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An assessment of seawater desalination impact on salinities in the Arabian / Persian Gulf using a 3D circulation model 利用三维环流模型评估阿拉伯/波斯湾海水淡化对盐度的影响
IF 3.1 3区 地球科学
Ocean Modelling Pub Date : 2025-01-27 DOI: 10.1016/j.ocemod.2025.102503
Oleksandr Nesterov
{"title":"An assessment of seawater desalination impact on salinities in the Arabian / Persian Gulf using a 3D circulation model","authors":"Oleksandr Nesterov","doi":"10.1016/j.ocemod.2025.102503","DOIUrl":"10.1016/j.ocemod.2025.102503","url":null,"abstract":"<div><div>The Arabian / Persian Gulf, hereinafter referred to as the Gulf, is one of the major sources of freshwater through desalination in Kuwait, Bahrain, Qatar, the United Arab Emirates, the eastern Kingdom of Saudi Arabia (KSA), as well as in the coastal regions of the Iranian provinces Bushehr and Hormozgan, and the Oman governorate Musandam. Over the past four decades, the seawater desalination capacities in these states have been steadily growing. By 2023 the total production capacity has reached 25.6 Mm<sup>3</sup>/day, more than double that in 2006 (∼12.1 Mm<sup>3</sup>/day), and it is expected to add at least 6.2 Mm<sup>3</sup>/day by 2030. However, not only the Gulf serves as a source of freshwater for domestic, agricultural and industrial use, but also as a sink for the reject brine. Being a semi-enclosed water body characterized by relatively high evaporation rates of 1.5 – 2 m/year on average, small and reportedly declining river inflows, and negligible precipitations, the Gulf may eventually become impacted by anthropogenic changes in salinities, raising concerns about acceptable freshwater production rates and the overall resilience of its ecosystem. In this study, to estimate a combined impact of the desalination facilities on salinities on global and local scales, a 3D high-resolution free-surface baroclinic model of the Gulf's hydrodynamics was established using the open-source unstructured-grid Semi-implicit Cross-scale Hydroscience Integrated System Model. The horizontal resolution of the numerical mesh varied from approximately 4 km in the Sea of Oman to higher than a hundred meters in some coastal areas of the Gulf, which is notably higher than in previous studies, with the vertical resolution of up to 64 local-sigma-coordinate levels. The desalination capacities of 738 coastal plants were considered based on the 35<sup>th</sup> Worldwide Desalting Inventory of 2023. Two simulations were carried out over 3 years to assess their impact: one without the effect of the plants (baseline), and the other one with the effect of the plants. The baseline model was validated against field measurements. The volume, near-surface and near-bed averaged salinity impacts in the whole Gulf were found converging to 0.03, 0.04, and 0.05 g/l, respectively. Higher salinity increments were modeled closer to the plants, in some cases at considerable distances. For example, the impact on the median salinities at the seabed was estimated to exceed 0.1 g/l as far as 50 km away from Jubail in KSA, and Al Abu Fontas and Umm Al Houl in Qatar. Even higher increments were modeled in poorly flushed zones, such as ∼0.3 g/l in the whole Gulf of Salwa, and in the range of 0.1 – 0.5 g/l in most of the Abu Dhabi canals. Although such salinity impacts are unlikely to pose environmental threats in the present, the effect of desalination may become more profound in the future, especially in view that salinities in the Gulf have remained quasi-equilibrium over the","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"194 ","pages":"Article 102503"},"PeriodicalIF":3.1,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372939","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}
引用次数: 0
Mechanism and application of the Lagrangian flow network method to indicate practical material distribution patterns in the tide-dominated Bohai Sea with multi-frequency tides 拉格朗日流网法在渤海多频潮汐中指示实际物质分布规律的机理及应用
IF 3.1 3区 地球科学
Ocean Modelling Pub Date : 2025-01-26 DOI: 10.1016/j.ocemod.2025.102504
Jinzhen Yu , Xueqing Zhang , Xiaoxuan Sheng , Fangjing Deng , Yanping Wang , Wensheng Jiang , Jihong Zhang
