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Multivariate Upstream Kuroshio Transport (UKT) prediction and targeted observation sensitive area identification of UKT seasonal reduction Ocean Model. (IF 3.2) Pub Date : 2024-03-11 Bin Mu, Yifan Yang-Hu, Bo Qin, Shijin Yuan
Variation and seasonal reduction in the Upstream Kuroshio Transport (UKT) have important impacts on surrounding climate and oceanic circulation systems. Therefore, reliable UKT prediction is crucial. In this paper, we propose an intelligent UKT prediction model, KuroshioNet, which is firstly pre-trained with simulation data generated by the Regional Ocean Modeling System (ROMS) and then fine-tuned
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Assimilation of New Rocket Dropsonde Data Using WRFDA and Its Impact on Numerical Simulations of Typhoon NORU Ocean Model. (IF 3.2) Pub Date : 2024-03-11 Yu Wei, Yu Xin, Bingke Zhao, Xiaoqin Lu, Shuai Zhang, Lei Zhang, jingyao Luo, Yonghang Chen, Qiong Liu, Tongqiang Liu, Yi Zheng
On September 26 at 2100 UTC and September 27 at 0900 and 2300 UTC, three rockets platform carrying dropsondes (TFTC-400) devices were launched off the east coast of Hainan Island to conduct a launch experiment aimed at detecting Typhoon NORU (2216). The experiment yielded valuable data that were subsequently analyzed to ascertain temperatures, wind speeds, and relative humidity in the atmosphere. Of
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BinWaves: An additive hybrid method to downscale directional wave spectra to nearshore areas Ocean Model. (IF 3.2) Pub Date : 2024-03-09 Laura Cagigal, Fernando J. Méndez, Alba Ricondo, David Gutiérrez-Barceló, Cyprien Bosserelle, Ron Hoeke
Accurate and timely early warning systems are a vital component in mitigating the risks faced by coastal communities worldwide. Unlike aggregated wave parameters, information extracted from the complete directional wave spectra is often indispensable in the development of such systems in multi-modal environments, such as remote islands, where concurrent waves from various directions are common. Dynamically
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Deep learning-based forecasting model for chlorophyll-a response to tropical cyclones in the Western North Pacific Ocean Model. (IF 3.2) Pub Date : 2024-03-05 Haobin Cen, Guoqing Han, Xiayan Lin, Yu Liu, Han Zhang
Tropical cyclones cause increases in sea surface chlorophyll-a concentration, which is important for studying variations in the regional marine environment. Precisely forecasting the variations of sea surface chlorophyll-a concentration induced by tropical cyclones remains a challenge. In this research, a bidirectional long short-term memory (BiLSTM) neural network deep learning model was applied to
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Accuracy and stability analysis of horizontal discretizations used in unstructured grid ocean models Ocean Model. (IF 3.2) Pub Date : 2024-02-20 Fabricio Rodrigues Lapolli, Pedro da Silva Peixoto, Peter Korn
One important tool at our disposal to evaluate the robustness of Global Circulation Models (GCMs) is to understand the horizontal discretization of the dynamical core under a shallow water approximation. Here, we evaluate the accuracy and stability of different methods used in, or adequate for, unstructured ocean models considering shallow water models. Our results show that the schemes have different
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A numerical study of multiscale current effects on waves in the northern South China Sea Ocean Model. (IF 3.2) Pub Date : 2024-02-20 Liqun Jia, Renhao Wu, Fei Shi, Bo Han, Qinghua Yang
The current effects on waves (CEW) are of interest owing to their importance for our understanding of wave dynamics. However, there is a lack of research on the effects of multiscale currents on waves in the northern South China Sea. In this study, we conducted a series of process-oriented numerical experiments to quantitatively investigate the characteristics of multiscale currents and their effects
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SHyTCWaves: A stop-motion hybrid model to predict tropical cyclone induced waves Ocean Model. (IF 3.2) Pub Date : 2024-02-15 Sara O. van Vloten, Laura Cagigal, Beatriz Pérez-Díaz, Ron Hoeke, Fernando J. Méndez
Waves produced by tropical cyclones (TCs) can be estimated using non-stationary wave models forced with time-varying wind fields. However, dynamical simulations are time and computationally demanding at regional-scale domains since high temporal and spatial resolutions are required to correctly simulate TC-induced wave propagation processes. Applications such as early warning systems, coastal risk
