Comparing the Currents Measured by CARTHE, CODE and SVP Drifters as a Function of Wind and Wave Conditions in the Southwestern Mediterranean Sea

Instruments drifting at the ocean surface are quasi-Lagrangian, that is, they do not follow exactly the near-surface ocean currents. The currents measured by three commonly-used drifters (CARTHE, CODE and SVP) are compared in a wide range of sea state conditions (winds up to 17 m/s and significant wave height up to 3 m). Nearly collocated and simultaneous drifter measurements in the southwestern Mediterranean reveal that the CARTHE and CODE drifters measure the currents in the first meter below the surface in approximately the same way. When compared to SVP drogued at 15 m nominal depth, the CODE and CARTHE currents are essentially downwind (and down-wave), with a typical speed of 0.5–1% of the wind speed. However, there is a large scatter in velocity differences between CODE/CARTHE and SVP for all wind and sea state conditions encountered, principally due to vertical and horizontal shears not related to the wind. For the CODE drifter with wind speed larger than 10 m/s and significant wave height larger than 1 m, about 30–40% of this difference can be explained by Stokes drift.

Wave Analysis for Offshore Aquaculture Projects: A Case Study for the Eastern Mediterranean Sea

The investigation of wave climate is of primary concern for the successful implementation of offshore aquaculture systems as waves can cause significant loads on them. Up until now, site selection and design (or selection) of offshore cage system structures on extended sea areas do not seem to follow any specific guidelines. This paper presents a novel methodology for the identification of favorable sites for offshore aquaculture development in an extended sea area based on two important technical factors: (i) the detailed characterization of the wave climate, and (ii) the water depth. Long-term statistics of the significant wave height, peak wave period, and wave steepness are estimated on an annual and monthly temporal scale, along with variability measures. Extreme value analysis is applied to estimate the design values and associated return periods of the significant wave height; structures should be designed based on this data, to avoid partial or total failure. The Eastern Mediterranean Sea is selected as a case study, and long-term time series of wave spectral parameters from the ERA5 dataset are utilized. Based on the obtained results, the most favorable areas for offshore aquaculture installations have been identified.

Estimation and Analysis of Wave Spectrum Parameter using HeMOSU-2 Observation Data

In this study, wave spectrum data were calculated using the water surface elevation data observed at 5Hz intervals from the HeMOSU-2 meteorological tower installed on the west coast of Korea, and wave parameters were estimated using wave spectrum data. For all significant wave height ranges, the peak enhancement parameter (γ opt ) of the JONSWAP spectrum and the scale parameter (α) and shape parameter (β) of the modify BM spectrum were estimated based on the observed spectrum, and the distribution of each parameter was confirmed. As a result of the analysis, the peak enhancement parameter (γ opt ) of the JONSWAP spectrum was calculated to be 1.27, which is very low compared to the previously proposed 3.3. And in the range of all significant wave heights, the distribution of the peak enhancement parameter (γ opt ) was shown as a combined distribution of probability mass function (PMF) and probability density function (PDF). In addition, the scale parameter (α) and shape parameter (β) of the modify BM spectrum were estimated to be [0.245, β1.278], which are lower than the existing [0.300, -1.098], and the result of the linear correlation analysis between the two parameters was β = =3.86α.

Ultimate Limit State Risk Assessment of Penta Pod Suction Bucket Support Structures for Offshore Wind Turbine due to Scour

The scour risk assessment was conducted for ultimate limit state of newly developed penta pod suction bucket support structures for a 5.5 MW offshore wind turbine. The hazard was found by using an empirical formula for scour depth suitable for considering marine environmental conditions such as significant wave height, significant wave period, and current velocity. The scour fragility curve was calculated by using allowable bearing capacity criteria of suction foundation. The scour risk was assessed by combining the scour hazard and the scour fragility.

CLTS-Net: A More Accurate and Universal Method for the Long-Term Prediction of Significant Wave Height

Significant wave height (SWH) prediction plays an important role in marine engineering areas such as fishery, exploration, power generation, and ocean transportation. For long-term forecasting of a specific location, classical numerical model wave height forecasting methods often require detailed climatic data and incur considerable calculation costs, which are often impractical in emergencies. In addition, how to capture and use the dynamic correlation between multiple variables is also a major research challenge for multivariate SWH prediction. To explore a new method for predicting SWH, this paper proposes a deep neural network model for multivariate time series SWH prediction—namely, CLTS-Net. In this study, the sea surface wind and wave height in the ERA5 dataset of the relevant points P1, P2, and P3 from 2011 to 2018 were used as input information to train the model and evaluate the model’s SWH prediction performance. The results show that the correlation coefficients (R) of CLTS-Net are 0.99 and 0.99, respectively, in the 24 h and 48 h SWH forecasts at point P1 along the coast. Compared with the current mainstream artificial intelligence-based SWH solutions, it is much higher than ANN (0.79, 0.70), RNN (0.82, 0.83), LSTM (0.93, 0.91), and Bi-LSTM (0.95, 0.94). Point P3 is located in the deep sea. In the 24 h and 48 h SWH forecasts, the R of CLTS-Net is 0.97 and 0.98, respectively, which are much higher than ANN (0.71, 0.72), RNN (0.85, 0.78), LSTM (0.85, 0.78), and Bi-LSTM (0.93, 0.93). Especially in the 72 h SWH forecast, when other methods have too large errors and have lost their practical application value, the R of CLTS-Net at P1, P2, and P3 can still reach 0.81, 0.71, and 0.98. The results also show that CLTS-Net can capture the short-term and long-term dependencies of data, so as to accurately predict long-term SWH, and has wide applicability in different sea areas.

Sea state from ocean video with singular spectrum analysis and extended Kalman filter

A method for estimating key parameters of ocean waves (the dominant frequency and the significant wave height) from uncalibrated monoscopic video is proposed, based on temporal variation of the wave field, specifically time series of pixel intensities. The methodology tracks the principal component of the movement of water in the video, which we propose is associated with the dominant frequency of the ocean. To accomplish this, the singular spectrum analysis algorithm and the extended Kalman filter are used. Then, the shape of an empirical spectrum is used in order to translate the dominant frequency output into a significant wave height estimation.