
Short summary
Ocean currents transport things over large distances across the ocean surface. Predicting this transport is key for tackling many environmental problems, such as marine plastic pollution and coral reef resilience. However, doing this requires a good understanding ocean currents, which is currently lacking. Here, we present and validate state-of-the-art simulations for surface currents in the southwestern Indian Ocean, which will support future marine dispersal studies across this region.
Ocean currents transport things over large distances across the ocean surface. Predicting this...