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Generalized structure of the group method of data handling for modeling iceberg drafts Ocean Model. (IF 3.2) Pub Date : 2024-02-13 Hamed Azimi, Hodjat Shiri, Masoud Mahdianpari
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Spurious internal wave generation during data assimilation in eddy resolving ocean model simulations Ocean Model. (IF 3.2) Pub Date : 2024-02-10 Keshav J. Raja, Maarten C. Buijsman, Alexandra Bozec, Robert W. Helber, Jay F. Shriver, Alan Wallcraft, Eric P. Chassignet, Brian K. Arbic
Data assimilation (DA) combines observational data and the dynamical ocean model to forecast the ocean state in a matter that is not possible from either observations or models by themselves. However, the incorporation of data-derived corrections into the model introduces the potential to disrupt the dynamical balance of the model state, leading to initialization shocks. These shocks arise as the model
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A simple and transparent method for improving the energetics and thermodynamics of seawater approximations: Static energy asymptotics (SEA) Ocean Model. (IF 3.2) Pub Date : 2024-02-09 Rémi Tailleux, Thomas Dubos
The static energy encodes all possible information about the thermodynamics and potential energy (and all related forces) of stratified geophysical fluids. In this paper, we develop a systematic methodology, called static energy asymptotics, that exploits this property for constructing energetically and thermodynamically consistent sound-proof approximations of the equations of motion. By approximating
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Tidal effects on dynamics and freshwater transport of a medium-scale river plume with multiple outlets Ocean Model. (IF 3.2) Pub Date : 2024-02-08 Xiaolong Zong, Xuan Cheng, Shuwen Zhang, Qiang Lian, Fangjing Deng, Zhaoyun Chen
Tides play a crucial role in regulating the dispersal and dynamics of a river plume. However, the impact of tides on the dynamics and transport of freshwater in a medium-scale river plume, particularly with multiple outlets, is still not well understood. Using the Hanjiang River Plume in the northern South China Sea as an example, we analyze the momentum and volume of the plume based on salinity space
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Dispersion diagrams of linear damped waves on the equatorial beta plane Ocean Model. (IF 3.2) Pub Date : 2024-02-02 P. Amol, D. Shankar
The linear equations of motion are solved to obtain dispersion diagrams with Rayleigh friction () and Laplacian friction (), the latter being solved numerically. Laplacian friction is more efficient at eliminating the short-wavelength Rossby waves, whereas Rayleigh friction is more effective at dissipating long-wavelength Rossby waves. For Rayleigh friction, short-wavelength Rossby waves do not exist
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Predicting temporal and spatial 4-D ocean temperature using satellite data based on a novel deep learning model Ocean Model. (IF 3.2) Pub Date : 2024-02-02 Yuliang Liu, Lin Zhang, Wei Hao, Lu Zhang, Limin Huang
The prediction of ocean temperature using sea surface data is crucial for studying ocean-related events and climate change. However, current temperature predictions mainly focus on surface data and rarely consider the temporal relationship of ocean temperature. In this study, we propose a novel deep-learning model to predict ocean temperature for the next two months, which fully considers both temporal
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Study of the tidal dynamics in the Southwestern Atlantic Continental Shelf based on data assimilation Ocean Model. (IF 3.2) Pub Date : 2024-02-01 Matías G. Dinápoli, Claudia G. Simionato
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Bias correction of operational storm surge forecasts using Neural Networks Ocean Model. (IF 3.2) Pub Date : 2024-02-01 Paulina Tedesco, Jean Rabault, Martin Lilleeng Sætra, Nils Melsom Kristensen, Ole Johan Aarnes, Øyvind Breivik, Cecilie Mauritzen, Øyvind Sætra
Storm surges can give rise to extreme floods in coastal areas. The Norwegian Meteorological Institute (MET Norway) produces 120 h regional operational storm surge forecasts along the coast of Norway based on the Regional Ocean Modeling System (ROMS), using a model setup called Nordic4-SS. Despite advances in the development of models and computational capabilities, forecast errors remain large enough
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CODAR data assimilation into an integrated ocean forecasting system for the Brazilian Southeastern coast Ocean Model. (IF 3.2) Pub Date : 2024-02-01 Raquel Toste, Carina Stefoni Böck, Maurício Soares da Silva, Nilton Oliveira Moraes, Anderson Elias Soares, Douglas Medeiros Nehme, Luiz Paulo de Freitas Assad, Luiz Landau, Fernando Barreto, Carlos Leandro da Silva Júnior
