Ocean Modelling最新文献_第2页

The fastest growing initial error and identification of sensitive area for targeted observation in predicting the Kuroshio intrusion into the South China Sea with a high-resolution regional ocean model 高分辨率区域海洋模式预测南海黑潮入侵的最快初始误差及目标观测敏感区识别

IF 2.9 3区地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES

Ocean Modelling

Pub Date : 2026-04-01 Epub Date: 2026-01-03 DOI: 10.1016/j.ocemod.2026.102679

Peng Liang , Yonghao Liang , Qiang Wang , Lina Yang , Tianyu Zhang

Kuroshio intrusion (KI) is a critical linkage between the Pacific and the South China Sea (SCS), profoundly influencing the variability of marine dynamical and ecological processes of the SCS. Due to the complex mechanism and the lack of predictability study on KI, the accuracy of KI prediction remains limited. This study obtains the fastest growing initial errors (FGIEs) of KI using the Regional Ocean Modelling System (ROMS) and conditional nonlinear optimal perturbation (CNOP) method. Specifically, the CNOP, which is an effective method in calculating FGIEs in a nonlinear system, refers to the perturbation that can lead to the maximum of an objective function at a target time under certain constraints. The calculation results reveal two types of FGIEs with similar spatial patterns but opposite signs. When superimposed on the background field, both types of errors exhibit rapid growth and northwestward propagation. At prediction time, the CNOP+ (with positive sea surface height error) and CNOP- (with negative sea surface height error) errors respectively cause significant overestimation and underestimation of KI. Notably, CNOP- errors may even lead to complete failure in predicting the occurrence of KI. The rapid error growth primarily originates from barotropic instability induced by the zonal velocity shear of the reference state. Sensitive areas for targeted observations, identified through vertical integration of initial total energy error, extend northwestward from the southern Luzon Strait to the interior SCS, centered near 120.5°E, 20°N. Remarkably, removing initial errors within this sensitive area (covering merely 0.1 % of the total model domain) can improve KI prediction accuracy most effectively, by 25 %∼38 %. This research provides an effective guidance for the design of targeted observation strategies, having great significance in improving the prediction skill of KI.

黑潮入侵（Kuroshio intrusion， KI）是连接太平洋与南海的重要纽带，深刻影响着南海海洋动力和生态过程的变异性。由于KI机制复杂且缺乏可预见性研究，KI预测的准确性仍然有限。本研究利用区域海洋模拟系统（ROMS）和条件非线性最优摄动（CNOP）方法获得了KI的最快增长初始误差（f吉斯）。具体来说，CNOP是指在一定约束条件下，能够导致目标函数在目标时间达到最大值的扰动，它是计算非线性系统中fgf的有效方法。计算结果表明，两种类型的fgf具有相似的空间格局，但符号相反。当叠加在背景场上时，这两种误差都表现出快速增长和向西北传播。在预测时，海面高度误差为正的CNOP+和海面高度误差为负的CNOP-分别导致KI的显著高估和显著低估。值得注意的是，CNOP-错误甚至可能导致完全无法预测KI的发生。误差的快速增长主要源于参考状态纬向速度切变引起的正压不稳定。通过初始总能量误差垂直积分确定的目标观测敏感区域，从吕宋海峡南部向西北延伸至南海内部，中心在120.5°E， 20°N附近。值得注意的是，去除该敏感区域（仅覆盖总模型域的0.1%）内的初始误差可以最有效地提高KI预测精度，提高25% ~ 38%。本研究为针对性观测策略的设计提供了有效的指导，对提高KI的预测能力具有重要意义。

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引用次数: 0

Wind-driven exchange flow and inter-basin connectivity in a multi-inlet bay during hurricane and non-hurricane periods 飓风和非飓风期间多入口海湾的风驱动交换流和盆地间连通性

