Search Results (248)

A FEM model of Shallow Wave Equations (SWE-FEM) is studied, taking into account the variable bathymetry of semi-enclosed sea basins. The model, with a spatially varying Coriolis term, is implemented for the description of combined refraction–diffraction effects, from which the eigenperiods and eigenmodes of extended geographical sea areas are calculated by means of a low-order FEM scheme. The model is applied to the western Mediterranean basin, illustrating its versatility to easily include the effects of geographical characteristics like islands and other coastal features. The calculated resonant frequencies and modes depend on the domain size and characteristics as well as the location of the open sea boundary, and it is shown to provide results compatible with tide measurements at several stations in the coastal region of France. The calculation of the natural oscillation modes in the western Mediterranean basin, bounded by open boundaries at the Strait of Gibraltar and the Strait of Sicily, reveals a natural period of around 6 h corresponding to the quarter-diurnal tidal components, which are stationary and of roughly constant amplitude on the northern coast of the basin and on the west coast of Corsica (France). On the east coast of Corsica, on the other hand, these components are of very low amplitude and in phase opposition. The semi-diurnal tidal components observed on the same tide gauges north of the basin and west of Corsica are also quasi-stationary although they are not resonant. Resonant oscillations are also observed at lower periods, especially at a period of around 3 h at the Sète station. This period corresponds to a higher-order natural mode of the western Mediterranean basin, but this resonance seems to be essentially linked to the presence of the Gulf of Lion, whose shallowness and the width of the shelf at this point induce a resonance. Other oscillations are also observed at lower periods (T = 1.5 h at station Fos-sur-Mer, T = 45 min in the Toulon harbour station), due to more local forcing. Full article

Sea level rise due to climate change poses an increasing threat to coastal ecosystems, infrastructure, and human settlements. However, accurately estimating sea level changes in regions without tide gauge observations remains a major challenge. While satellite altimetry provides wide spatial coverage, its accuracy diminishes near coastlines. In contrast, tide gauges offer high precision but are spatially limited. This study aims to develop an artificial neural network-based model for estimating relative sea level changes in coastal regions where tide gauge data are unavailable. Unlike conventional forecasting approaches focused on future time series prediction, the proposed model is designed to learn spatial distribution patterns and temporal rates of sea level change from a fusion of satellite altimetry and tide gauge data. A normalization scheme is applied to reduce inconsistencies in reference levels, and Bayesian optimization is employed to fine-tune hyperparameters. A case analysis is conducted in two coastal regions in South Korea, Busan and Ansan, using data from 2018 to 2023. The model demonstrates strong agreement with observed tide gauge records, particularly in estimating temporal trends of sea level rise. This approach effectively compensates for the limitations of satellite altimetry in coastal regions and fills critical observational gaps in ungauged areas. The proposed method holds substantial promise for coastal hazard mitigation, infrastructure planning, and climate adaptation strategies. Full article

This study applied an adjoint data assimilation model capable of integrating wind fields to investigate a temperate storm surge event in the Bohai Sea region during October 18 to 21, 2024. Based on in situ water level measurements from five tide gauge stations, the model simulated the spatial distributions of water levels under different wind stress drag coefficients (C_D) schemes driven by reanalysis wind fields and interpolated wind fields. The results demonstrated that the scheme without the adjoint data assimilation exhibited relatively low accuracy. Upon integrating the adjoint data assimlation method, the errors of the reanalysis wind fields were reduced by 44%, while those of the interpolated wind fields experienced a 74% decrease in error magnitude. Overall, this study provides a reference for enhancing the accuracy of water level predictions during storm surge events. Full article

