Ocean Modelling最新文献

{"title":"Theory and analysis of acoustic-gravity waves in a free-surface compressible and stratified ocean: Impact of the bottom-boundary condition","authors":"Pierre-Antoine Dumont ,&nbsp;Francis Auclair ,&nbsp;Franck Dumas ,&nbsp;Yann Stéphan ,&nbsp;Laurent Debreu","doi":"10.1016/j.ocemod.2024.102371","DOIUrl":"https://doi.org/10.1016/j.ocemod.2024.102371","url":null,"abstract":"<div><p>Auclair et al. (2021) analyzed the propagation of acoustic-gravity waves (AGWaves) in the ocean and showed that AGWaves dispersion can be described based on the inner and boundary dispersion relations. A major limitation to their two-dispersion-relation model is the assumption of a rigid bottom boundary since acoustic waves can cross the ocean bottom and propagate in the sediment. An extension of their AGWaves-dispersion model is consequently proposed toward a more realistic two-layers fluid model. This improvement enables the evaluation of the perspectives opened by the new generation of compressible ocean models for ocean-acoustics applications. The acoustic regimes in this resulting model are shown to be in agreement with underwater acoustics literature. In addition, the free-surface boundary condition is in turn compared to the pressure release boundary condition to establish a bridge with classical acoustic dispersion models.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"189 ","pages":"Article 102371"},"PeriodicalIF":3.2,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140552353","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":"Modelling beaches morphodynamic by Hadamard sensitivity analysis","authors":"R. Dupont ,&nbsp;F. Bouchette ,&nbsp;B. Mohammadi","doi":"10.1016/j.ocemod.2024.102370","DOIUrl":"https://doi.org/10.1016/j.ocemod.2024.102370","url":null,"abstract":"<div><p>The paper presents a morphodynamic model which can be coupled with any wave model capable of producing time/spectral averaged wave quantities. This model based on a wave energy minimization principle highlights the morphodynamic phenomenology, such as the sandbar creation. Such a model can be used in solving engineering optimization problems. It is also developed to illustrate the idea that beach sand transport can be thought as a non-local phenomenon. We used wave calculations from SWAN and XBeach in our model, and we compared the morphodynamic results to LIP and SANDS hydro-morphodynamic benchmark as well as open-sea simulations. Using supplementary mathematical development, we improved the minimization method using the Hadamard derivative.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"189 ","pages":"Article 102370"},"PeriodicalIF":3.2,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S146350032400057X/pdfft?md5=b8c0817a6647bad0e191b3243f9e642b&pid=1-s2.0-S146350032400057X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140545741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combined surge-meteotsunami dynamics: A numerical model for hurricane Leslie on the coast of Portugal","authors":"Jihwan Kim ,&nbsp;Rachid Omira","doi":"10.1016/j.ocemod.2024.102368","DOIUrl":"https://doi.org/10.1016/j.ocemod.2024.102368","url":null,"abstract":"<div><p>In recent years, Portugal's coastal regions have experienced an increase in the frequency and intensity of severe weather events, including tropical cyclones and extratropical storms. This paper presents an analysis of Hurricane Leslie(2018)'s impact on Portugal, with a specific focus on the complex and often underestimated meteotsunami phenomena accompanying the storm system. Our analysis examines data collected from multiple sources, and employs advanced numerical simulations, integrated within the GeoClaw framework. These simulations encompass both storm surge and meteotsunami effects. One of the findings is the significant role played by meteotsunamis in amplifying coastal sea levels during extreme weather events. The observed sea-level fluctuations closely align with the combined surge-meteotsunami simulations, emphasizing the importance of considering these high-frequency phenomena in coastal hazard assessments.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"189 ","pages":"Article 102368"},"PeriodicalIF":3.2,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1463500324000556/pdfft?md5=5743e7cd98efdb3459a76a3f896cade7&pid=1-s2.0-S1463500324000556-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140543259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A hybrid model for significant wave height prediction based on an improved empirical wavelet transform decomposition and long-short term memory network","authors":"Jin Wang ,&nbsp;Brandon J. Bethel ,&nbsp;Wenhong Xie ,&nbsp;Changming Dong","doi":"10.1016/j.ocemod.2024.102367","DOIUrl":"https://doi.org/10.1016/j.ocemod.2024.102367","url":null,"abstract":"<div><p>Due to strong non-linearity, ocean surface gravity waves are difficult to directly and accurately predict, despite their importance for a wide range of coastal, nearshore, and offshore activities. To minimize forecast errors, a hybrid combined improved empirical wavelet transform decomposition (IEWT) and long-short term memory network (LSTM) model has been proposed. Data from National Data Buoy Center buoys deployed in the North Pacific Ocean are taken as an example to verify the models. Wave forecasts using the LSTM, EWT-LSTM, and IWET-LSTM models are compared with the observations at 6, 12, 18, 24 and 48 h forecast windows. Consequently, IEWT-LSTM is superior to EWT-LSTM or LSTM models, especially for larger waves at longer long forecast windows.