{"title":"Mechanism and application of the Lagrangian flow network method to indicate practical material distribution patterns in the tide-dominated Bohai Sea with multi-frequency tides","authors":"Jinzhen Yu ,&nbsp;Xueqing Zhang ,&nbsp;Xiaoxuan Sheng ,&nbsp;Fangjing Deng ,&nbsp;Yanping Wang ,&nbsp;Wensheng Jiang ,&nbsp;Jihong Zhang","doi":"10.1016/j.ocemod.2025.102504","DOIUrl":"10.1016/j.ocemod.2025.102504","url":null,"abstract":"<div><div>Mass transport process is vital for the spatial distribution of materials in coastal environments, and comprehending this process is essential for efficient marine pollution control and environmental conservation. As tides is an essential process in coastal environments, the patterns of practical material distribution are decoded in the tide-dominated Bohai Sea with multi-frequency tides by employing the Lagrangian flow network (LFN). Here, the parameter of degree represents the mass transport process, and the concept of the hydrodynamic province is used to depict the spatial distribution of passively transported materials. The emergent pattern of hydrodynamic provinces driven by multiple tidal constituents aligns with the climatological salinity trend, pollutant distribution and phytoplankton community in the springtime Bohai Sea, demonstrating the practical utility of the LFN. The mechanism elucidated by the LFN can be mainly attributed to the intertidal Lagrangian residual velocity induced by tides. Particularly in spring, the tide-induced residual current in the Bohai Sea significantly contributes to basin-scale circulation, while the wind-driven component in winter and the thermohaline part in summer play a more important role than those in spring. In the realm of marine management and conservation strategies, taking into account both terrestrial and maritime perspectives, and incorporation of the marine mass transport process is crucial for the formulation of effective policies.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"194 ","pages":"Article 102504"},"PeriodicalIF":3.1,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147302","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}
引用次数: 0
Enhancing downscaled ocean wave conditions with machine learning and wave spectra 用机器学习和波浪谱增强缩小尺度的海浪条件
IF 3.1 3区 地球科学
Ocean Modelling Pub Date : 2025-01-25 DOI: 10.1016/j.ocemod.2025.102502
Leo Peach , Nick Cartwright , Guilherme Viera da Silva , Darrell Strauss
{"title":"Enhancing downscaled ocean wave conditions with machine learning and wave spectra","authors":"Leo Peach ,&nbsp;Nick Cartwright ,&nbsp;Guilherme Viera da Silva ,&nbsp;Darrell Strauss","doi":"10.1016/j.ocemod.2025.102502","DOIUrl":"10.1016/j.ocemod.2025.102502","url":null,"abstract":"<div><div>Machine Learning (ML) is becoming an increasingly popular and important tool for predicting ocean wave conditions. Here it is applied to downscale offshore conditions to a nearshore location utilising more detailed representations of the offshore wave field using 1D wave spectra. Our aim is to identify some of the sensitivities in input data when using machine learning to conduct downscaling (a common application) and present results from different approaches. The results demonstrate that downscaling wave conditions using ML can be enhanced using 1D wave spectra to improve performance. Here, we obtained a 27 % reduction in root mean squared error in significant wave height when compared to integrated parameter only machine learning approach with performance improved when using 1D wave spectra. Though we identified that the Long-Term Short-Term Memory approach applied here improved performance overall, it also appears there is not a one-size fits-all approach for all wave parameters. Careful feature selection (which features to include or exclude when training a model), feature engineering (such as feature encoding and sequence selection) and model configuration continue to be key factors in achieving accurate wave conditions.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"194 ","pages":"Article 102502"},"PeriodicalIF":3.1,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143148260","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}
引用次数: 0
Regional ocean model uncertainties using stochastic parameterizations and a global atmospheric ensemble 利用随机参数化和全球大气综合的区域海洋模式不确定性
IF 3.1 3区 地球科学
Ocean Modelling Pub Date : 2025-01-22 DOI: 10.1016/j.ocemod.2025.102501
Vassilios D. Vervatis , Pierre De Mey-Frémaux , John Karagiorgos , Bénédicte Lemieux-Dudon , Nadia K. Ayoub , Sarantis Sofianos