This study aimed to accurately simulate the main tidal characteristics in a regional domain featuring four open boundaries, with a primary focus on baroclinic tides. Such understanding is crucial for improving the representation of oceanic energy transfer and mixing processes in numerical models. To this end, the astronomical potential, load tide effects, and a wavelet-based analysis method were implemented in the three-dimensional ROMS model. The inclusion of the astronomical tidal and load tide aimed to enhance the accuracy of tidal simulations, while the wavelet method was employed to analyze the generation and propagation of internal tides from their source regions and to characterize their main features. Twin simulations with and without astronomical potential forcing were conducted to evaluate its influence on tidal elevations and currents. Model performance was assessed through comparison with tide gauge observations. Incorporating the potential forcing improves simulation accuracy, as the model fields successfully reproduced the main features of the barotropic tide and showed good agreement with observed amplitude and phase data. A complex principal component analysis was then applied to a matrix of normalized wavelet coefficients derived from the enhanced model outputs, enabling the characterization of horizontal modal propagation and vertical mode decomposition of both $M_2$ and nonlinear $M_4$ internal tides. Full article

The primary contribution of this study lies in analyzing the dynamic drivers during two anomalous sea level rise events in the Bohai Sea through coupled numeric modeling using the Weather Research and Forecasting (WRF) model and the Finite-Volume Community Ocean Model (FVCOM) integrated with the Simulating Waves Nearshore (SWAN) module (hereafter referred to as FVCOM-SWAVE). WRF-derived wind speeds (0.05° grid resolution) were validated against Haiyang-2 (HY-2) scatterometer observations, yielding a root mean square error (RMSE) of 1.88 m/s and a correlation coefficient (Cor) of 0.85. Similarly, comparisons of significant wave height (SWH) simulated by FVCOM-SWAVE (0.05° triangular mesh) with HY-2 altimeter data showed an RMSE of 0.67 m and a Cor of 0.84. Four FVCOM sensitivity experiments were conducted to assess drivers of sea level rise, validated against tide gauge observations. The results identified tides as the primary driver of sea level rise, with wind stress and elevation forcing (e.g., storm surge) amplifying variability, while currents exhibited negligible influence. During the two events, i.e., 20–21 October and 25–26 August 2024, elevation forcing contributed to localized sea level rises of 0.6 m in the northern and southern Bohai Sea and 1.1 m in the southern Bohai Sea. A 1 m surge in the northern region correlated with intense Yellow Sea winds (20 m/s) and waves (5 m SWH), which drove water masses into the Bohai Sea. Stokes transport (wave-driven circulation) significantly amplified water levels during the 21 October and 26 August peak, underscoring critical wave–tide interactions. This study highlights the necessity of incorporating tides, wind, elevation forcing, and wave effects into coastal hydrodynamic models to improve predictions of extreme sea level rise events. In contrast, the role of imposed boundary current can be marginalized in such scenarios. Full article

Sea surface temperature (SST) is considered a strong indicator of climate change, being an essential parameter for long-range weather and climate forecasting. Another important indicator of climate change is sea level (SL), which has a longer history of systematic instrumental observations. This paper aims to examine the relationships between low-latitude variations in ocean characteristics (SST and SL) and surface air temperature (SAT) anomalies in the Arctic and mid-latitudes, and discuss the possibility of using SST and SL as predictors to forecast seasonal SAT anomalies. Archives of meteorological observations, atmospheric and oceanic reanalyses, and long-term series of tide gauge data on SL were used in this study. An analysis of relationships between seasonal SAT in different mid-to-high latitude regions and SST made it possible to identify areas in the ocean that have the greatest influence on SAT patterns. The most commonly identified area is located in the tropical North Atlantic. Another area was found in the Indo-Pacific warm pool. The predictive potential of the relationships identified between ocean characteristics (SST and SL) and SAT will be used to build deep learning models aimed at predicting climate variability in mid-to-high latitudes. Full article