IF 2.9 3区地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES

Ocean Modelling

Pub Date : 2026-02-01 Epub Date: 2025-08-31 DOI: 10.1016/j.ocemod.2025.102624

Wei Huang , Chunyan Li , Arnoldo Valle-Levinson , Daniel Gann , Michael C. Sukop , Jayantha T. Obeysekera , Tiffany Troxler

This study quantifies wind-induced water volume exchanges through bay-ocean interfaces and among sub-bays of a multiple-inlet estuary, Biscayne Bay in Florida. The bay is elongated and oriented roughly in the north-south direction. Numerical simulations were conducted for both typical and extreme (Hurricane Irma) wind conditions. Results show that wind forcing accounts for 〈 10 % of total volume exchanges during typical winds but for 〉 60 % during hurricane conditions. Further, volume transport through seven inlets and five inter-basin transects is mainly driven by the North wind component (∼ parallel to the orientation of the bay). As a result, the major outflow through inlets is related to Ekman transport driven by southerly (or northward) winds. Except for the fifth inlet, volume transport through all the other six inlets is outward under southerly wind (R²>0.65). In contrast, southward inter-basin transports are mainly driven by northerly (or southward) wind and northward transports by southerly (or northward) wind. Inter-basin volume transport is highly related with the N-S wind (R² >0.74), i.e., the northward/southward transport is in line with the southerly/northerly wind. Additionally, the forcing-response joint Empirical Orthogonal Function (EOF) analysis shows that Biscayne Bay exhibits only one predominant exchange pattern, which explains > 90 % under typical winds and > 80 % during hurricane winds.

本研究量化了佛罗里达州比斯坎湾（Biscayne Bay）一个多入口河口的海湾-海洋界面和子海湾之间的风致水量交换。海湾呈细长状，大致面向南北方向。数值模拟了典型和极端（飓风Irma）风条件。结果表明，在典型风条件下，风强迫占总体积交换的10%以下，而在飓风条件下，风强迫占60%以上。此外，通过七个入口和五个盆地间横断面的体积运输主要由北风分量驱动（与海湾方向平行）。因此，通过入口的主要流出与南风（或北风）驱动的Ekman运输有关。除第5进气道外，其余6个进气道在南风条件下均为向外输送（R2>0.65）。南向的盆地间运输主要由北风（或南风）驱动，向北的盆地间运输主要由南风（或北风）驱动。盆地间体积输送与南南风高度相关（R2 >0.74），即向北/向南输送与南北风一致。此外，强迫-响应联合经验正交函数（EOF）分析表明，比斯坎湾仅表现出一种主要的交换模式，在典型风和飓风中分别解释了90%和80%。

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引用次数: 0

Impacts of a layered snow density evolution scheme on Arctic snow and sea ice simulation in the CICE sea ice model 分层雪密度演变方案对CICE海冰模式下北极雪和海冰模拟的影响

IF 2.9 3区地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES

Ocean Modelling

Pub Date : 2026-02-01 Epub Date: 2025-10-15 DOI: 10.1016/j.ocemod.2025.102640

Hao Yin , Jie Su , Jiping Liu , Mingfeng Wang

Snow density plays crucial roles in snow and sea ice thermodynamics. However, current coupled global climate models typically rely on empirical constants for snow properties in sea ice model components, limiting our understanding of how snow processes influence snow and sea ice evolution. To address this, we implemented a layered snow density parameterization in the Los Alamos Sea Ice Model (CICE), which explicitly considers strain compaction, wind-driven compaction, and fresh snow deposition. Compared to the control run, our experiments show that this scheme reduces wintertime positive bias in snow depth and cold bias in snow temperature in the Arctic. The reduction in winter conductivity heat loss accounts for the improvement in temperature biases, resulting in an enhanced net surface energy gain in the winter. Eighty-five percent of this additional energy gain is attributed solely to the density-dependent variation of the snow thermal conductivity over the Arctic. Further spatiotemporal analysis reveals distinct seasonal difference in the drivers of snow depth and density changes. Wind compaction and snowfall emerge as competing processes in winter, while ablation dominates during June and July. Their contributions to pan-Arctic multi-year mean snow density change are +0.161 (wind compaction), -0.198 (snowfall), +0.016 (strain compaction), +0.012 (phase changes), and -0.003 (snow-ice) kg·m^-3·hr^-1. The corresponding rates of snow depth changes are -0.095, +0.277, -0.020, -0.103, and -0.009 cm·day^-1.