{"title":"Regional ocean model uncertainties using stochastic parameterizations and a global atmospheric ensemble","authors":"Vassilios D. Vervatis ,&nbsp;Pierre De Mey-Frémaux ,&nbsp;John Karagiorgos ,&nbsp;Bénédicte Lemieux-Dudon ,&nbsp;Nadia K. Ayoub ,&nbsp;Sarantis Sofianos","doi":"10.1016/j.ocemod.2025.102501","DOIUrl":"10.1016/j.ocemod.2025.102501","url":null,"abstract":"<div><div>A Bay of Biscay model configuration is used as a test case to assess the data-based consistency of ensemble-based ocean model uncertainties of several types: [A] built-in stochastic parameterizations at regional ocean scales, [B] ocean model response to a global atmospheric model ensemble and [C] both A and B simultaneously. Ensembles of varying length were generated. In addition to a seasonal-range ensemble, three medium-range ensembles were carried out over successive overlapping segments permitting to compare consistency metrics for different lead times. The largest spread was obtained for the C case, although most of the model uncertainties were attributable to the stochastic ocean parameterizations in A. We addressed the question of which ensemble type and lead time was able to provide the most realistic model uncertainties given observations of SST, sea level, and Chlorophyll a, using a theoretical and diagnostic consistency analysis framework expanded from Vervatis et al. (2021a). In our results, consistency was satisfactory for the stochastic ensembles of types A and C, for the “aged” error cases (but only marginally with respect to the “young” error cases), and whenever physical and biogeochemical uncertainty processes were active in the region and could be detected by the observational networks, such as the onset of the spring shoaling of the thermocline and the phytoplankton abundance primary bloom. Sea level empirical consistency was improved when a wide range of low- to high-frequency errors were included in the signal of dynamic atmospheric process in the data and in the model inverse barometer. These findings provide additional insight that can help configure ensemble-based methods in academic studies and in operational ocean forecasting systems.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"194 ","pages":"Article 102501"},"PeriodicalIF":3.1,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147303","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}
引用次数: 0
Role of atmospheric and oceanographic frequency variability on surface Marine Heatwaves in the Northern Humboldt Current System 北洪堡流系统中大气和海洋频率变化对海洋表面热浪的影响
IF 3.1 3区 地球科学
Ocean Modelling Pub Date : 2025-01-09 DOI: 10.1016/j.ocemod.2024.102494
Rodrigo Mogollón , Jorge Quispe , François Colas , Jorge Tam
{"title":"Role of atmospheric and oceanographic frequency variability on surface Marine Heatwaves in the Northern Humboldt Current System","authors":"Rodrigo Mogollón ,&nbsp;Jorge Quispe ,&nbsp;François Colas ,&nbsp;Jorge Tam","doi":"10.1016/j.ocemod.2024.102494","DOIUrl":"10.1016/j.ocemod.2024.102494","url":null,"abstract":"<div><div>In this study, we investigated the role of atmospheric and oceanographic variability in shaping surface Marine Heatwaves (MHWs) in the Northern Humboldt Current System (NHCS) over the last two decades. Through a series of pluriannual hydrodynamic model simulations, we highlighted the importance of considering at least high-frequency atmospheric variability to accurately reproduce the observed MHW characteristics. On the contrary, when synoptic atmosphere variability is removed, the simulation results in fewer, longer, less frequent, less intense, and less severe MHWs. As a consequence, simulations forced with low-frequency data are only able to partially reproduce persistent MHWs. Additionally, using the heat balance analysis, it is shown that at the north, short-lived events are primarily driven by advective causes, while persistent events show an equal contribution between advection and heat fluxes. In the south, changes in heat fluxes are crucial in forming MHWs. During the dissipation phase of MHWs, cooling is dominated by advective processes, mainly coastal upwelling, in both coastal regions. Overall, these findings indicate a reduced dependence on high-frequency oceanic forcing and highlight the need to consider the atmospheric variability in regional downscaling of global climate model simulations to capture almost the full range of MHW events in the NHCS.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"194 ","pages":"Article 102494"},"PeriodicalIF":3.1,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147304","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}