Near real-time surface current measurements from shore-based high-frequency (HF) radars have increasingly proved to be an essential observation for ocean data assimilation (DA) into operational forecasting systems. For the first time in Brazil, a high-resolution operational system was developed assimilating HF ocean currents data. The system comprises a well known ocean model, the Regional Ocean Modeling
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A deep learning-based bias correction model for Arctic sea ice concentration towards MITgcm Ocean Model. (IF 3.2) Pub Date : 2024-01-28 Shijin Yuan, Shichen Zhu, Xiaodan Luo, Bin Mu
Accurate prediction of Arctic sea ice is essential for ship navigation. The numerical forecast is an important method to predict sea ice. However, currently, it has significant bias from observation data. In this paper, we propose a deep learning-based bias correction model, Ice-BCNet, to post-process the weekly sea ice concentration (SIC) forecast data of MITgcm to improve its accuracy. Different
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The relationship between linearised 3D and 2DH models for tidally dominated shallow waters Ocean Model. (IF 3.2) Pub Date : 2024-01-24 Marco P. Rozendaal, Yoeri M. Dijkstra, Henk M. Schuttelaars
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Impact of tropical cyclones on the hydrodynamics and sediment dynamics of the radial sand ridge system in the southern Yellow Sea Ocean Model. (IF 3.2) Pub Date : 2024-01-18 Gang Yang, Chunhui Li, Yi Zhong, Xishan Pan, Chengyi Zhao, Changming Dong
The large radial sand ridge (RSR) system located in the southern Yellow Sea near the Jiangsu coast, China, is highly impacted by tropical cyclones (TCs). However, the temporal and spatial variations of sediment dynamics and associated morphodynamics in this region under the influence of TCs have been little explored due to the difficulty of implementing direct observation during these extreme events
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Quantifying numerical mixing in a tidally forced global eddy-permitting ocean model Ocean Model. (IF 3.2) Pub Date : 2024-01-18 A, l, e, x, , M, e, g, a, n, n
An ensemble of experiments based on a ¼° global NEMO configuration is presented, including tidally forced and non-tidal simulations, and using both the default z* geopotential vertical coordinate and the z∼ filtered Arbitrary Lagrangian-Eulerian coordinate, the latter being known to reduce numerical mixing. This is used to investigate the sensitivity of numerical mixing, and the resulting model drifts
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Investigation of multimodal wave climate using spectral partitioning and wave system tracking algorithms Ocean Model. (IF 3.2) Pub Date : 2024-01-17 Zhenjun Zheng, Guohai Dong, Xiaozhou Ma, Huawei Dong, Xuezhi Huang, Mingfu Tang
Typically, ocean waves comprise both wind sea and swell systems, each exhibiting different characteristics in terms of decay, propagation, and their impact on engineering. Distinguishing between wind sea and short/long swell systems is critical for both scientific research and engineering applications, such as climate assessment, harbor agitation, and structural design, which has led to a growing interest
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Characterization and future projection of marine heatwaves under climate change in the South China Sea Ocean Model. (IF 3.2) Pub Date : 2024-01-13 Wenjin Sun, Yifei Yang, Yindi Wang, Jingsong Yang, Jinlin Ji, Changming Dong
Marine heatwaves (MHWs) are widely recognized as prolonged periods of significantly elevated sea surface temperatures, leading to substantial adverse impacts on marine ecosystems. However, a comprehensive understanding of their characteristics and potential changes under climate change in the South China Sea (SCS, 0 ∼ 25°N, 105 ∼ 125°E) remains insufficient. Here, utilizing the OISST V2.0 reanalysis
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Empirical-singular-wavelet based machine learning models for sea level forecasting in the bosphorus strait: A performance analysis Ocean Model. (IF 3.2) Pub Date : 2024-01-13 Elif Kartal, Abdüsselam Altunkaynak
Forecasting sea level is significant for sustainable water supply management, flood mitigation, shoreline maintenance, ecological sustainability, and economic advancement. In this study, a novel approach that incorporates decomposition methods with machine learning algorithms is presented. The objective is to enhance the accuracy of sea level predictions by tackling the challenges associated with sea