雪密度在雪和海冰热力学中起着至关重要的作用。然而，目前的耦合全球气候模式通常依赖于海冰模式分量中雪特性的经验常数，这限制了我们对雪过程如何影响雪和海冰演变的理解。为了解决这个问题，我们在洛斯阿拉莫斯海冰模型（CICE）中实现了分层雪密度参数化，该模型明确考虑了应变压实、风力压实和新雪沉积。与对照运行相比，我们的实验表明，该方案减少了冬季雪深的正偏和北极雪温的冷偏。冬季电导率热损失的减少说明了温度偏差的改善，从而在冬季增加了净表面能增益。85%的额外能量增益完全归因于北极上空积雪热导率的密度依赖性变化。进一步的时空分析表明，积雪深度和积雪密度变化的驱动因素存在明显的季节差异。冬季以风压实和降雪为竞争过程，6、7月以消融为主。它们对泛北极多年平均雪密度变化的贡献分别为+0.161（风压实）、-0.198（降雪）、+0.016（应变压实）、+0.012（相变）和-0.003（雪冰）kg·m-3·hr-1。相应的雪深变化率分别为-0.095、+0.277、-0.020、-0.103和-0.009 cm·day-1。

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引用次数: 0

Evolution of wind-generated shallow water waves in a Benney–Luke equation Benney-Luke方程中风力产生的浅水波浪的演化

IF 2.9 3区地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES

Ocean Modelling

Pub Date : 2026-02-01 Epub Date: 2025-12-02 DOI: 10.1016/j.ocemod.2025.102659

Montri Maleewong , Roger Grimshaw

In our recent papers Maleewong and Grimshaw (2024b, 2025), we used the Korteweg–de Vries (KdV) equation and its two-dimensional extension, the Kadomtsev–Petviashvili (KP) equation to describe the evolution of wind-driven water wave packets in shallow water. Both equations were modified to include the effect of wind forcing, modelled using the Miles critical level instability theory. In this paper that is extended to a Benney–Luke (BL) equation, similarly modified for wind forcing. The motivation is that the BL equation is isotropic in the horizontal space variables, unlike the KP model, and noting that the KdV model is one-dimensional. The modified BL equation is studied using wave modulation theory as in our previous work on the forced KdV and KP equations, and with comprehensive numerical simulations. Despite the very different spatial structure the results show that under the right initial conditions and parameter settings, solitary wave trains again emerge.

在我们最近的论文Maleewong和Grimshaw （2024b, 2025）中，我们使用了Korteweg-de Vries （KdV）方程及其二维扩展Kadomtsev-Petviashvili （KP）方程来描述浅水中风力水波包的演化。两个方程都进行了修改，以包括风强迫的影响，使用迈尔斯临界水平不稳定理论建模。本文将其推广为对风强迫进行类似修正的Benney-Luke （BL）方程。动机是BL方程在水平空间变量中是各向同性的，不像KP模型，并且注意到KdV模型是一维的。与之前研究强制KdV和KP方程一样，本文采用波调制理论对修正后的BL方程进行研究，并进行了全面的数值模拟。结果表明，在适当的初始条件和参数设置下，孤波列再次出现。

引用次数: 0

Local effect of a submesoscale parameterization scheme and its remote influences on large-scale circulation in the Northwest Pacific 一个亚中尺度参数化方案的局地效应及其对西北太平洋大尺度环流的远程影响

