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Probabilistic models for long-term estimations and deep learning models for short-term predictions have been evaluated and analyzed for ocean wave parameters. Estimation of design and operational wave parameters for long-term return periods is essential for various coastal and ocean engineering applications. Three probability distributions, namely generalized extreme value distribution (EV), generalized Pareto distribution (PD), and Weibull distribution (WD), have been considered in this work. The design wave parameter considered is the maximal wave height for a specified return period, and the operational wave parameters are the mean maximal wave height and the highest occurring maximal wave height. For precise location-based estimation, wave heights are considered from a nested wave model, which has been configured to have a 10 km spatial resolution. As per availability, buoy-observed data are utilized for validation purposes at the Agatti, Digha, Gopalpur, and Ratnagiri stations along the Indian coasts. At the stations mentioned above, the long short-term memory (LSTM)-based deep learning model is applied to provide short-term predictions with higher accuracy. The probabilistic approach for long-term estimation and the deep learning model for short-term prediction can be used in combination to forecast wave statistics along the coasts, reducing hazards.

Characteristics of the wind waves measured in the coastal waters of the northeastern Bay of Bengal are examined for 4 years. A comparison of the energy wave period ( T e ) with different wave periods shows that the average wave period ( T m–1,1 ), significant wave period ( T 1/3 ), and integral period ( T i ) are closer to T e . A maximum wave height of 5.5 m is observed, and the most typical values for the wave period range between 4 and 6.5 s. The steepness of the highest wave is 0.058. In the coastal waters, the values of the peak wave period ( T p ) indicate a swell dominance in the monsoon. Short-period waves ( T p  < 6 s) are relatively higher in 2015 and the long-period waves ( T p  > 8 s) in 2013 and the changes are due to the variations in monsoon. A large number of long-period waves is observed during the northeast monsoon. Thirty-seven freak wave events occurred, and the presence of freak waves is higher in the monsoon. Interannual variations in the mean of T avg are up to 5% and that of the 90-percentile of the average wavelength ( λ T avg ) is up to 10%. The annual mean wave power is 5 kW/m and annually during 25% of the time, the wave power is more than 7 kW/m.

The dams and banks of small water reservoirs face significant erosion from wind-generated oscillatory waves. Proper design of structure height is crucial to protect such banks against erosion, considering the maximum characteristics of wind waves. Long-term measurements at the Hulín reservoir revealed that the wave spectrum aligns best with the Bretschneider type. This spectrum serves as a basis for simulating oscillatory waves and their impact on shore protection structure design. Empirical models were evaluated using wind and wave data from Hulín reservoir in the Czech Republic. The measured wind speeds attained a maximum of 8 m/s, and wave heights reached up to 15 cm. The Bretschneider (SMB) empirical formula provided the most accurate estimation of wave height ( ), with an average underestimate of RMSE = 0.038 m. On the other hand, Wilson revisited (WIL rev.) performed less effectively, with an average RMSE = 0.304 m. For wave period ( ) estimation, Bretschneider (SMB) yielded the best results, with an average RMSE = 0.062 s. Conversely, Wilson revisited (WIL rev.) showed poorer performance, with an average underestimate of RMSE = 2.196 s. The discrepancy between the empirical formulas and measured values, particularly in underestimating , can be attributed to inaccurate determination of fetch length and wind speed.