The Baltic Sea is an intra-continental marginal sea that is vertically stratified with a strong halocline isolating the saline bottom layer from the brackish surface layer. The surface layer is eutrophic, and abiotic zones lacking oxygen are common in the deeper regions. While freshwater is constantly flowing into the North Sea, oxygen-rich bottom waters can only occasionally enter the Baltic Sea following a special sequence of transient weather conditions. These so-called Major Baltic Inflow events can be monitored via the sea level gradients between the Kattegat and the Western Baltic Sea. Innovative interferometric altimetry from the Surface Water and Ocean Topography (SWOT) mission gave us the first opportunity to directly observe the sea level signal associated with the inflow event in December 2023. Recent high-rate multi-mission nadir altimetry observations support the SWOT findings for scales larger than 50 km. The SWOT observations are compared to the simulations with the regional 3D HBMnoku ocean circulation model operated by the German Federal Maritime and Hydrographic Agency (BSH). The model explains more than 80% of the variance observed by SWOT and up to 90% of the variance observed by the nadir altimeters. However, the north–south gradients of the two datasets differ by about 10% of the overall gradient. Comparisons with tide gauges suggest possible model deficiencies on daily to sub-daily time scales. In addition, the SWOT data have many fine scale structures, such as eddies and fronts, which cannot be adequately modeled. Full article

Surf during typhoon events poses severe threats to coastal infrastructure and public safety. Traditional monitoring approaches, including in situ sensors and numerical simulations, face inherent limitations in capturing surf impacts—sensors are constrained by point-based measurements, while simulations require intensive computational resources for real-time monitoring. Video-based monitoring offers promising potential for continuous surf observation, yet the development of deep learning models for surf detection remains underexplored, primarily due to the lack of high-quality training datasets from typhoon events. To bridge this gap, we propose a lightweight YOLO (You Only Look Once) based framework for real-time surf detection. A novel dataset of 2855 labeled images with surf annotations, collected from five typhoon events at the Chongwu Tide Gauge Station, captures diverse scenarios such as daytime, nighttime, and extreme weather conditions. The proposed YOLOv6n model achieved 99.3% $mA{P}_{50}$ at 161.8 FPS, outperforming both other YOLO variants and traditional two-stage detectors in accuracy and computational efficiency. Scaling analysis further revealed that YOLO models with 2–5 M parameters provide an optimal trade-off between accuracy and computational efficiency. These findings demonstrate the effectiveness of YOLO-based video monitoring systems for real-time surf detection, offering a practical and reliable solution for coastal hazard monitoring under extreme weather conditions. Full article

A high-resolution numerical model called Delft3D (5 km resolution) forced with realistic high-frequency atmospheric conditions was set up to describe the circulation pattern in the Red Sea basin. The validation of the model was performed considering several tide gauge data, the SST of AVHRR/Pathfinder, and the available literature. The model outcomes show that the general circulation pattern in the Red Sea is dominated by energetic anticyclonic eddies consistent with observations in terms of both size and magnitude. We conducted two scenarios of numerical experiments considering thermohaline and wind forcing to investigate the main driving mechanism of the circulation patterns. When simulated using full forcing (wind and thermohaline), the wind forcing experiment mostly reproduces the circulation patterns. On the other hand, thermohaline forcing generates weaker circulation patterns with cyclonic eddy dominance. The model effectively replicates the reversal of the three-layer exchange flow system at the Bab el Mandeb Strait, which is enhanced by both wind and thermohaline forcing. The simulation indicates that subsurface inflow deflects along the eastern coastline of the southern part of the Red Sea. Full article