IF 2.9 3区地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES

Ocean Modelling

Pub Date : 2026-02-01 Epub Date: 2025-10-31 DOI: 10.1016/j.ocemod.2025.102650

Ziyi Zhang , Bo An , Zhiwei Zhang , Yuyang Guo , Jinchao Zhang , Zhe Feng , Yongqiang Yu

Submesoscale processes play important roles in vertical heat and mass transport, modulating mesoscale eddies and the energy cycle; thus a parameterization is essential for most ocean models due to submesoscale’s spatial scales (∼100 m–10 km). This study describes the impact of the submesoscale parameterization scheme by Zhang et al. (2023; Zhang23) in a regional eddy-resolving ocean model in the North Pacific. Compared with the numerical experiment without the scheme, the simulated winter mixed-layer depth (MLD) bias is reduced by 70 % in the Kuroshio Extension (KE) region and the KE jet shifted southward from 36.5°N to 35.5°N, closer to observations. Surface cold biases at 32°–34°N and subsurface warm biases at 36–40°N are reduced by ∼1 °C and ∼2 °C across four seasons, respectively. The effect of submesoscale vertical buoyancy fluxes (VBF) on winter MLD is debated. While widely shown to promote basin-scale shoaling via restratification, they are also known to cause powerful, localized deepening in regions with strong fronts and air-sea interaction. Focusing on this latter scenario, our study reveals a more detailed mechanism, notably distinguishing between local (direct) and remote (indirect) impacts on circulation in the mixed layer and subsurface. Enhanced submesoscale VBF drives weather-scale MLD deepening and subduction along tilted isopycnals in boreal winter in the most active eddy region, mainly limited to 38°–42°N/140°–150°E, promoting southward subsurface cooling and strengthening ocean memory. This feedback modulates the KE's large-scale circulation by shifting its path southward, reducing downstream heat transport, and promoting stratification and shoaling in the eastern region throughout all seasons. These findings demonstrate the importance of submesoscale parameterization for improving simulations of western boundary current systems and highlight its effects in representing remote and subsurface dynamic processes.

亚中尺度过程在垂直热质输运、调节中尺度涡旋和能量循环中起重要作用；因此，由于亚中尺度的空间尺度（~ 100 m-10 km），对大多数海洋模式来说，参数化是必不可少的。本文描述了Zhang et al. （2023; Zhang23）的亚中尺度参数化方案对北太平洋区域涡旋解析海洋模式的影响。与不采用该方案的数值试验相比，模拟黑潮延伸（KE）地区冬季混合层深度（MLD）偏差减小了70%，KE急流从36.5°N向南移动至35.5°N，与观测值更接近。在32°-34°N的地表冷偏差和36-40°N的地下暖偏差在四个季节中分别减少了~ 1°C和~ 2°C。讨论了亚中尺度垂直浮力通量（VBF）对冬季MLD的影响。虽然它们被广泛证明可以通过再酸化促进盆地尺度的浅滩化，但在锋面强和海气相互作用的地区，它们也会导致强大的局部深化。针对后一种情况，我们的研究揭示了更详细的机制，特别是区分了对混合层和地下环流的局部（直接）和远程（间接）影响。亚中尺度VBF的增强，在最活跃的涡动区（主要局限于38°-42°N/140°-150°E），驱动了北纬冬季天气尺度MLD沿倾斜等平线加深和俯冲，促进了向南的地下冷却，增强了海洋记忆。这种反馈调节了KE的大尺度环流，使其路径南移，减少了下游的热输送，并在整个季节促进了东部地区的分层和浅滩化。这些发现表明了亚中尺度参数化对于改善西部边界流系统模拟的重要性，并突出了其在表征远程和地下动力过程方面的作用。

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引用次数: 0

Assessing basin scale modelling for projecting storm surge extremes under climate change scenarios in northwest Ireland 评估在爱尔兰西北部气候变化情景下预测极端风暴潮的流域尺度模型

