Ocean Modelling最新文献

The transformation of wave height is of paramount significance in coastal engineering and the design of coastal structures. Considering the influence of air bubbles, this study devised an optimal dissipation model for accurately calculating changes in significant wave height (H_m0) and wave set-up for irregular waves undergoing breaking. Existing regular wave breaking models, which consider the effects of air bubbles, were adapted for direct application to irregular waves by deriving novel formulations. The proposed models leverage the probability of the fraction of broken waves. H_m0 was computed using the energy balance equation, while the wave set-up was calculated based on the momentum balance equation. A wide range of test scenarios, incorporating diverse scales (small and large) and experimental field data, was considered for validation. One of the proposed models, namely model-I (M-I), particularly demonstrated superior performance, manifesting lower error indices (P20), root-mean-square relative error (RMSRE), and Brier skill score (BSS) values in computing both H_m0 and wave set-up. Therefore, utilising M-I is strongly recommended for the precise estimation of H_m0 and set-up transformation.

In polar regions, sea ice linear kinematic features (LKFs) play a critical role in the exchange of mass and energy between the ocean and atmosphere. These features also serve as an important reference for navigation decision, highlighting the growing need to accurately monitor and simulate their changes. An identification and labeling method using artificial intelligence (AI) to detect LKFs based on Synthetic Aperture Radar (SAR) data is proposed in this study. This approach uses sea ice deformation data derived from sea ice drift in the SAR observations and employs a specialized encoder–decoder convolutional neural network, known as LadderNet, to segment these fine-grained LKFs. A post-processing algorithm utilizing connected region detection further assigns markers for individual LKFs. Results show that our detection method has a higher accuracy with F1 Scores ranging between 0.6 and 0.7 than that using UNET architecture. Training the AI model with seasonal data effects the detection results slightly. Compared to the classical algorithm, our study also demonstrates more consistent detection results for both numerical model and observations regardless of practical parameters after training, which provides a standardized metric for inter-comparisons between models and observations.

The oblique interactions between internal solitary waves frequently occur in the ocean owing to their different propagation directions after originated from more than one potential generation sites, which can further be modulated and reshaped by the varying topography and the Earth’s rotation. Here a variable-coefficient rotational Kadomtsev–Petviashvili (KP) equation is devoted to investigate the interaction of initial X-shaped waves in presence of the respective one-dimensional (1D) and two-dimensional (2D) slope-shelf topography and rotations at different latitudes. Based on the analytical solutions, the long-time results can be classified as three types depending on the initial amplitudes and oblique angles. Then, numerical results suggest that the sufficiently shallow 1D shoaling topography can render polarity change, which reshapes the waveform of oblique interactions to resemble webs composed of straight wave crest lines. If the rotation were also taken into account, then the nonlinear interactions are inhibited resulting in less waves in the eventual long-time wave packets and more junction points in the webs of waveform. More importantly, the combined effect of rotation and localized small and narrow canyons and plateaus resting on 1D shoaling topography can significantly modulate the waveforms induced by oblique interactions to make them more like rank-ordered wavetrains.

Despite tremendous progress in algorithm development, computational efficiency and transition into operations over the past two decades, coastal modeling still lacks scientific rigor due to proliferation of many ‘gray’ areas related to various modeling choices made by modelers. In this paper, we propose some guiding principles for the modeling community to improve performance, and we also debunk commonly held myths that make the coastal modeling lack rigor. Using our own experience in developing seamless cross-scale unstructured-grid based models for the past two decades, we describe in unprecedented detail the end-to-end modeling process (i.e., from digital elevation models (DEMs) to mesh generation to post analysis), and demonstrate that defensible modeling is within reach for any end user by following three guiding principles: (1) Bathymetry is a first order forcing in coastal domains and thus should be respected in all aspects of modeling; (2) Oceanographic processes are driven across multiple spatial scales and so models should enable appropriate resolution as needed; and (3) Model assessment should focus on physical processes. Through qualitative and quantitative model assessments, we demonstrate the fundamental role played by bathymetry/topography as embedded in DEMs in making the results defensible, which is unfortunately glossed over in many modeling studies. Focusing on process-based assessment simplifies the calibration process. A major conclusion of this work is that model developers and operators should maximize the scientific rigor for in silico oceanography by avoiding some common pitfalls that rely on error compensation at the expense of representation of physical system processes. We present some best practice procedures for defensive and trustworthy numerical modeling.