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"189 ","pages":"Article 102367"},"PeriodicalIF":3.2,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140543970","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":"Construction of a wavefront model for internal solitary waves and its application in the Northern South China Sea","authors":"Zijian Cui ,&nbsp;Chujin Liang ,&nbsp;Feilong Lin ,&nbsp;Shuangshuang Chen ,&nbsp;Tao Ding ,&nbsp;Beifeng Zhou ,&nbsp;Weifang Jin ,&nbsp;Wankang Yang","doi":"10.1016/j.ocemod.2024.102366","DOIUrl":"https://doi.org/10.1016/j.ocemod.2024.102366","url":null,"abstract":"<div><p>Internal solitary waves (ISWs) play a crucial role in the development of various physical and biological processes, and numerous high-precision two-dimensional or three-dimensional numerical models have been developed to simulate the generation and propagation processes of ISWs. However, these numerical models, especially when simulating the interaction between ISWs and ocean circulation, require substantial computational resources. This burden can make it challenging to apply them in real-time or short-term forecasting scenarios. In this study, we propose a new numerical model for ISWs by combining traditional one-dimensional ISW theory with wave refraction theory. The proposed model resolves the issues of ray crossing and divergence, which are commonly encountered in traditional refraction models, by employing equally spaced grids along the wave crest line. As a result, this model is capable of simulating the far-field propagation of ISWs. This model enables rapid prediction of the vertical structure and wave crest morphology of ISWs in specific current fields and at given time frames, and it is utilized to investigate the characteristics and propagation of ISWs generated by the nonlinear steepening of internal tide (IT) in the South China Sea. Comparative analysis with satellite imagery demonstrates the model's accurate representation of ISW processes and phenomena, such as wave crest line discontinuities, diffraction, and wave‒wave interactions when passing through Dongsha Island. Furthermore, propagation time estimates based on this model have errors of ±0.98 h (1σ) over which the ISWs are observed by a mooring system, and the average time difference is 0.81 h</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"189 ","pages":"Article 102366"},"PeriodicalIF":3.2,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140330941","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":"Comment on papers using machine learning for significant wave height time series prediction: Complex models do not outperform auto-regression","authors":"Haoyu Jiang ,&nbsp;Yuan Zhang ,&nbsp;Chengcheng Qian ,&nbsp;Xuan Wang","doi":"10.1016/j.ocemod.2024.102364","DOIUrl":"10.1016/j.ocemod.2024.102364","url":null,"abstract":"<div><p>Significant Wave Height (SWH) is crucial in many aspect of ocean engineering. The accurate prediction of SWH has therefore been of immense practical value. Recently, Artificial Intelligence (AI) time series prediction methods have been widely used for single-point short-term SWH time-series forecasting, resulting in many AI-based models claiming to achieve good results. However, the extent to which these complex AI models can outperform traditional methods has largely been overlooked. This study compared five different models - AutoRegressive (AR), eXtreme Gradient Boosting (XGB), Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), and WaveNet - for their performance on SWH time series prediction at 16 buoy locations. Surprisingly, the results suggest that the differences of performance among different models are negligible, indicating that all these AI models have only “learned” the linear auto-regression from the data. Additionally, we noticed that many recent studies used signal decomposition method for such time series prediction, and most of them decomposed the test sets, which is WRONG.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"189 ","pages":"Article 102364"},"PeriodicalIF":3.2,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140405893","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":"Impact of atmospheric forcing on SST biases in the LETKF-based ocean research analysis (LORA)","authors":"Shun Ohishi ,&nbsp;Takemasa Miyoshi ,&nbsp;Misako Kachi","doi":"10.1016/j.ocemod.2024.102357","DOIUrl":"10.1016/j.ocemod.2024.102357","url":null,"abstract":"<div><p>In the previous study, the authors have produced an eddy-resolving ocean ensemble analysis product called the local ensemble transform Kalman filter (LETKF)-based ocean research analysis (LORA) over the western North Pacific and Maritime Continent regions using an ocean data assimilation system driven by the Japanese operational atmospheric reanalysis dataset known as the JRA-55. However, the LORA includes warm biases in sea surface temperatures (SSTs) in coastal regions during the boreal winter. In this study, we perform sensitivity experiments with atmospheric forcing using an ocean forcing dataset known as the JRA55-do, which adjusts the JRA-55 to high-quality reference datasets to reduce biases and uncertainties. The results show that the nearshore warm SST biases are significantly improved by the JRA55-do. During the boreal autumn, the improvement comes from mainly two factors: (i) enhancement of surface cooling by latent heat releases caused by removing contamination of weak winds at the land grid cells, and (ii) weakening surface heating by downward shortwave radiation through the adjustment in the JRA55-do.