IF 2.9 3区地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES

Ocean Modelling

Pub Date : 2026-02-01 Epub Date: 2025-12-03 DOI: 10.1016/j.ocemod.2025.102660

Tasneem Ahmed , Andrea Cucco , Giovanni Quattrocchi , Leo Creedon , Iulia Anton , Michele Bendoni , Stefano Taddei , Carlo Brandini , Salem S Gharbia

This study evaluates the performance of the SHYFEM (System of HydrodYnamic Finite Element Modules) ocean model in simulating storm surges within Donegal Bay (northwest Ireland) for climate projection applications. A high-resolution Basin Scale Model (BSM) configuration of SHYFEM, spanning the North Atlantic is employed in barotropic mode accounting exclusively for atmospheric forcing with no tidal contribution included. To evaluate its accuracy, the BSM is compared against a Limited Area Model (LAM) configuration of SHYFEM implemented at the same study site.

The LAM includes tidal constituents through the downscaling of sea surface height (SSH) from a calibrated deep-water ocean model provided by the Copernicus Marine Environment Monitoring Service (CMEMS). Comparison is performed to quantify the impact of non-linear tide-surge interaction on residual water levels computation.

On average the LAM achieves 3 cm greater accuracy than the BSM in reproducing the time series of residual water levels measured by four tide gauges within the bay. Nevertheless, although both models tend to underestimate the extreme values, the BSM better captures the climatological statistics of storm surge events, closely matching the observed return levels associated with 5, 10, 25, and 50 year return periods.

Further improvements in return level estimates and residual water level error metrics are obtained through iterative calibration of main model parameters, validating the BSM’s effectiveness in simulating storm surges despite the absence of tide-surge interaction.

A Chi-squared significance test applied to tide gauge observations confirms that tide-surge interaction is statistically non-significant within Donegal Bay for surge thresholds at the 99th, 99.95th, and 99.99th percentiles. These findings support the use of BSM, driven exclusively with atmospheric fields (without including tides), for reliable simulation of storm surges and their climatological statistics in this region.

本研究评估了SHYFEM（水动力有限元模块系统）海洋模式在模拟多尼戈尔湾（爱尔兰西北部）风暴潮中的气候预测应用的性能。采用横跨北大西洋的高分辨率盆地尺度模式（BSM）配置，在正压模式下只考虑大气强迫，不包括潮汐贡献。为了评估其准确性，将BSM与在同一研究地点实施的SHYFEM的有限区域模型（LAM）配置进行了比较。通过哥白尼海洋环境监测服务（CMEMS）提供的校准深水海洋模型，通过降低海面高度（SSH）的比例，LAM包括潮汐成分。通过比较来量化非线性潮涌相互作用对剩余水位计算的影响。在重现湾内四个潮汐计所测得的剩余水位时间序列时，LAM的准确度比BSM平均高3厘米。然而，尽管两种模式都倾向于低估极端值，但BSM更好地捕捉了风暴潮事件的气候统计数据，与观测到的与5年、10年、25年和50年的回归期相关的回归水平密切匹配。通过对主要模型参数的迭代校准，进一步改进了回归水位估计和剩余水位误差指标，验证了BSM在没有潮涌相互作用的情况下模拟风暴潮的有效性。应用于验潮仪观测的卡方显著性检验证实，在第99、99.95和99.99百分位的潮涌阈值上，多尼戈尔湾内的潮涌相互作用在统计上不显著。这些发现支持使用仅由大气场（不包括潮汐）驱动的BSM来可靠地模拟该地区的风暴潮及其气候统计。

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引用次数: 0

Improving multi-variable wave forecasting with AI: Integrating LSTM and random forest, using a window and flatten technique 用人工智能改进多变量波浪预报：结合LSTM和随机森林，利用窗口和平坦化技术