Background P‐wave parameters, readily obtainable from standard 12‐lead ECGs, have been associated with atrial fibrillation (AF), ischemic stroke, and other cardiovascular conditions. Left atrial cardiomyopathy (AtCM), characterized by atrial fibrosis and functional impairment, is considered a central substrate in the development of AF and embolic stroke of undetermined source. This study examines the relationship between P‐wave parameters and left atrial hemodynamics and evaluates their potential diagnostic utility in identifying AtCM. Methods We conducted a monocentric, prospective study in hospitalized patients. Inclusion criteria were sinus rhythm and age ≥ 18 years. P‐wave parameters were assessed in conjunction with echocardiographic measures of left atrial function. Statistical analyses compared patients with and without pathological P‐wave parameters. Results A total of 416 patients were included. Pathological P‐wave parameters were highly prevalent, with 55% of patients exhibiting ≥ 3 abnormalities. Advanced interatrial block (IAB) showed a robust association with impaired left atrial hemodynamics, whereas other parameters, such as PTFV1, demonstrated only weak correlations. Patients with advanced IAB exhibited significant alterations in left atrial size, function, and NT‐proBNP levels. Conclusions Advanced IAB emerged as the most reliable P‐wave parameter for detecting left atrial dysfunction in AtCM, whereas other P‐wave indices, including PTFV1, were less informative. These findings highlight the diagnostic value of advanced IAB in identifying AtCM, particularly in patients with embolic stroke of undetermined source, and emphasize the need for more refined diagnostic criteria in future investigations. In the present study, the validity of seven established P‐wave parameters in relation to left atrial hemodynamics was investigated. Our study suggests that advanced IAB is the strongest indicator of altered left atrial hemodynamics and, thus, AtCM.

This study examines the variation and trends in wave parameters across the Arctic, including the marginal ice zone (MIZ), by comparing historical data (1980–2009) with projections for a future climate scenario (2070–2099) as outlined by the IPCC. Utilizing the WAVEWATCH III (WW3) numerical wave prediction model, we simulate the wave climate for these periods, incorporating advanced parameterizations to account for wave-ice interactions within the MIZ. Our analysis focuses on the extreme values of significant wave heights (Hs), mean wave periods (T0), and dominant mean wave direction (MWD), calculated for both winter and summer seasons. To assess changes in wave climate under future climate scenarios, we first use a similarity matrix, applying the kappa variable and cell-by-cell numerical comparison methods to assess model congruence across different conditions. We also follow a standard approach, by assessing the extreme wave conditions for 20 and 100-year return periods using standard stochastic models, including Gumbel, exponential, and Weibull distributions.

During its service life, a deep-sea floating structure is likely to encounter extreme marine disasters. The combined action of wind and wave loads poses a threat to its structural safety. In this study, elliptical copula, Archimedean copula, and vine copula models are employed to depict the intricate dependence structure between wind and waves in a specific sea area of the Shandong Peninsula. Moreover, hourly significant wave height, spectral peak period, and 10 m average wind speed hindcast data from 2004 to 2023 are utilized to explore the joint distribution of multidimensional parameters and environmental design values. The results indicate the following: (1) There exists a significant correlation between wind speed and wave parameters. Among them, the C-vine copula model represents the optimal trivariate joint distribution, followed by the Gaussian copula, while the Frank copula exhibits the poorest fit. (2) Compared with the high-dimensional symmetric copula models, the vine copula model has distinct advantages in describing the dependence structure among several variables. The wave height and period demonstrate upper tail dependence characteristics and follow the Gumbel copula distribution. The optimal joint distribution of wave height and wind speed is the t copula distribution. (3) The identification of extreme environmental parameters based on the joint probability distribution derived from environmental contour lines is more in line with the actual sea conditions. Compared with the design values of independent variables with target return periods, it can significantly reduce engineering costs. In conclusion, the vine copula model can accurately identify the complex dependency characteristics among marine variables, offering scientific support for the reliability-based design of floating structures.