The historical City of Venice, with its lagoon, has been severely exposed to repeated marine flooding since historical times due to the combined effects of sea level rise (SLR) and land subsidence (LS) by natural and anthropogenic causes. Although the sea level change in this area has been studied for several years, no detailed flooding scenarios have yet been realized to predict the effects of the expected SLR in the coming decades on the coasts and islands of the lagoon due to global warming. From the analysis of geodetic data and climatic projections for the Shared Socioeconomic Pathways (SSP1-2.6; SSP3-7.0 and SSP5-8.5) released in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC), we estimated the rates of LS, the projected local relative sea level rise (RSLR), and the expected extent of flooded surfaces for 11 selected areas of the Venice Lagoon for the years 2050, 2100, and 2150 AD. Vertical Land Movements (VLM) were obtained from the integrated analysis of Global Navigation Satellite System (GNSS) and Interferometry Synthetic Aperture Radar (InSAR) data in the time spans of 1996–2023 and 2017–2023, respectively. The spatial distribution of VLM at 1–3 mm/yr, with maximum values up to 7 mm/yr, is driving the observed variable trend in the RSLR across the lagoon, as also shown by the analysis of the tide gauge data. This is leading to different expected flooding scenarios in the emerging sectors of the investigated area. Scenarios were projected on accurate high-resolution Digital Surface Models (DSMs) derived from LiDAR data. By 2150, over 112 km² is at risk of flooding for the SSP1-2.6 low-emission scenario, with critical values of 139 km² for the SSP5-8.5 high-emission scenario. In the case of extreme events of high water levels caused by the joint effects of astronomical tides, seiches, and atmospheric forcing, the RSLR in 2150 may temporarily increase up to 3.47 m above the reference level of the Punta della Salute tide gauge station. This results in up to 65% of land flooding. This extreme scenario poses the question of the future durability and effectiveness of the MoSE (Modulo Sperimentale Elettromeccanico), an artificial barrier that protects the lagoon from high tides, SLR, flooding, and storm surges up to 3 m, which could be submerged by the sea around 2100 AD as a consequence of global warming. Finally, the expected scenarios highlight the need for the local communities to improve the flood resiliency plans to mitigate the consequences of the expected RSLR by 2150 in the UNESCO site of Venice and the unique environmental area of its lagoon. Full article

Storm surges represent a prominent and significant natural hazard in the coastal areas of China and cause substantial human and economic losses. We investigated historical storm surge events in these areas to assess the distribution of associated hazards and to construct a storm surge hazard index. The tide-gauge data from 83 observational stations along the Chinese coast were collected, and the assessment was based on two indicators, namely the storm surge height and the exceeded water warning level of these events. Further, we conducted a vulnerability assessment of coastal counties in China using population and economic distribution data. Thereafter, the distribution of storm surge hazards and vulnerability levels was considered, and we determined the county-level risk of storm surges covering 219 coastal counties in China. The findings revealed substantial spatial variations therein, with high-risk areas in terms of the population and economic effects of such surges accounting for 25.1% (55/219) and 27.4% (60/219) of all coastal counties, respectively. These results provide preliminary insight into storm surge risks in China and have implications for the prevention and mitigation of storm surges for central government. Full article

Accurate ocean tide models are required to remove tidal loading effects in geophysical research. Beyond a mere intercomparison, the accuracy of eight modern global models (DTU10, EOT20, FES2014b, FES2022b, GOT4.10c, HAMTIDE11a, OSU12, TPXO10-atlas-v2) and one regional model (NAO99Jb) was assessed in the eastern China marginal seas (ECMSs) using geodetic measurements. This involved rigorous comparisons with the tidal constant measurements at 65 tide gauges and with the GPS-measured M₂ vertical ocean tide loading (OTL) displacements at 22 sites. The selected models showed significant disagreements close to the coasts of eastern China and the western Korean Peninsula, where the largest discrepancy for the M₂ constituent could exceed 30 cm. However, EOT20 and FES2014b provided relatively close results, differing by only about 15 cm in Hangzhou Bay. EOT20 compared more favourably than the others to the tidal constant measurements, with a root sum square (RSS) of 11.1 cm, and to the GPS-measured M₂ vertical OTL displacements, with a root mean square (RMS) of 0.49 mm. In addition, to differentiate between ocean tide models with subtle discrepancies when comparing them with the OTL measurements, consideration of the asthenospheric anelasticity effect was necessary. Full article