IF 2.9 3区地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES

Ocean Modelling

Pub Date : 2026-02-01 Epub Date: 2025-10-06 DOI: 10.1016/j.ocemod.2025.102638

Nerea Portillo Juan, Mónica Ferrer Gómez-Cano, Sara Yagüe Rubio, Vicente Negro Valdecantos

Accurate wave prediction is essential for coastal and ocean engineering, as sea state conditions directly impact the design and operation of marine infrastructure, renewable energy systems, and maritime safety. While most research focuses on forecasting significant wave height (Hs) using increasingly complex models, other essential variables such as wave period (Tp) and direction (Dir) are often overlooked despite their importance in fully characterizing sea states.

This study addresses this gap by applying Artificial Intelligence (AI) models – Long Short-Term Memory (LSTM) networks and Random Forests (RF) – to predict Hs, Tp, and Dir. A novel window and flatten technique was introduced to restructure temporal data into a format suitable for machine learning, enhancing model performance for Dir and Tp predictions. Both models were tested under various wave conditions in the Mediterranean Sea

Results show that LSTM generally outperforms RF, particularly for Dir. However, RF models, which are not inherently designed for time series tasks, performed surprisingly well for Hs prediction and for short term Tp predictions. This opens promising avenues for developing hybrid models that combine sequential and non-sequential methods, potentially surpassing traditional sequence-to-sequence approaches in accuracy and robustness.

The study also highlights the challenge of accurately modelling Tp and the importance of evaluating model performance under varying energy conditions. Significant sensitivity to testing scenarios was observed, underlining the need for careful dataset selection and model validation. These findings provide a foundation for extending wave forecasting tools to more energetic environments such as the Atlantic Ocean and for advancing hybrid AI-based prediction frameworks.

准确的海浪预测对于沿海和海洋工程至关重要，因为海况条件直接影响海洋基础设施、可再生能源系统和海上安全的设计和运行。虽然大多数研究都集中在使用日益复杂的模型预测有效波高（Hs），但其他基本变量，如波浪周期（Tp）和方向（Dir），尽管它们在充分表征海况方面很重要，但往往被忽视。本研究通过应用人工智能（AI）模型-长短期记忆（LSTM）网络和随机森林(RF) -来预测Hs， Tp和Dir，从而解决了这一差距。引入了一种新的窗口和平坦技术，将时间数据重构为适合机器学习的格式，提高了Dir和Tp预测的模型性能。两种模型都在地中海的各种波浪条件下进行了测试。结果表明，LSTM总体上优于RF，特别是对于Dir。然而，RF模型本身并不是为时间序列任务而设计的，它在Hs预测和短期Tp预测中表现得出奇地好。这为开发结合序列和非序列方法的混合模型开辟了有希望的途径，有可能在准确性和鲁棒性方面超越传统的序列对序列方法。该研究还强调了准确建模Tp的挑战以及在不同能量条件下评估模型性能的重要性。观察到对测试场景的显着敏感性，强调需要仔细选择数据集和模型验证。这些发现为将海浪预报工具扩展到大西洋等能量更大的环境以及推进基于人工智能的混合预测框架提供了基础。

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引用次数: 0

Modelling wave dissipation and mean water level over salt marshes 模拟盐沼上的波浪耗散和平均水位