Background The aim of this study was to examine the prevalence of abnormal P‐wave parameters in patients with thrombus and/or spontaneous echo contrast (SEC) in the left atrial appendage (LAA), and to identify P‐wave parameters particularly associated with thrombus and SEC formation. Hypothesis We presume a significant relationship of P‐wave parameters with thrombi and SEC. Methods All patients in whom a thrombus or SEC was detected in the LAA on transoesophageal echocardiography were included in this study. Patients at risk (CHA2DS2‐VASc Score ≥3) and routine transoesophageal echocardiography to exclude thrombi served as the control group. A detailed ECG analysis was performed. Results Of a total of 4062 transoesophageal echocardiographies, thrombi and SEC were detected in 302 patients (7.4%). Of these patients, 27 (8.9%) presented with sinus rhythm. The control group included 79 patients. There was no difference in mean CHA2DS2‐VASc score in the two groups (p = .182). A high prevalence of abnormal P‐wave parameters was detected in patients with thrombus/SEC. Indicators for the presence of thrombi or SEC in the LAA were P‐wave duration >118 ms (Odds ratio (OR) 3.418, Confidence interval (CI) 1.522–7.674, p < .001), P‐wave dispersion >40 ms (OR 2.521, CI 1.390–4.571, p < .001) and advanced interatrial block (OR 1.431, CI 1.033–1.984, p = .005). Conclusion Our study revealed that several P‐wave parameters are associated with thrombi and SEC in the LAA. The results may help identify patients who are at particularly high risk for thromboembolic events (e.g., in patients with embolic stroke of undetermined source). Several P‐wave parameters are associated with atrial fibrillation and with ischemic stroke. However, it is uncertain whether P‐wave parameters are associated with thrombus or spontaneous echo contrast in the left atrial appendage. Our study demonstrated a significant association of P‐wave duration, P‐wave dispersion, and advanced interatrial block with thrombus or spontaneous echo contrast in the left atrial appendage. IAB, interatrial block; PTFV1, P‐wave terminal force in V1.

The storm activity in the Sea of Azov from 1982 to 2020 is analyzed. The data on the wind wave parameters have been obtained using the WAVEWATCH III model and NCEP/CFSR/CFSv2 reanalysis. The ESA SST CCI and C3S analysis was chosen as a source of data on sea ice concentration. The calculations were performed on an unstructured computational grid with a spatial resolution of 3–5 km for the open part of the Sea of Azov and 200–400 m along the coast. Analysis of the frequency of storm waves with a height of 2–3 m has been carried out. An average significant wave height equal to 0.6–0.65 m is observed in the center of the sea. The maximum significant wave height for the entire simulation period is 3.42 m. A significant negative trend has been found for storms with the wave height above 2 m. A positive significant trend has been revealed for the average annual wave height in the western part of the sea.

This study is dedicated to the assessment of the current influence on the wind wave height in the Black Sea based on numerical modeling. The research was carried out based on the SWAN wave model driven by NCEP/CFSv2 wind reanalysis. Current data from the Remote Sensing Department's archive of the Marine Hydrophysical Institute of RAS were used. It is shown that the average wave height mainly decreases when sea currents are considered. These changes are insignificant relative to the average values of wave heights. The greatest negative changes are typical for the western, central, and northeast parts of the Black Sea. Here, currents reduce the average annual wave heights down to – 7.5 cm. A slight increase in the average wave height is typical for the southern, southeast parts, and the northwest shelf of the sea. Currents have the greatest influence on the wave parameters during winter and the least during late spring and summer. The validation shows that currents increase the correlation coefficient when wave heights are > 2 m, but this increase is insignificant, over 0.05. In general, the quality of wave simulation in the Black Sea does not improve by supplementing currents in the model used in this study.

In this study, laboratory experiments were conducted to investigate the influence of changes in storm wave height and water level on beach response in a medium-scale wave flume. A schematic storm was simulated (rising, apex, and waning phases). A non-intrusive photogrammetric method was used to collect high-resolution and synchronous data regarding the free surface water elevation and bed level, from which shoreline location, sandbar position, cross-shore sediment transport rates, and nonlinear wave parameters were derived. The cross-shore sediment transport was in agreement with previous laboratory measurements, including the monotonous exchange from foreshore erosion to shoaling zone accretion in most stages of the storm simulation. The surf zone was the main region supplying sediment for beach morphology modification and sandbar generation. The degree of storm erosion was not completely determined by the largest wave height and water level or the cumulative wave power of the apex phase. The largest gradients of the wave parameter sequence change occurred in the rising phase, and this was the main factor generating efficient beachface erosion. It induced an increase in sandbar size, accompanied by the cross-shore motion of maximum velocity amplitude, more violent disturbances of wave nonlinearity, and increased surf zone erosion, with these factors increasing beach instability and leading to more severe storm erosion. The large wave height and water level resulted in shoreline retreat, with a more significant swash zone erosion under a higher runup. The offshore sediment transport turned toward the onshore direction as the original large sandbar deteriorated under the decreasing wave parameter sequence in the waning phase.