引用次数: 0
Dynamic and thermodynamic coupling between the atmosphere and ocean near the Kuroshio current and extension system 黑潮及其延伸系统附近大气与海洋的动力与热力学耦合
IF 3.1 3区 地球科学
Ocean Modelling Pub Date : 2025-01-08 DOI: 10.1016/j.ocemod.2024.102496
Ajin Cho , Hajoon Song , Hyodae Seo , Rui Sun , Matthew R. Mazloff , Aneesh C. Subramanian , Bruce D. Cornuelle , Arthur J. Miller
{"title":"Dynamic and thermodynamic coupling between the atmosphere and ocean near the Kuroshio current and extension system","authors":"Ajin Cho ,&nbsp;Hajoon Song ,&nbsp;Hyodae Seo ,&nbsp;Rui Sun ,&nbsp;Matthew R. Mazloff ,&nbsp;Aneesh C. Subramanian ,&nbsp;Bruce D. Cornuelle ,&nbsp;Arthur J. Miller","doi":"10.1016/j.ocemod.2024.102496","DOIUrl":"10.1016/j.ocemod.2024.102496","url":null,"abstract":"<div><div>Relative wind (RW; wind relative to surface currents) has been shown to play a crucial role in air-sea interactions, influencing both atmospheric and oceanic dynamics. While the RW effects through momentum flux are well-documented, those through turbulent heat fluxes remain unknown. In this study, we investigate two distinct surface current feedbacks – those associated with the momentum flux and turbulent heat fluxes – by modifying respective bulk formulations in the regional ocean-atmosphere coupled system, and analyze both immediate and seasonal changes in the boundary layers. Our results show that strong ocean currents in the Kuroshio Current and Extension significantly impact surface coupling, with responses generally contingent on the wind-current angle: an increase (decrease) in air-sea momentum and turbulent heat fluxes occurs when the low-level wind and surface currents are aligned (opposed). The instantaneous responses to surface currents include changes in low-level wind, surface current speed, and humidity, which are consistent with anticipated changes for a given wind-current angle based on the bulk formulations. While the wind-current angle is still an important factor, it does not adequately capture the seasonal responses. On the seasonal timescale, both surface current feedbacks can alter the path of the Kuroshio Extension and mesoscale activities, resulting in different background states that affect air-sea momentum and turbulent heat exchanges. Our results suggest that the energetic current system, such as the Kuroshio Current and Extension, can be significantly influenced by surface current coupling through both momentum and turbulent heat fluxes.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"194 ","pages":"Article 102496"},"PeriodicalIF":3.1,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147306","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}
引用次数: 0
Machine Learning Approaches for Early Warning of Tsunami Induced by Volcano Flank Collapse and Implication for Future Risk Management: Case of Anak Krakatau 火山侧翼崩塌引发海啸预警的机器学习方法及其对未来风险管理的启示——以喀拉喀托火山为例
IF 3.1 3区 地球科学
Ocean Modelling Pub Date : 2025-01-07 DOI: 10.1016/j.ocemod.2025.102497
E. Juanara, C.Y. Lam
{"title":"Machine Learning Approaches for Early Warning of Tsunami Induced by Volcano Flank Collapse and Implication for Future Risk Management: Case of Anak Krakatau","authors":"E. Juanara,&nbsp;C.Y. Lam","doi":"10.1016/j.ocemod.2025.102497","DOIUrl":"10.1016/j.ocemod.2025.102497","url":null,"abstract":"<div><div>A tsunami triggered by volcanic collapse is a low-probability but high-impact event. Unlike tsunamis triggered by earthquakes which the mechanism is well understood, volcanic tsunami events have complex trigger mechanisms and occur with little to no warning such as the event in December 2018 of the Anak Krakatau volcano tsunami, making it more difficult to detect and issue a warning. We adopted collapse tsunami machine learning (ML) approach model which does not require source information, to predict maximum tsunami amplitude on four coastal stations. Observations from six synthetic observation stations around Anak Krakatau volcano were used as input for collapse tsunami ML. The 320 collapse scenarios triggering tsunamis with various parameters and directions were generated to train model. To evaluate the accuracy and reliability of the tsunami