IF 2.9 3区地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES

Ocean Modelling

Pub Date : 2026-02-01 Epub Date: 2025-12-12 DOI: 10.1016/j.ocemod.2025.102672

Laura Lavaud , Xavier Bertin , Kévin Martins

Besides its well-known capacity to dissipate wave energy, salt marsh vegetation can also affect wave setup, although this mechanism has been much less studied and quantified so far. This study reports on a field experiment conducted under moderate energy conditions across a French Atlantic salt marsh. The data analysis is complemented with numerical simulations performed with the 3D fully-coupled wave–current modelling system SCHISM. While the model could already resolve vegetation-induced drag on mean currents and turbulence, it was here extended to account for vegetation intrawave drag effects and the wave force associated with vegetation-induced dissipation. Using published lab data, we first verify the model’s capacity to reproduce wave dissipation by vegetation and its effect on mean water levels, namely a reduction in wave setup, which is controlled by wave–current-vegetation interactions including intrawave processes. In the field, the model also demonstrates good predictive skills in simulating wave parameters across vegetation and suggests that vegetation can decrease the wave setup. However, this last process was too modest to be measured with pressure transducers, calling for future field experiments under storm conditions. This capacity of vegetation to reduce nearshore mean water levels should be thoroughly considered when evaluating the potential of salt marshes as nature-based coastal protection. This study places the SCHISM model as a state-of-the-art, efficient tool to simulate 3D multi-scale wave–current processes over vegetation ecosystems. Our results finally highlight that vegetation and depth-induced breaking induce a frequency-dependent dissipation, whose representation in phase-averaged models is presently limited and will require future research.

除了众所周知的耗散波浪能量的能力外，盐沼植被还可以影响波浪的形成，尽管迄今为止对这一机制的研究和量化都要少得多。本研究报告了在法国大西洋盐沼的中等能量条件下进行的现场试验。数据分析与三维全耦合波流模拟系统SCHISM的数值模拟相辅相成。虽然该模型已经可以解决平均海流和湍流中植被引起的阻力，但这里将其扩展到考虑植被波内阻力效应和与植被引起的耗散相关的波浪力。利用已发表的实验室数据，我们首先验证了该模型再现植被耗散波的能力及其对平均水位的影响，即波浪设置的减少，这是由波-流-植被相互作用控制的，包括波内过程。在野外，该模型在模拟跨植被的波浪参数方面也显示出良好的预测能力，并表明植被可以减少波浪的设置。然而，最后一个过程过于温和，无法用压力传感器测量，需要在未来的风暴条件下进行现场实验。在评估盐沼作为基于自然的海岸保护的潜力时，应充分考虑到植被降低近岸平均水位的能力。本研究将SCHISM模型作为模拟植被生态系统上三维多尺度波流过程的最先进、最有效的工具。我们的研究结果最后强调，植被和深度诱发的断裂引起频率相关耗散，其在相位平均模型中的表示目前是有限的，需要进一步的研究。

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引用次数: 0

West-East asymmetry in the South Pacific Western subtropical mode water 南太平洋西副热带模态水的东西不对称性

IF 2.9 3区地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES

Ocean Modelling

Pub Date : 2026-02-01 Epub Date: 2025-12-11 DOI: 10.1016/j.ocemod.2025.102670

Xueying Wang, Yiyong Luo, Yingying Wang, Ruiyi Chen

This study investigates the spatio-temporal variability and forcing mechanisms of the South Pacific western subtropical mode water (SPWSTMW) using the RG-Argo observations and the eddy-resolving GLORYS12 reanalysis from 2004 to 2023. The SPWSTMW exhibits pronounced zonal asymmetries in both its variability and forcing processes. To better understand these west-east asymmetries, we divide the SPWSTMW into the West (150°E–160°E) and East (160°E–170°W) types. On a seasonal timescale, the West type forms approximately one month earlier than the East type, primarily due to enhanced heat convergence from the mean flow and associated eddies of the East Australian Current. These oceanic processes effectively offset winter surface heat loss, accelerating upper-ocean restratification and subduction. On an interannual timescale, the East type volume correlates strongly with El Niño-Southern Oscillation (ENSO) through direct atmospheric forcing. However, the West type volume shows no significant correlation with ENSO, resulting from the complex interaction of surface heat flux, mean flow-induced heat convergence, and eddy-induced heat convergence. These findings underscore the critical role of regional ocean dynamics in modulating SPWSTMW variations.