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Application of deep learning in estimating the convective mixing induced by brine rejection Ocean Model. (IF 3.2) Pub Date : 2024-01-10 Xiaoqian Gao, Guoqing Han, Wenjin Sun, Shuyi Zhou, Wenhong Xie, Haobin Cen, Jinlin Ji, Haili Wang, Changming Dong
The open-water deep convection induced by brine rejection constitutes a primary process for deep water formation in high latitudes, playing a critical role in the global thermohaline circulation. Proper parameterization of subgrid-scale convective salt plumes arising from brine rejection is crucial for improving climate model simulations of ocean convection. Traditional physically driven parameterization
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Application of data-driven mixing parameterization scheme in a regional ocean model Ocean Model. (IF 3.2) Pub Date : 2024-01-09 Qingfeng Feng, Guoqing Han, Yu Liu, Xiayan Lin, Bo Li, Xiaoqian Gao, Changming Dong, Yinghui He, Haili Wang
In this study, based on the data-driven parameterization proposed in previous studies, we implemented a data-driven vertical turbulence parameterization scheme (backpropagation neural network, BPNN) into a regional ocean model and compared the simulation results with those obtained using the traditional physics-driven scheme (K-profile parameterization, KPP). The Kuroshio-Oyashio Confluence Region
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Spatiotemporal wave forecast with transformer-based network: A case study for the northwestern Pacific Ocean Ocean Model. (IF 3.2) Pub Date : 2024-01-07 Yong Liu, Wenfang Lu, Dong Wang, Zhigang Lai, Chao Ying, Xinwen Li, Ying Han, Zhifeng Wang, Changming Dong
The forecast of ocean waves relies mostly on complex dynamic-based models, which are expensive in computation and demanding in professional skills to run. Diverse deep learning methods have been proposed to tackle this problem, yet the architecture of Transformer (i.e., the self-attention) was seldom tested for such a learning problem. To bridge this gap, we apply a state-of-the-art spatiotemporal
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Lagrangian and Eulerian modelling of river plumes in the Great Barrier Reef system, Australia Ocean Model. (IF 3.2) Pub Date : 2024-01-04 Saima Aijaz, Frank Colberg, Gary B. Brassington
In this paper, we describe methods to verify the adequacy and accuracy of Lagrangian particles from a Lagrangian model to reproduce the concentrations of a passive tracer from an Eulerian-model in river plumes. The modelling simulates plumes from two major rivers discharging in the Great Barrier Reef (GBR), Australia, under real-world scenarios. The study has been a part of a major project to aid in
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Multi-scale free oscillations and resonances over the continental shelf of the East China Sea from the 2011 Tohoku-Oki tsunami Ocean Model. (IF 3.2) Pub Date : 2024-01-03 Peitao Wang, Wei Lu, Yuchen Wang, Zongchen Wang, Jingming Hou, Lining Sun
A number of coastal tide gauges and offshore Deep-ocean Assessment and Reporting of Tsunamis (DART) buoys across the Pacific Basin recorded persistent oscillations excited by the 2011 Tohoku-Oki tsunami. The hazardous persistent oscillations prompted authorities to maintain a tsunami warning for dozens of hours. Tsunami waves reached the eastern China coast about five hours after the earthquake. The
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The sensitivity of the equatorial pacific ODZ to particulate organic matter remineralization in a climate model under pre-industrial conditions Ocean Model. (IF 3.2) Pub Date : 2023-12-27 Paul Lerner, Anastasia Romanou, David Nicholson, Maxwell Kelley, Reto Ruedy, Gary Russell
Marine oxygen plays a fundamental role in regulating the transfer of organic carbon and nutrients to their dissolved inorganic forms, serving as the terminal electron acceptor for heterotrophic respiration. Oxygen can become limiting to these processes in coastal and open-ocean oxygen deficient zones (ODZs). The maintenance of ODZs depends on the balance between physical processes such as ventilation
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Improving wave height prediction accuracy with deep learning Ocean Model. (IF 3.2) Pub Date : 2023-12-27 Jie Zhang, Feng Luo, Xiufeng Quan, Yi Wang, Jian Shi, Chengji Shen, Chi Zhang
A novel convolutional neural network-long short-term memory (CNN-LSTM) model is proposed for wave height prediction. The model effectively extracts relevant features such as wind speed, wind direction, wave height, latitude, and longitude. The proposed model outperforms traditional machine learning algorithms such as multi-layer perceptron (MLP), support vector machine (SVM), random forest and LSTM