The Lombok Strait shows active large-amplitude internal solitary waves (ISWs) and is also a primary gateway for the Indonesian Throughflow (ITF), which is a critical ocean current affecting the ocean ecosystem. This study collected 858 satellite images from 2018 to 2022, and ISW wave crests were extracted. Analysis shows that ISW 5-year cumulative occurrences reached the highest/ lowest of 136/28 days, with a 29 %/6 % frequency in October/ June. Satellite and reanalysis data revealed that ISW occurrence and propagation speed correlate to ITF variations. Enhanced southward ITF corresponds to less ISW occurrence and decreased/increased northward/southward ISW propagation speed. To understand how ITF modulates ISWs, three-dimensional MITgcm simulations were employed. Results show that when southward ITF decreases, ISWs tend to generate earlier/later, thus leading to a longer/shorter propagation distance for ISWs in the north/ south direction, revealing a suppressive effect on northward ISW generation.

Marine heatwaves (MHWs) are discrete yet persistent events of anomalously warm ocean temperatures which are becoming a hot topic in climate change research due to their extensive disruption of marine ecosystems worldwide. As a consequence, surface MHW events (SMHWs) and their drivers have been characterised worldwide typically under a consolidated common methodology. However, subsurface and bottom events of MHW (BMHWs) are less known due to the limited availability of data. Furthermore, recent advances suggest an improved MHW definition to distinguish the extreme event from the long-term ocean warming. Here, we use high-resolution GLORYS12V1 reanalysis data from 1993 to 2022 to characterise both SMHWs and BMHWs along the Spanish Marine Demarcation (SMD) areas defined within the Marine Strategy Framework Directive. We also broadly analyse their interconnections and ultimately generate a regional assessment of the integrated exposure of SMD to MHWs. We find that both SMHWs and BMHWs were more intense, longer-lasting, and widespread over the last 15 years. We also find that while SMHWs exhibit spatial variation following heat fluxes anomalies in the ocean surface layers, BMHWs roughly scale with ocean bottom depth and persist longer than their surface counterparts. Further, in shallower coastal regions where the mixed layer extends to the ocean bottom, average BMHW intensities can be comparable or even higher than those concurrently overlaying at the surface. Finally, we also demonstrate that both SMHWs and BMHWs are more likely to co-occur with high cumulative intensities in coastal SMD areas, with the 69% of their spatial extent categorised as highly exposed to MHWs. This highlights the imperative need for analysing and integrating SMHWs and BMHWs, especially in coastal zones, when assessing and addressing present and future impacts on wildlife and economies under the expected climate change scenario.

Swell waves, characterized by the long wavelength components generated by distant weather systems or storms, exert a significant influence on various air–sea interaction processes, thereby impacting weather and climate systems. Over recent decades, substantial progress has been achieved in comprehending the dynamics of swell waves and their implications for air–sea interactions. This paper presents a comprehensive review of advancements and key findings concerning surface swell waves and their interactions with the atmosphere. It encompasses a range of topics, including wave growth theory, the effects of swell waves on air–sea momentum, heat, and mass fluxes, as well as their influence on atmospheric turbulence and mixed layer processes. The most important characteristics of the swell impact (where it differs from wind sea conditions) are the wave-induced upward component of the surface stress leading to alteration of total surface stress, generation of a low-level wind maxima or changed wind profile and change of scale and behaviour of turbulence properties (turbulence kinetic energy and integral length scale). Furthermore, the paper explores the modelling of swell dissipation, the integration of swell influences in weather and climate models, and the broader climatic implications of surface swell waves. Despite notable advances in understanding swell processes, persistent knowledge gaps remain, underscoring the need for further research efforts, which are outlined in the paper.