simulations, we conducted a comparison between the simulated waveforms and those recorded at four coastal stations during the December 2018 event. The RMSE values between predicted and actual (via forward tsunami) of Random Forest model consistently provide the most accurate predictions ranging from 0.0586 to 0.1945 across three out of the four stations. We also applied deep learning algorithms, LSTM, and Complex LSTM to predict tsunami full waveform by using short-duration observation as input. Furthermore, we also pointed out the potential of risk management that can be explored and integrated from results of the maximum tsunami amplitude and arrival time predictions for support decision-making. We suggest that the ML approach could be a good alternative for volcanic tsunamis early warning purposes.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"194 ","pages":"Article 102497"},"PeriodicalIF":3.1,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143148261","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}
引用次数: 0
On the speeding up and accuracy of the Second Order Moment (SOM) advection scheme using a mixed-precision method 基于混合精度方法的二阶矩平流格式的加速和精度研究
IF 3.1 3区 地球科学
Ocean Modelling Pub Date : 2025-01-04 DOI: 10.1016/j.ocemod.2024.102495
Hideyuki Nakano, L. Shogo Urakawa, Kunihiro Aoki, Yuma Kawakami, Shoji Hirahara
{"title":"On the speeding up and accuracy of the Second Order Moment (SOM) advection scheme using a mixed-precision method","authors":"Hideyuki Nakano,&nbsp;L. Shogo Urakawa,&nbsp;Kunihiro Aoki,&nbsp;Yuma Kawakami,&nbsp;Shoji Hirahara","doi":"10.1016/j.ocemod.2024.102495","DOIUrl":"10.1016/j.ocemod.2024.102495","url":null,"abstract":"<div><div>The ocean model is accelerated using the mixed-precision method for the second-order moment (SOM) advection scheme, which is highly accurate but computationally demanding. The execution time of the subroutine of the SOM scheme is successfully reduced by 43%, and since the SOM accounted for about 30% of the total time, the overall reduction in computation time is about 13%. A series of 300-year simulations showed that the mixed-precision method has sufficiently small negative impact on temperature (less than 0.02 °C), confirming that it can be used for climate simulations. When all the calculations are done in a simple single precision, an unacceptable difference in zonal mean temperature as a climate model of up to 0.4 °C in the deep ocean and 1 °C in the thermocline appears after the 300-year integration. We also conduct a sensitivity study using an idealized rectangular model, finding that consistency between the continuity equation and the tracer advection is necessary to guarantee accuracy in long-term integration, and it is shown that this consistency can be checked in a short time in a small rectangular domain as an salinity anomaly. In addition to the mixed-precision method, we have introduced two other methods for calculating the single-precision SOM algorithm. One is the Kahan method to compensate for the loss of information in the addition of some important variables represented in single precision, and the other is the conversion reduction method to compensate for the error due to data conversion between single and double precision at the entry and exit of subroutines. When both the methods are used simultaneously, the accuracy is comparable to mixed precision. We also evaluate them in an eddying OGCM and find that errors are difficult to evaluate because they are hidden by the inherent nonlinearity of the model at the stage when the nonlinearity develops.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"194 ","pages":"Article 102495"},"PeriodicalIF":3.1,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147307","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}
引用次数: 0
Analysis of the impact of vertical variation and temporal frequency of the chlorophyll forcing field on modelled temperature in the Mediterranean Sea and potential implications for regional climate projections 叶绿素强迫场的垂直变化和时间频率对地中海模拟温度的影响分析及其对区域气候预估的潜在影响
IF 3.1 3区 地球科学
Ocean Modelling Pub Date : 2025-01-03 DOI: 10.1016/j.ocemod.2024.102490
Yutong Zhang , Florence Sevault , Romain Pennel , Melika Baklouti