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Examining Antarctic sea ice bias sensitivity in the multi-variate parameter space using a global coupled climate modelling system Ocean Model. (IF 3.2) Pub Date : 2023-12-24 S. Schroeter, P.A. Sandery
Coupled global numerical climate models (GCMs) typically underestimate mean Antarctic sea ice area and extent, particularly during the austral summer months, contributing to uncertainties in climate prediction. This study examines the climatological behaviour of Antarctic sea ice in a coupled GCM in the multivariate sea ice model parameter space. Individual parameters dominate the ice response in different
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Description of FIO-ESM version 2.1 and evaluation of its sea ice simulations Ocean Model. (IF 3.2) Pub Date : 2023-12-18 Qi Shu, Fangli Qiao, Jiping Liu, Ying Bao, Zhenya Song
To improve Arctic sea ice simulations by the First Institute of Oceanography–Earth System Model (FIO–ESM), the model version has been updated from FIO–ESM v2.0 to FIO–ESM v2.1 by upgrading its sea ice component from Los Alamos Sea–Ice Model (CICE) version 4.0 (CICE4.0) to CICE6.0, and improving the ice–ocean heat exchange process from a two–equation boundary condition parameterization to a more realistic
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Improving wave modeling performance by incorporating wave-generated turbulence dissipation and improved post-breaking spectrum Ocean Model. (IF 3.2) Pub Date : 2023-12-23 Fuwei Wang, Yongzeng Yang, Xunqiang Yin, Xingjie Jiang, Meng Sun
The wave-generated turbulence dissipation term together with the improved post-breaking spectrum term proposed in this paper are incorporated in the MASNUM wave model as new dissipation terms. To compare the performance of these terms with the previous dissipation term in wave simulation, comprehensive validations of the simulated results were conducted against satellite data and NDBC buoy data on
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Effect of the different stratification changes along the two sides of a typhoon track on near-inertial energy propagation Ocean Model. (IF 3.2) Pub Date : 2023-12-21 Xingshang Qian, Guanghong Liao, Lei Zhou, Juncheng Xie
The -effect and mesoscale vorticity are considered the two important mechanisms guiding the downward propagation of near-inertial energy (NIE), while the influence of stratification is often neglected. In this study, the “heat pumping” and “cold suction” effects of Typhoon Kalmaegi on ocean stratification were analyzed. Enhanced stratification accelerated the vertical propagation of near-inertial waves
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Evolution of wave directional properties in sea ice Ocean Model. (IF 3.2) Pub Date : 2023-12-20 Alberto Alberello, Emilian I. Părău, Qingxiang Liu, Francesca De Santi
Ocean waves and sea ice properties are intimately linked in the marginal ice zone (MIZ), nevertheless a definitive modelling paradigm for the wave attenuation in the MIZ is missing. The evolution of wave directional properties in the MIZ is a proxy for the main attenuation mechanism but paucity of measurements and disagreement between them contributed to current uncertainty. Here we provide an analytical
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The Impacts of Air-Sea Fluxes and Model Resolution on Seasonal and Inter-Annual Variability of the Atlantic Meridional Overturning Circulation across the OSNAP West Section Ocean Model. (IF 3.2) Pub Date : 2023-12-17 Pouneh Hoshyar, Clark Pennelly, Paul G. Myers
The present study investigates the Atlantic Meridional Overturning Circulation (AMOC) in the sub-polar North Atlantic. Despite the identification of a weaker AMOC across the OSNAP (Overturning in the Subpolar North Atlantic Program) West section, low-resolution models have continuously overestimated the subpolar AMOC link to the Labrador Sea Water mass formation, underscoring the need for a deeper
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Representing uncertainty in limited-area data assimilating ocean models Ocean Model. (IF 3.2) Pub Date : 2023-12-13 Paul A. Sandery, Emlyn Jones, David Griffin
A limited-area ocean prediction system is developed to acquire forecast error covariances related to uncertainty in atmospheric forcing and turbulent mixing using perturbed model parameters within an Ensemble Kalman Filter (EnKF). The system performs sequential data assimilation delivering realistic ocean state estimation and forecasts. It is initialised to observations using the EnKF, the hybrid-EnKF