利用2004 - 2023年RG-Argo观测资料和gloys12涡旋再分析资料，研究了南太平洋西部副热带模态水（SPWSTMW）的时空变化及其强迫机制。SPWSTMW在变率和强迫过程中都表现出明显的纬向不对称性。为了更好地理解这些东西不对称，我们将SPWSTMW分为西（150°E - 160°E）和东（160°E - 170°W）两类。在季节时间尺度上，西型比东型早形成大约一个月，主要是由于东澳大利亚洋流的平均流和相关漩涡增强了热辐合。这些海洋过程有效地抵消了冬季地表热损失，加速了上层海洋的再冰化和俯冲。在年际尺度上，东型体积通过大气直接强迫与El Niño-Southern涛动（ENSO）密切相关。而西型体积与ENSO的相关性不显著，这是地表热通量、平均流致热辐合和涡旋致热辐合复杂相互作用的结果。这些发现强调了区域海洋动力学在调节SPWSTMW变化中的关键作用。

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引用次数: 0

Surface current detection in regional seas using Lagrangian coherent structures 基于拉格朗日相干结构的区域海洋表面流探测

IF 2.9 3区地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES

Ocean Modelling

Pub Date : 2026-02-01 Epub Date: 2025-10-31 DOI: 10.1016/j.ocemod.2025.102647

Huy Cong Vu, Binh Quang Nguyen

Eddies play a vital role in the transport of heat, salt, and other materials, as well as in shaping the circulation structure of the ocean. Understanding eddies is therefore essential for elucidating the mechanisms that govern the formation, evolution, and variability of ocean currents. This study aims to analyze the characteristics of ocean currents in the East Vietnam Sea (South China Sea–SCS) by combining two approaches: the Euler method and the Lagrangian Coherent Structures (LCS) method. This integrated approach provides a comprehensive understanding of current dynamics and eddy formation. Using velocity vector images (Euler method), the study identifies the direction, location, and intensity of major ocean currents in the SCS. Meanwhile, the LCS method is applied to detect and delineate the boundaries and sizes of eddies. The ocean current data were obtained from the global HYCOM model on a daily basis throughout 2023. Our findings indicate that: (i) ocean currents in the SCS exhibit a clear seasonal pattern. In winter, the dominant flow moves from north to south along the Vietnamese coast, while in summer, the flow reverses, moving from south to north, with a disruption near 11 °N close to the Vietnamese coast. The current can extend up to 220 km near China, narrowing to 56 km as it approaches Vietnam. (ii) A table summarizing the characteristics of eddies with diameters greater than 100 km is included. The number of eddies is higher during the summer, but larger eddies tend to occur during the winter. In addition to single eddies, the SCS is also home to double and triple eddies.

漩涡在热、盐和其他物质的运输中起着至关重要的作用，也在塑造海洋的环流结构中起着至关重要的作用。因此，了解涡流对于阐明控制洋流形成、演化和变化的机制至关重要。本研究旨在结合欧拉方法和拉格朗日相干结构（LCS）方法分析东越南海（南中国海）洋流特征。这种综合方法提供了对电流动力学和涡流形成的全面理解。利用速度矢量图像（欧拉法），该研究确定了南海主要洋流的方向、位置和强度。同时，利用LCS方法对涡流的边界和大小进行检测和圈定。2023年的海流数据来自全球HYCOM模型的每日数据。我们的研究结果表明：(1)南海洋流表现出明显的季节性模式。冬季主要气流沿越南海岸由北向南移动，夏季主要气流由南向北移动，在靠近越南海岸的11°N附近出现中断。洋流在中国附近可以延伸220公里，在接近越南时缩小到56公里。（ii）附有一个表，概述了直径大于100公里的涡流的特征。涡旋的数量在夏季较高，但较大的涡旋往往发生在冬季。除了单涡旋外，南海还有双涡旋和三涡旋。

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引用次数: 0