Ocean Modelling最新文献

{"title":"Fourier limit in fluid mechanics, and link to the turbulence","authors":"Alexander V. Babanin","doi":"10.1016/j.ocemod.2025.102580","DOIUrl":"10.1016/j.ocemod.2025.102580","url":null,"abstract":"<div><div>Macroscopic fluids are considered continuous down to microscopic scales where they fail to be dense enough for separate particles to have sufficiently large number of collisions (interactions) over that scale. We argue that a similar limit applies to the characteristic fluid length scales in the Fourier space, defined by wavenumber k. At <span><math><mrow><mfrac><mrow><mstyle><mi>Δ</mi></mstyle><mi>k</mi></mrow><mi>k</mi></mfrac><mo>≪</mo><mn>1</mn></mrow></math></span>, the Fourier space cannot be regarded continuous, and at these scales the energy-density spectrum becomes discrete. We further note that in physical space, the particle centres cannot come closer to each other than their diameter, and within this volume the physical forces are of a completely different nature. Similarly, very different interactions can be expected if wave modes have wavenumbers closer than a threshold in the Fourier space. It is argued that the wavenumber space <span><math><mrow><mfrac><mrow><mstyle><mi>Δ</mi></mstyle><mi>k</mi></mrow><mi>k</mi></mfrac><mo>&lt;</mo><mn>1</mn><mo>/</mo><mn>400</mn></mrow></math></span> can be considered as a Fourier volume of wave mode k. It is the hypothesis of this paper that this volume of the Fourier modes is filled with background seed turbulence, - like the volume of solid particles in the physical space is filled with the matter. The wave energy between modes in the discrete wave spectrum is not missing, it is the energy of background turbulence, like internal energy of molecules of the moving solid particle. This turbulence seed energy is about 0.1 % of the energy of neighbouring wave modes as argued in this paper, and it can grow subject to instabilities. The unidirectional flow can be treated as a half-wave with wavelength twice the size of the phenomenon where the mean velocity defines kinetic energy, part of which goes to the seed turbulence. The depth (cross-length) of this flow is not an independent property and is proportional to ratio of the length and velocity scales all squared. In case of surface present, this depth is perpendicular to the surface and defines the length scale of the boundary layer.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"197 ","pages":"Article 102580"},"PeriodicalIF":3.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144572678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiation condition enforcement in linear free-surface wave modeling","authors":"Junhui Liu,&nbsp;Scott F. Bradford,&nbsp;Douglas A. Schwer,&nbsp;Ralph L. Fiedler","doi":"10.1016/j.ocemod.2025.102594","DOIUrl":"10.1016/j.ocemod.2025.102594","url":null,"abstract":"<div><div>Linear free-surface wave models must satisfy the radiation condition to avoid unphysical solutions. The radiation condition requires that the wave amplitude vanishes at infinite boundaries and waves propagate outward from the source location. The former requirement has received much attention in the literature, but the latter is often ignored. Linear-free surface waves at the deep-water condition are defined by dispersion curves that include two V shaped curves and an additional ring curve when the pulsation frequency is below a certain value. Constraints that enforce both requirements of the radiation condition have been developed and applied to wave solutions associated with each dispersion curve. The two requirements of the radiation condition produce the same constraint for the ring curve and one V shaped curve referred to as the Inner V curve. However, for the second V shaped curve referred to as the Outer V curve, satisfying the requirement of vanishing wave amplitude at infinite boundaries does not guarantee the outgoing condition. When the ring curve exists, this Outer V curve only generates ingoing waves. At higher pulsation frequencies, the dimensionless wavenumber component in the source moving direction should be smaller than the dimensionless frequency to satisfy both requirements of the rdiation conditions. Thus, models that only satisfy vanishing amplitude at infinite boundaries would include ingoing waves associated with this Outer V curve. The wave patterns that include ingoing waves are found to be oversensitive to a small deviation from the steady source motion. The ingoing waves may also affect predictions of the wave amplitude and the wave resistance of the ship.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"197 ","pages":"Article 102594"},"PeriodicalIF":3.