The efficiency of satellite altimetry in monitoring coastal areas and lakes is limited due to the contaminated waveform caused by non-water features included in the satellite footprint. Therefore, to mitigate these limitations, waveforms need to be retracked. In this research, the Generalized Logistic Function (GLF) has been introduced with Analytical (GLFA) and Numerical (GLFN) approaches to retrack the first sub-waveform. The results have been compared with those obtained from on-board retrackers existing in Level-2 altimetry data, the retracking of the full-waveform, the first sub-waveform, and the mean of the sub-waveforms using the threshold retracker. The Level-2 and Level-1B data of the Sentinel-3A (SRAL) mission for passes 141, 700, 244, and 311, respectively, passing over Vättern and Hjälmaren Lakes in Sweden, and 0–2 km distance from the coasts of the Bay of Alcudia and the Northeast Gulf of Bothnia from January 2019 to December 2022, were investigated. The results of the retracking approaches used in this study were evaluated against tide gauge data in terms of RMSE and its improvement percentage. The results demonstrate the superiority of the GLFA over the GLFN in coastal areas, while over lakes, the results are nearly equivalent. The improvement percentages of RMSE for the GLFA and GLFN compared to on-board retrackers, respectively, are as follows: for Vättern Lake, 53% and 58%; for Hjälmaren Lake, 40% and 33%; for the Bay of Alcudia, 81% and 46%; and for the Northeast Gulf of Bothnia, the GLFA shows a 36% improvement, while the GLFN yields results equivalent to on-board retrackers. The GLF has shown better performance compared to other approaches, except for Vättern Lake, which yields results almost equivalent to the first sub-waveform retracking approach. Additionally, the mean of the sub-waveform retracking approach by making use of the threshold algorithm has mostly demonstrated weaker performance compared to other methods. Full article

On 28 March 2005, a major M_w 8.6 earthquake occurred near Nias and Simeulueislands, in the vicinity of northwestern Sumatra (Indonesia). The earthquake generated a significant tsunami. Although it was not as destructive as the 2004 Sumatra tsunami, the 2005 event was of sufficient strength to be recorded by tide gauges throughout the entire Indian Ocean. We selected 12 records for analysis, most from open-ocean islands but also some from continental stations. The maximum wave heights were measured at Salalah (Oman) (87 cm), Colombo (Sri Lanka), Pointe La Rue (Seychelles) and Rodrigues Island (53–54 cm). The dominant wave periods, estimated from frequency–time (f-t) diagrams, were 60–66 min, 40–48 min, and 20 min, which we assume are associated with the 2005 tsunami source. From the same stations, we calculated the mean ratio of the 2004 to 2005 tsunami heights as 5.11 ± 0.60, with the maximum and minimum heights to the west and south of the source region as 9.0 and 2.49, respectively. We also used these data to estimate the mean energy index, $E_0$ = 65 cm², for the 2005 tsunami, which was 16 times smaller than for the 2004 event. The USGS seismic solution was used to construct a numerical model of the 2005 tsunami and to simulate the tsunami waveforms for all 12 tide gauge stations. The results of the numerical computations were in general agreement with the observations and enabled us to map the spatial wave field of the event. To estimate the influence of location and orientation of the source area on the propagating tsunami waves, we undertook a set of additional numerical experiments and found that this influence is substantial and that these factors explain some of the differences between the physical properties of the 2004 and 2005 events. Full article

To investigate the spatiotemporal characteristics of sea level changes in Hangzhou Bay over the past 40 years, we collected tide gauge data from six stations within the bay. Various mathematical and statistical methods, including linear regression, empirical orthogonal function (EOF) analysis, and wavelet analysis, were employed to reveal the long-term variation patterns and spatiotemporal characteristics of sea levels in Hangzhou Bay. The results show that the overall trend of sea levels in this area is characterized by a fluctuating rise, with the rate of rise at the top of the bay (Ganpu Station) reaching 6.74 mm/year, higher than the average rise rate of 3.5 mm/year along the coastal areas of Zhejiang Province. Since the 2010s, the rate of sea level change has accelerated. There is a significant seasonal variation in sea levels, with high values occurring in summer and autumn and low values in spring and winter. The sea level in Hangzhou Bay exhibits multi-timescale periodic changes, including astronomical tides, solar activity cycles, and seasonal cycles. It is projected that the sea level will transition from a rising cycle to a declining cycle after 2026. The rise in sea level in the open sea is the main factor contributing to the rising trend of sea levels in Hangzhou Bay. The contracted river for regulation and morphological evolution of the estuary have intensified tidal wave deformation, resulting in a significant impact on local sea level changes. Full article