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Reynolds-averaged Navier-Stokes simulation of nearshore Langmuir circulation and the formation of oil-particle aggregates Ocean Model. (IF 3.2) Pub Date : 2023-12-16 J.J. Peñaloza-Gutierrez, A.E. Tejada-Martínez, M.C. Boufadel
Langmuir turbulence in the inner shelf coastal ocean is characterized by Langmuir circulation (LC) or cells that can span the full depth of unstratified water columns. A Reynolds-averaged Navier-Stokes (RANS) simulation strategy resolving full-depth LC coupled with an oil-particle aggregate (OPA) formation model is introduced. It is seen that full-depth LC generated by wind and waves under storm conditions
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Weak interannual variability of sea–air carbon flux in the Tropical Pacific Ocean simulated by CMIP6 models Ocean Model. (IF 3.2) Pub Date : 2023-12-14 YangChun Li, YuJie Jing, YongFu Xu
Air–sea carbon fluxes (FCO2) simulated by 20 CMIP6 models in the pre-industrial control experiments are analyzed. 13 models can simulate the dominant role of the equatorial Pacific (EP) in the interannual variation of global FCO2, which is related to ENSO. Compared with CMIP5, CMIP6 has improved the simulation performance of interannual variation of global FCO2, while for the simulation of FCO2 in
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Hydrodynamic responses of estuarine bays along the Texas-Louisiana coast during Hurricane Harvey Ocean Model. (IF 3.2) Pub Date : 2023-12-10 Wei Huang, Fei Ye, Y. Joseph Zhang, Jiabi Du, Kyeong Park, Hao-Cheng Yu, Zhengui Wang
Hurricane Harvey (2017) delivered an extraordinarily large amount of freshwater, sediment, and pollutants to the Texas-Louisiana (TX-LA) coastal ocean. While the impact of extreme precipitation and river discharge on the freshwater plumes has been investigated, the role of winds has rarely been addressed. Using a 3D creek-to-ocean mode, SCHISM, we conducted numerical experiments including/excluding
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Weather-type statistical downscaling for ocean wave climate in the Chinese marginal seas Ocean Model. (IF 3.2) Pub Date : 2023-12-02 Guangfeng Zhao, Delei Li, Paula Camus, Xinli Zhang, Jifeng Qi, Baoshu Yin
A comprehensive understanding of wave characteristics and their variability, based on reliable long-term wave data, is essential in the design, construction, operation and management in offshore and coastal applications. This study aims to downscale multivariate wave data in the Chinese marginal seas at different time scales by employing two weather-type statistical downscaling models. The calibration
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A semi-Lagrangian Splitting framework for the simulation of non-hydrostatic free-surface flows Ocean Model. (IF 3.2) Pub Date : 2023-11-30 Andreas Alexandris-Galanopoulos, George Papadakis, Kostas Belibassakis
Incorporation of the free-surface dynamics plays an important role in the numerical modelling of non-hydrostatic flows. In the present work a novel semi-Lagrangian splitting (SLS) scheme for the free-surface Euler system is proposed. Using the operator splitting technique, the three main components emerge: the multilayer Shallow Water Equations (mSWE) (enforcing the free-surface kinematics), the Vertical
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A deep-learning real-time bias correction method for significant wave height forecasts in the Western North Pacific Ocean Model. (IF 3.2) Pub Date : 2023-11-25 Wei Zhang, Yu Sun, Yapeng Wu, Junyu Dong, Xiaojiang Song, Zhiyi Gao, Renbo Pang, Boyu Guoan
Significant wave height (SWH) is one of the most important parameters characterizing ocean waves, and accurate numerical ocean wave forecasting is crucial for coastal protection and shipping. However, due to the randomness and nonlinearity of the wind fields that generate ocean waves and the complex interaction between wave and wind fields, current forecasts of numerical ocean waves have biases. In
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Improvement of sea ice thermodynamics with variable sea ice salinity and melt pond parameterizations in an OGCM Ocean Model. (IF 3.2) Pub Date : 2023-11-14 Takahiro Toyoda, Kei Sakamoto, Takenobu Toyota, Hiroyuki Tsujino, L. Shogo Urakawa, Yuma Kawakami, Akio Yamagami, Kensuke K. Komatsu, Goro Yamanaka, Tomonori Tanikawa, Rigen Shimada, Hideyuki Nakano
Enhanced representation of sea ice processes in ocean modeling studies is required for advancing our understanding and prediction of the climate variability. In the present study, we improved the sea ice thermodynamics in an OGCM by introducing processes for variable sea ice salinity and melt ponds on sea ice. The former affects the latent heat and conductivity of sea ice as well as the salt budget