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tidal estimates from sun-synchronous satellite altimeters in the Bohai Sea via an improved harmonic analysis model","authors":"Haidong Pan ,&nbsp;Dingqi Wang ,&nbsp;Junchuan Sun ,&nbsp;Tengfei Xu ,&nbsp;Zexun Wei","doi":"10.1016/j.ocemod.2025.102593","DOIUrl":"10.1016/j.ocemod.2025.102593","url":null,"abstract":"<div><div>Multi-satellite altimeters have greatly elevated our understanding of tidal dynamics around the globe. Among all publicly available satellite altimeters, the T/P-Jason series are widely considered as the core of diverse satellite-based tidal investigations. By contrast, sun-synchronous satellites only play auxiliary roles in previous studies mostly due to their pathological aliasing for tidal estimation. In this study, MHACS, an improved version of the classical harmonic analysis model utilizing the smooth nature of tidal admittances, is applied to estimate tidal constants from 24-year sun-synchronous ERS-Envisat-Saral (EES) series in the Bohai Sea. MHACS utilizes the intrinsic natural connections among major tidal constituents to overcome the restrictions of the Rayleigh criterion. Tricky K₁-P₁-Sa and K₂-Ssa pairs as well as S₂ tides in EES series are resolved by MHACS with regularization algorithms (i.e. ridge regression). Practical experiments in the Bohai Sea suggest that tidal estimates from the EES series through MHACS are in high agreement with the FES2014, with an average error of only 2.18 cm. Such consistency indicates the satisfactory performance of MHACS with ridge regression on processing the EES series. Although the proposed method has some limitations, it can potentially be a widely-used tool to extract tides from heterogeneous satellite altimeters including Sentinel series and Surface Water Ocean Topography (SWOT).</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"197 ","pages":"Article 102593"},"PeriodicalIF":3.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144662605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of a 3D unstructured grid model for the New York-New Jersey Harbor under different forcing sources","authors":"Kyungmin Park ,&nbsp;Y. Joseph Zhang ,&nbsp;Emanuele Di Lorenzo ,&nbsp;Gregory Seroka ,&nbsp;Ayumi Fujisaki-Manome ,&nbsp;Shachak Pe'eri ,&nbsp;Saeed Moghimi ,&nbsp;John G.W. Kelley","doi":"10.1016/j.ocemod.2025.102598","DOIUrl":"10.1016/j.ocemod.2025.102598","url":null,"abstract":"<div><div>This paper presents an in-depth evaluation of a 3D unstructured grid model under various forcing sources, with a focus on the New York-New Jersey (NY-NJ) harbor. The model is first calibrated and evaluated through control runs, ensuring it accurately captures essential processes around the NY/NJ harbor. The sensitivity experiments highlight the significant roles and contributions of different forcing sources in coastal ocean conditions such as total water level, currents, salinity, and water temperature. Different tidal forcings, including FES2014, TPXO9 v1, and TPXO9 v5, show significant effects on tidal components, total water levels, currents, and water temperature, with minimal impact on salinity. Surface forcings from the HRRR, ERA5, and GFS demonstrate variable influences on water temperature predictions, while total water level, currents, and salinity are less sensitive to the different atmospheric forcing sources. Different open ocean conditions from CMEMS, HYCOM, and GRTOFS exhibited minor impacts on hydrodynamic variables in the inland rivers and estuaries but noticeably affected ocean surface currents and vertical structures of water temperature on the continental shelf. Different river discharges from USGS and NWM show high sensitivities of salinities and upstream water levels while shelf-scale ocean currents and vertical structures of water temperatures are similar across the different river discharges. The findings emphasize the necessity of selecting optimal forcing sources to minimize uncertainties and enhance predictive capabilities, supporting better decision-making in coastal management and hazard mitigation.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"197 ","pages":"Article 102598"},"PeriodicalIF":3.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144703498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Controlled Four-Parameter Method for cross-assignment of directional wave systems","authors":"Andre Luiz Cordeiro dos Santos ,&nbsp;Felipe Marques dos Santos ,&nbsp;Nelson Violante-Carvalho ,&nbsp;Luiz Mariano Carvalho ,&nbsp;Helder Manoel Venceslau","doi":"10.1016/j.ocemod.2025.102584","DOIUrl":"10.1016/j.ocemod.2025.102584","url":null,"abstract":"<div><div>Cross-assignment of directional wave spectra is a critical task in wave data assimilation. Traditionally, most methods rely on two-parameter spectral distances or energy ranking approaches, which often fail to account for the complexities of the wave field, leading to inaccuracies. To address these limitations, we propose the Controlled Four-Parameter Method (C4PM), which independently considers four integrated wave parameters. This method enhances the accuracy and robustness of cross-assignment by offering flexibility in assigning weights and controls to each wave parameter. We compare C4PM with a two-parameter spectral distance method using data from two buoys moored 13 km apart in deep water. Although both methods produce negligible bias and high correlation, C4PM demonstrates superior performance by preventing the occurrence of outliers and achieving a lower root mean square error across all parameters. The negligible computational cost and customization position C4PM as a potential alternative for wave data assimilation, possibly improving the reliability of forecasts and model validations.