</p><p>During the boreal winter, enhanced cooling by the analysis increments suppresses the growth of the warm SST biases when the JRA55-do is used. However, if the JRA-55 dataset is used, the adaptive observation error inflation (AOEI) scheme acts negatively to keep the nearshore SST biases in winter. Based on the innovation statistics, the AOEI inflates the observation errors when the differences between the squared observation-minus-forecast innovations and the squared forecast ensemble spreads are larger than the prescribed observation error variance, and improves the accuracy in the open ocean, especially around the frontal regions. However, when substantial warm SST biases are formed in the previous season, AOEI's observation error inflation makes the analysis increments smaller and cannot suppress the warm biases.</p><p>We also validate the analysis accuracy using various data such as sea surface height and horizontal velocities and find that the JRA55-do has significant advantages. Therefore, continuous maintenance and development of ocean forcing datasets are essential for ocean modeling and data assimilation.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"189 ","pages":"Article 102357"},"PeriodicalIF":3.2,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1463500324000441/pdfft?md5=83d306f647dd57df61d98fef35b46c30&pid=1-s2.0-S1463500324000441-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140280821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The linkage between wintertime sea ice drift and atmospheric circulation in an Arctic ice-ocean coupled simulation","authors":"Xi Liang ,&nbsp;Haibo Bi ,&nbsp;Chengyan Liu ,&nbsp;Xichen Li ,&nbsp;Dakui Wang ,&nbsp;Fu Zhao ,&nbsp;Zhongxiang Tian ,&nbsp;Ming Li ,&nbsp;Na Liu","doi":"10.1016/j.ocemod.2024.102362","DOIUrl":"https://doi.org/10.1016/j.ocemod.2024.102362","url":null,"abstract":"<div><p>By analyzing an Arctic ice-ocean coupled simulation, we study the linkage between wintertime sea ice drift and atmospheric circulation, and interpret the driving force terms in the sea ice dynamic equation. Sea ice drift anomaly is featured by an anticyclonic (cyclonic) gyre when regulated by negative (positive) phase of Arctic Oscillation with positive (negative) phase of Arctic Dipole, and a quasi-meridional stream from Chukchi-Beaufort (Barents-Kara) Seas to Barents-Kara (Chukchi-Beaufort) Seas when regulated by positive (negative) phase of Arctic Oscillation with positive (negative) phase of Arctic Dipole. Sea ice drift anomaly, when regulated by the mode alone, resembles spatial pattern of leading atmospheric mode. Decomposing sea ice dynamical equation shows that wind-ice stress dominates sea ice drift in areas away from islands and continental coastlines, ocean-ice stress acts as a resistant power to partly cancel the wind-ice stress in these areas, while in the coastal areas such as the thick multiyear ice zone north of the Canadian Arctic Archipelago, the wind-ice and ocean-ice stresses are small, the balance exists between sea surface height potential gradient and internal ice stress divergence. Developing more sophisticated internal ice stress expression in ice model is of great important to correctly project future sea ice change for the ice modeling community.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"189 ","pages":"Article 102362"},"PeriodicalIF":3.2,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140191985","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":"Sensitivity of boundary layer features to depth-dependent baroclinic pressure gradient and turbulent mixing in an ocean of finite depth","authors":"Víctor J. Llorente ,&nbsp;Enrique M. Padilla ,&nbsp;Manuel Díez-Minguito","doi":"10.1016/j.ocemod.2024.102359","DOIUrl":"https://doi.org/10.1016/j.ocemod.2024.102359","url":null,"abstract":"&lt;div&gt;&lt;p&gt;The present numerical study builds on Ekman (1905)’s work in surface boundary layer and extends the boundary value problem to overcome some of its limitations. Previous studies addressed model’s limitations by assuming that deviations from observations are usually ascribed to different eddy viscosity shapes, but seldom to the presence of baroclinic pressure gradients and shallow seas, which are the mainstays of this work. Improved solutions in the ocean boundary layer are obtained considering both depth-dependent wind-induced eddy viscosity and horizontal density gradients, ranging