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An “objective” definition of potential vorticity. Generalized evolution equation and application to the study of coastal upwelling instability Ocean Model. (IF 3.2) Pub Date : 2023-11-07 Yves Morel, Guillaume Morvan, Rachid Benshila, Lionel Renault, Jonathan Gula, Francis Auclair
In this paper, we propose a form for potential vorticity (PV), rescaled using the Lorenz’s rearranged density profile, the novelty being that we here take into account its time evolution. We argue this rescaled PV is more representative of the dynamics, in particular to evaluate the respective impact of mixing and friction on the generation of geostrophic circulation. The impact of mixing at global
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Quantification of hydrodynamic model sea level bias utilizing deep learning and synergistic integration of data sources Ocean Model. (IF 3.2) Pub Date : 2023-11-08 Vahidreza Jahanmard, Robinson Hordoir, Nicole Delpeche-Ellmann, Artu Ellmann
This study demonstrates the use of machine learning strategies to examine and quantify the bias that often exists in sea level data from hydrodynamic models. The sea level bias is considered to consist of two components: (i) hydrodynamic modelling errors due to numerical modelling limitations, and (ii) a bias related to the difference between vertical datums. The goal is to accurately quantify these
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Comprehensive characterization of Marine Heatwaves in a coastal Northern Humboldt Current System regional model over recent decades Ocean Model. (IF 3.2) Pub Date : 2023-10-28 Rodrigo Mogollón, Alice Pietri, Jorge Tam, François Colas
In this study, a high-resolution hydrodynamic model simulation was used to analyze the three-dimensional characteristics of marine heatwaves (MHWs) in the coastal region of the Northern Humboldt Current System (NHCS) over the period 2000–2019. Three distinct vertical layers were identified. The near-surface layer, extending down to 75 m depth, is identified as the region where both the maximum MHW
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Harmonic generation in Palu Bay, Indonesia Ocean Model. (IF 3.2) Pub Date : 2023-10-31 I. Magdalena, J.F. Pradharma, H.Q. Rif’atin, M. Farid
Harbor resonance, which occurs when an incoming wave’s period matches the natural period of the harbor, can be severely damaging to the surrounding areas. Using shallow water equations, we estimated the (natural) resonant period of a bay, particularly one with a hyperbolic-cosine squared bottom shape. There are two scenarios discussed: a constant-width harbor and a non-constant-width harbor. The resonant
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Modeling the long-term transport and fate of oil spilled from the 2021 A Symphony tanker collision in the Yellow Sea, China: Reliability of the stochastic simulation Ocean Model. (IF 3.2) Pub Date : 2023-10-30 Ruichen Cao, Zengrui Rong, Haibo Chen, Yi Liu, Lin Mu, Xianqing Lv
Coupled with a 3D hydrodynamic model, a well-established 3D oil spill model is used to simulate the transport and fate of oil spilled from the A Symphony oil tanker collision in the Yellow Sea on April 27, 2021. The model is first validated by airborne mini-SAR and shipborne X-band radar observation in a 30-day simulation. Subsequently, the model prediction capabilities are investigated over a longer
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On a probabilistic evolutionary approach to ocean modelling: From Lorenz-63 to idealized ocean models Ocean Model. (IF 3.2) Pub Date : 2023-10-20 Igor Shevchenko, Pavel Berloff
In this study we develop an alternative way to model the ocean reflecting the chaotic nature of ocean flows and uncertainty of ocean models — instead of making use of classical deterministic or stochastic differential equations we offer a probabilistic evolutionary approach (PEA) that capitalizes on the use of probabilistic dynamics in phase space. The main feature of the data-driven version of PEA
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Improving storm surge simulations by considering wave-steepness-dependent drag coefficient in the northern East China Sea Ocean Model. (IF 3.2) Pub Date : 2023-10-21 Zhao Li, Shuiqing Li, Po Hu, Xingru Feng, Dongxue Mo, Jian Li
The northern East China Sea (NECS) is a semienclosed basin that is frequently attacked by tropical cyclones (TCs), and the accompanied storm surges are huge threats to coastal regions. In this study, numerical simulations of storm surges in the NECS are performed in the impacts of wave-induced surface drag (wave drag) and wave radiation stress (wave setup). The wave drag is estimated using a wave-steepness-dependent