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"197 ","pages":"Article 102584"},"PeriodicalIF":3.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144514307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comparative assessment of different machine learning algorithms for estimating near realistic salinity in the North Indian Ocean","authors":"Avinash Paul ,&nbsp;P.A. Maheswaran ,&nbsp;K. Satheesan ,&nbsp;Ajil Kottayil ,&nbsp;M. Harikrishnan","doi":"10.1016/j.ocemod.2025.102561","DOIUrl":"10.1016/j.ocemod.2025.102561","url":null,"abstract":"<div><div>Salinity affects the density of water and hence plays a significant role in the transport of mass, heat, and salt across the globe. Though temperature observations are abundant over the North Indian Ocean (NIO), the salinity observations are generally sparse. Accurate estimation of sound speed profiles is vital for naval operations, particularly for acoustic communication and underwater target detection. Typically, in naval missions, operators rely on in-situ point measurements from Expendable Bathythermographs (XBTs), supplemented by climatological salinity data for sound speed profile derivation. In this study, we explore the effectiveness of three machine learning techniques: Light Gradient Boosting (LightGBM), Extreme Gradient Boosting (XGBoost), and Artificial Neural Network (ANN) for deriving salinity profiles from temperature data. All three models performed well, but XGBoost outperformed the others with a strong correlation coefficient of 0.975 and a very low root mean square error value on the testing dataset. To gain further insights into the model’s behavior, a sensitivity analysis was conducted to identify the most influential parameters for salinity profile estimation. The model’s performance was then evaluated in the coastal and open ocean areas. While generally performing well, a slight decrease in accuracy was observed in areas with limited training data, particularly near coastlines. Furthermore, we evaluated the model using the time series observations from independent ocean buoys located in the NIO, and the results clearly recommended the model’s ability to fill the gaps in buoy-based salinity measurements. In conclusion, this supervised learning model presents a robust alternative for deriving salinity profiles using in-situ temperature data within the NIO region. Its implementation in the NIO region with limited salinity data holds significant promise for enhancing data availability and furthering oceanographic research.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"197 ","pages":"Article 102561"},"PeriodicalIF":3.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144239463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Neural Synthetic Profiles from Remote Sensing and Observations (NeSPReSO) — Reconstructing temperature and salinity fields in the Gulf of Mexico” [Ocean Modelling 196 (2025) 102550]","authors":"Jose R. Miranda ,&nbsp;Olmo Zavala-Romero ,&nbsp;Luna Hiron ,&nbsp;Eric P. Chassignet ,&nbsp;Bulusu Subrahmanyam ,&nbsp;Thomas Meunier ,&nbsp;Robert W. Helber ,&nbsp;Enric Pallas-Sanz ,&nbsp;Miguel Tenreiro","doi":"10.1016/j.ocemod.2025.102585","DOIUrl":"10.1016/j.ocemod.2025.102585","url":null,"abstract":"","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"197 ","pages":"Article 102585"},"PeriodicalIF":2.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of wave-induced mixing on the simulation of the upper mixed layer in climate models","authors":"Yujie Jing ,&nbsp;Jian Sun ,&nbsp;Rui Li ,&nbsp;Kejian Wu ,&nbsp;Zipeng Yu ,&nbsp;Pengfei Lin ,&nbsp;Xianghui Dong ,&nbsp;Alexander V. Babanin","doi":"10.1016/j.ocemod.2025.102583","DOIUrl":"10.1016/j.ocemod.2025.102583","url":null,"abstract":"<div><div>The upper ocean plays a critical role in the atmosphere-ocean coupled system. Wave-induced vertical mixing significantly influences the structure of the upper ocean which is crucial for climate predictions. This study evaluates the biases in the LICOM model’s simulation of the upper ocean and incorporates the wave-induced mixing coefficient <em>Bv</em>, derived from the WAVEWATCHIII wave model using a parameterization scheme for non-breaking wave-induced mixing. This coefficient was integrated into the vertical mixing scheme of the LICOM model to assess the impact on upper ocean simulation. The results indicate that wave-induced mixing increases the mixed layer depth (MLD) and decreases the sea surface temperature (SST), enhances vertical mixing, and leads to a decrease in upper ocean temperature while increasing subsurface temperature. Validation with Argo observations and the EN4 data product demonstrates that considering wave-induced mixing improves the simulated MLD, SST, and upper ocean temperature climatology, aligning them more closely with observed values. Consequently, incorporating wave-induced mixing can enhance the predictive capabilities of the LICOM model.