from well-mixed to highly-stratified conditions in a finite-depth ocean. High-order numerical solutions extend those in previous analytical and numerical works in the literature and widens the parameter space analyzed. Remarkably, the current profiles are obtained without ambiguity as a truly superposition of a geostrophic and a ageostrophic terms. Results indicate that, for a vertically-uniform eddy viscosity without density gradients and in shallow waters, currents are practically aligned with wind. As depth increases, misalignment between currents and wind increases and the complexity of the vertical structure increases. At large depths, Ekman’s values are attained, i.e., deflection angles relative to wind direction, &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;W&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;, are &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;S&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;W&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;4&lt;/mn&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mn&gt;5&lt;/mn&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mo&gt;∘&lt;/mo&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; at the surface, where the current is maximum, and &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;W&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;90&lt;/mn&gt;&lt;mo&gt;°&lt;/mo&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; for the depth-integrated transport (negative for deflections to the right in the Northern Hemisphere). These features remain regardless of the magnitude of the eddy-viscosity. For non-uniform eddy viscosity, &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;S&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;W&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; decreases from &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;4&lt;/mn&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mn&gt;5&lt;/mn&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mo&gt;∘&lt;/mo&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; up to &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;9&lt;/mn&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mo&gt;∘&lt;/mo&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; from low to high stratification level, respectively, whereas &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;W&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; is rather insensitive (&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;θ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;W&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;≈&lt;/mo&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;9&lt;/mn&gt;&lt;ms","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"189 ","pages":"Article 102359"},"PeriodicalIF":3.2,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140191983","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 hybrid network for significant wave height estimation","authors":"Luca Patanè,&nbsp;Claudio Iuppa,&nbsp;Carla Faraci,&nbsp;Maria Gabriella Xibilia","doi":"10.1016/j.ocemod.2024.102363","DOIUrl":"https://doi.org/10.1016/j.ocemod.2024.102363","url":null,"abstract":"<div><p>The influence of weather conditions on sea state, and in particular on the dynamic evolution of waves, is an important issue that affects several areas, including maritime traffic and the planning of coastal works. To collect relevant data, buoys are used to set up distributed sensor networks along coastal areas. However, unfavourable weather conditions can lead to downtime, which can be extended due to maintenance issues. The ability to improve the robustness of these sensor systems using predictive models, i.e. digital twins, to interpolate and extrapolate missing data is an important and growing area of research. To accomplish such a task, models must be found that can account for both the spatial and temporal dynamics of the input data to correctly estimate the variables of interest. In this work, a deep learning architecture is proposed to realize a digital twin for the monitoring buoy for significant wave height estimation using spatial and temporal information about the wind field in the area of interest. The proposed methodology was applied to a case study using wave height data from an Italian Sea Monitoring Network buoy installed near the coast of Sicily and wind field data from the Copernicus Climate Change Service ERA5 reanalysis. The reported results show that the use of a multi-block hybrid deep neural network consisting of convolutional layers for spatial feature extraction and short-term memory layers for modelling the involved dynamics, which takes into account the buoy surrounding area, outperforms other empirical, numerical, machine learning and deep learning methods used in the literature.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"189 ","pages":"Article 102363"},"PeriodicalIF":3.2,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1463500324000507/pdfft?md5=688e886ada571b1357f4ef54284280b5&pid=1-s2.0-S1463500324000507-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140191984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}