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Improvement of the sediment flux estimation in the Yangtze River Estuary with a GOCI data adjusted numerical model Ocean Model. (IF 3.2) Pub Date : 2023-10-21 Guohu Xie, Yang Zhang, Jia Liu, Huijie Xue, Jianzhong Ge, Xianqiang He, Wentao Ma, Fei Chai
Sediment flux (SF) in the estuary is vital to the coastal and estuarine environment, especially the morphodynamical and ecological processes. However, its quantitative estimation with high accuracy is difficult because it is controlled by complex mechanisms and multiple processes. This study corrects the seasonal variations of the simulated suspended sediment concentration (SSC) by using GOCI-derived
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Contribution of tropical cyclone induced waves to the mean and extreme wave climatology in the Bay of Bengal Ocean Model. (IF 3.2) Pub Date : 2023-10-20 Sohan Pal Meena, Neetu S, V. Adithyan, Imsangla Imchen
This paper examines the contribution of tropical cyclones (TCs) to the mean wave and the extreme wave climatology in the Bay of Bengal (BoB). To assess the impact of TCs on the wave activity in the BoB, we compare 40-years long WAVEWATCH III (WW3) numerical simulation with a twin experiment, where TC signatures are filtered out from the wind forcing dataset. Our experimental strategy of twin simulations
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The impact of rough topography on behaviors of mesoscale eddies as revealed by submesoscale resolving simulations Ocean Model. (IF 3.2) Pub Date : 2023-10-18 Kaiwen Zheng, Zhiwei Zhang, Wei Zhao, Jiwei Tian
Mesoscale eddies are ubiquitous in the world ocean and are a key factor in maintaining the global oceanic energy balance. Geophysical turbulence theory predicts that the eddy length scale should increase to Rhines scale as it inherits the inverse energy cascade from smaller scales that help to stabilize the ocean circulation system. However, satellite-observed mesoscale eddies are much smaller than
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Modelling secondary circulations in stratified bi-directional flows: A potential mechanism for flux transfer from lower to upper fluid layers Ocean Model. (IF 3.2) Pub Date : 2023-10-13 Manel Grifoll, Jarle Berntsen, Alan Cuthbertson
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Seasonal dynamics of water circulation and exchange flows in a shallow lagoon-inlet-coastal ocean system Ocean Model. (IF 3.2) Pub Date : 2023-10-12 Miaohua Mao, Meng Xia
A wave–current coupled, unstructured-grid, three-dimensional hydrodynamic model was applied to investigate the seasonal dynamics of the Maryland Coastal Bays system. The model's performance was validated successfully against hydrodynamic observations from the spring to fall of 2014, and the driving forces of water circulation and exchange flows were discussed. Results indicate that seasonal dynamics
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Combining uncertain machine learning predictions and numerical simulation results for the extreme value analysis of cyclone-induced wave heights – Application in Guadeloupe Ocean Model. (IF 3.2) Pub Date : 2023-09-28 Jeremy Rohmer, Andrea G. Filippini, Rodrigo Pedreros
Assessing return level RL (with return period typically ranging from 100 to 500 years) for extreme waves in cyclone-prone regions is often made problematic by the lack of sufficient representative samples to properly fit the extreme value probability distributions. Motivated by the Guadeloupe context (French West Indies), we address this problem when the wave numerical model is too expensive to be
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A numerical assessment of the dispersion of dissolved pollutants in the Arabian Gulf associated with the Barakah nuclear power plant Ocean Model. (IF 3.2) Pub Date : 2023-09-18 Oleksandr Nesterov, Yacine Addad, Sana Bilal, Emmanuel Bosc, Rachid Abida, Maryam Rashed Al Shehhi, Marouane Temimi
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On global wave height climatology and trends from multiplatform altimeter measurements and wave hindcast Ocean Model. (IF 3.2) Pub Date : 2023-09-17 Qingxiang Liu, Ian R. Young, Stefan Zieger, Agustinus Ribal, Shang-Min Long, Xianghui Dong, Zhenya Song, Changlong Guan, Alexander V. Babanin
Reliable estimates of ocean surface waves and their long-term global trends are fundamentally important for numerous ocean engineering and geophysical applications. Nonetheless, it is scientifically and technically demanding to accurately identify such relatively small trends [O(0.1−1) cm yr−1] from wave data currently available. In 2022, Young and Ribal demonstrated that by changing the calibration