{"title":"Analysis of the impact of vertical variation and temporal frequency of the chlorophyll forcing field on modelled temperature in the Mediterranean Sea and potential implications for regional climate projections","authors":"Yutong Zhang ,&nbsp;Florence Sevault ,&nbsp;Romain Pennel ,&nbsp;Melika Baklouti","doi":"10.1016/j.ocemod.2024.102490","DOIUrl":"10.1016/j.ocemod.2024.102490","url":null,"abstract":"<div><div>The urgency of climate change calls for the exploration of a variety of multi-forcing scenarios based on Shared Socio-economic Pathways. Ensuring the reliability of the climate projections is therefore an imperative prerequisite. In this paper, we examined the impact of the vertical variability and temporal frequency of the chlorophyll field used to force the NEMOMED12 ocean circulation model in the absence of a biogeochemical model on some key physical characteristics, mainly seawater temperature. Our analysis reveals that forcing by a chlorophyll field that is homogeneous in the vertical direction favours heat accumulation below the Deep Chlorophyll Maximum, leading to a positive temperature bias increasing with time. The extrapolation of the trend determined over the 11-year simulations leads to a bias in temperature as high as +1 °C after 100 years in the intermediate layer. Comparison with in situ data clearly shows that forcing the model with a realistically varying Chl field over the vertical allows the model to better represent temperature and avoid the presence of this bias. Additionally, we find that using the same chlorophyll field saved at different time frequencies, namely daily, monthly and monthly climatology, to force the NEMOMED12 model also creates temperature differences between simulations that increase with time, especially in the intermediate layer. The simulation forced by the daily chlorophyll is warmer in the surface layers than the two others, and we suggest that this is due to the asymmetric role of chlorophyll extremes on heat distribution. Finally, using a monthly chlorophyll climatology to force the NEMOMED12 ocean circulation model seems to be sufficient for physical modelling of the Mediterranean basin if the vertical variability of the Chl field is realistic.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"194 ","pages":"Article 102490"},"PeriodicalIF":3.1,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147305","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}
引用次数: 0
Deep learning-based solution for the KdV-family governing equations of ocean internal waves 基于深度学习的海洋内波kdv族控制方程解
IF 3.1 3区 地球科学
Ocean Modelling Pub Date : 2024-12-26 DOI: 10.1016/j.ocemod.2024.102493
Xiaofeng Li , Haoyu Wang , Yi Yang , Xudong Zhang
{"title":"Deep learning-based solution for the KdV-family governing equations of ocean internal waves","authors":"Xiaofeng Li ,&nbsp;Haoyu Wang ,&nbsp;Yi Yang ,&nbsp;Xudong Zhang","doi":"10.1016/j.ocemod.2024.102493","DOIUrl":"10.1016/j.ocemod.2024.102493","url":null,"abstract":"<div><div>Internal Solitary Waves (ISWs) are critical for ocean studies due to their large amplitude and long-travel capabilities. Conventionally, the Korteweg-de Vries (KdV) equations and their extensions are employed to simulate ISW properties, but traditional numerical methods lack flexibility and efficiency. This study introduces a universal, deep learning-based model that streamlines solving KdV-family equations. Within the framework of physics-informed neural networks, we implement an optimized Radial Basis Function (RBF) neural network and a new progressive expansion training strategy. This innovation minimizes error during training, leading to efficient convergence. Our model is tested on KdV and forced KdV equations, dimensional and non-dimensional equations using soliton, cnoidal, and dnoidal waveforms to simulate ISW propagation. The model results align with theoretical and numerical benchmarks, as demonstrated in a case study in the Sulu Sea. This paper does not concern ISW dynamics but uses the KdV equation as an example to showcase how to solve the partial differential equations with a new deep-learning method. The developed deep-learning model offers an efficient and accurate approach to solving KdV-family equations in oceanographic studies.</div></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"194 ","pages":"Article 102493"},"PeriodicalIF":3.1,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143148257","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}
引用次数: 0
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