Ocean general circulation models at the eddy-permitting regime are known to under-resolve the mesoscale eddy activity and associated eddy-mean interaction. Under-resolving the mesoscale eddy field has consequences for the resulting mean state, affecting the modelled ocean circulation and biogeochemical responses, and impacting the quality of climate projections. There is an ongoing debate on whether and how a parameterisation should be utilised in the eddy-permitting regime. Focusing on the Gent–McWilliams (GM) based parameterisations, it is known that, on the one hand, not utilising a parameterisation leads to insufficient eddy feedback and results in biases. On the other hand, utilising a parameterisation leads to double-counting of the eddy feedback, and introduces other biases. A recently proposed approach, known as splitting, modifies the way GM-based schemes are applied in eddy-permitting regimes, and has been demonstrated to be effective in an idealised Southern Ocean channel model. In this work, we evaluate whether the splitting approach can lead to improvements in the physical and biogeochemical responses in an idealised double gyre model. Compared with a high resolution mesoscale eddy resolving model truth, the use of the GM-based GEOMETRIC parameterisation together with splitting in the eddy-permitting regime leads to broad improvements in the control pre-industrial scenario and an idealised climate change scenario, over models with and models without the GM-based GEOMETRIC parameterisation active. While there are still some deficiencies, particularly in the subtropical region where the transport is too weak and may need momentum re-injection to reduce the biases, the present work provides further evidence in support of using the splitting procedure together with a GM-based parameterisation in ocean general circulation models at eddy-permitting resolutions.

The ocean is a key player in the Earth's climate, absorbing heat and carbon dioxide from the atmosphere. The ocean's temperature and salinity are influenced by climate change, which can significantly impact marine ecosystems. Reliable data sets of atmospheric and oceanographic parameters are of special interest in coastal productive areas to adequately monitor their variability at regional and local levels. It is therefore essential to continue monitoring and studying the ocean to develop effective mitigation and adaptation strategies. In this context, the main aim of this study is to identify the Earth System Models (ESMs) from the Coupled Model Intercomparison Project 6 (CMIP6) that best capture the variability of water temperature, salinity, and wind speed along the continental Spanish coasts, using them to estimate future impacts in these regions. To achieve this, a multifaceted approach is used, encompassing a historical (2000−2014) assessment comparing ESM outputs to in situ observations from Puertos del Estado (PdE) oceanographic buoys, an examination of the present period (2015−2022) under three IPCC scenarios (SSP1−2.6, SSP2−4.5, and SSP5−8.5), and a projection of future (2023−2100) trends using the same emission scenarios. Results showed that the ESMs from CMIP6 can reproduce the historical patterns of meteo-oceanographic properties, rendering them valuable tools for climate change studies. In the future (2100), considering the most pessimistic scenario (SSP5−8.5), the water temperature may increase by 2.8°C, salinity may decrease by -1.6, and wind speed may decrease by -0.4 m·s⁻¹. These projected changes can significantly impact the Spanish coasts, jeopardizing the growth, reproduction, survival, abundance, and distribution of some marine species.

The ocean surface albedo (OSA) is an important parameter in ocean and climate models for air-sea heat flux calculations. Current OSA schemes are either too simple, making them only suitable for clear sky conditions, or too complex, because they depend on parameters that are not often measured in conventional ocean observations. Using radiation observations at a fixed offshore platform, we propose a simple but effective parameterization scheme of OSA, in which the broadband OSA is an analytical function of both the solar zenith angle and atmospheric transparency. It depends only on the downward shortwave radiation measured at the ocean surface and applies to all sky conditions. During our 15-month radiation observations, the correlation coefficient between the calculated OSA and the observations reached 0.90 for all skies, and the root mean square deviation was 0.0130. Three other OSA observation datasets are also introduced to verify this scheme.