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"197 ","pages":"Article 102583"},"PeriodicalIF":3.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144514306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A deep learning approach for coastal downscaling: The northern Adriatic Sea case-study","authors":"Federica Adobbati ,&nbsp;Lorenzo Bonin ,&nbsp;Gianpiero Cossarini ,&nbsp;Valeria Di Biagio ,&nbsp;Fabio Giordano ,&nbsp;Luca Manzoni ,&nbsp;Stefano Querin","doi":"10.1016/j.ocemod.2025.102581","DOIUrl":"10.1016/j.ocemod.2025.102581","url":null,"abstract":"<div><div>Current regional-scale oceanographic operational systems may lack the resolution needed for coastal applications, where fine-scale dynamics such as river outflow and local processes are poorly represented. Artificial intelligence based techniques for interpolation and fine-scale reconstruction can be applied for studying coastal dynamics. In this paper, we propose a deep learning method based on a UNet-like architecture for coastal downscaling of marine ecosystem modeling products. Our method is applied to the northern Adriatic Sea, a marginal region of the Mediterranean characterized by strong spatial and temporal variability, where river inputs significantly influence the physical and biogeochemical state and dynamics, especially near the coast. To address these challenges, we trained a neural network on a reanalysis dataset, covering the period from 2006 to 2017, with a horizontal resolution of about 750 m, using as input the regional-scale products of the Marine Copernicus Service for the Mediterranean Sea. We demonstrate that our architecture is capable of recovering fine-scale features that are not captured by low-resolution modeling systems. Although this paper focuses on the northern Adriatic Sea, the robustness of the method, as demonstrated by the validation metrics, suggests that it can be effectively applied to other study areas.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"197 ","pages":"Article 102581"},"PeriodicalIF":3.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wave dynamics in the Yellow River Estuary during cold wave and typhoon events","authors":"Shenghan Gao ,&nbsp;Miaohua Mao ,&nbsp;Meng Xia","doi":"10.1016/j.ocemod.2025.102568","DOIUrl":"10.1016/j.ocemod.2025.102568","url":null,"abstract":"<div><div>The Yellow River Estuary (YRE), located in the semi-enclosed Bohai Sea, is characterized by complex shorelines and shallow water depths and is vulnerable to high waves during extreme weather events. Therefore, a dual-nested third-generation wave model was applied to investigate wave dynamics during Typhoons In-Fa (2021) and Mui-Fa (2022) and a pair of cold wave events in 2021 and 2022. The YRE model was refined to reproduce realistic high-resolution terrain and then calibrated against observations at four long-term buoy stations. Results indicate that wave characteristics closely correlate with winds, modulated by local bathymetry. During cold waves, the temporal evolution of the significant wave height (<em>H_s</em>) exhibits double peaks, whereas a single peak is observed during typhoons due to alternative development responses to winds. This resulted in a 1.5-h time lag between <em>H_s</em> and winds. Wind waves primarily dominate sea states, while swells occur after the typhoon passage. Bathymetric refraction plays an essential role in sheltering the southern region of the YRE from remotely energetic swells. Further investigations reveal that depth-induced breaking and whitecapping jointly control wave energy dissipation. Bathymetric heterogeneity and shoaling processes substantially influence wave energy, resulting in wave attenuation and spatial variability. Intense triad wave-wave interactions and wave breaking contribute to increased <em>H_s</em>, causing multiple wave-breaking processes during propagation. The findings in the YRE help enhance the understanding of wave dynamics in similar shallow-water mega deltas and estuaries.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"197 ","pages":"Article 102568"},"PeriodicalIF":3.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144212922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}