Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.

A combination of multiple data sources has been used to study the characteristics of internal solitary waves (ISWs) in the Gulf of Oman (GoO). Water column stratification in the Gulf has been examined using field observations and World Ocean Atlas 2018 datasets. The spatiotemporal distribution of ISWs has been obtained from satellite images obtained by means of Synthetic Aperture Radar (SAR) and optical sensors taken from 2018 to 2020. The mechanisms of ISW generation in the GoO have been studied using the data revealed from different available sources. The results show that there are annually two major typical stratifications in the GoO throughout the year, strong stratification in May through September and weak stratification during other months. Dispersion relations corresponding to these types of stratification have been obtained with acceptable accuracy for both deep and shallow regions. The spatiotemporal distribution of ISWs demonstrates that the western and southern regions of the GoO are the hotspots for generation of ISWs in this basin. Several mechanisms of ISW generation in the GoO are discussed including tide, eddies, lee waves, and atmospheric perturbation; the latter one is, apparently, responsible for the appearance of large-amplitude ISWs.

Allahdadi, M.N. and Li, C., 2018. Numerical simulation of Louisiana shelf circulation under Hurricane Katrina. The response of currents on the Louisiana shelf to Hurricane Katrina was studied using the 3-D Finite Volume Community Ocean Model (FVCOM). The study area encompassed the Louisiana shelf covering both sides of the Mississippi River's Birdsfoot Delta. The model was forced by a wind field prepared by combining the Hurricane Research Division Wind Analysis System data for the hurricane with background winds outside of the hurricane's influence from National Centers for Environmental Prediction (NCEP)/North American Regional Reanalysis (NARR). Current and water-level data recorded at Wave-Current-Surge Information System (WAVCIS) stations over the inner shelf provided a unique opportunity to examine shelf hydrodynamics in response to Katrina. Model performance was evaluated by examining water-column stratification under different scenarios and using a range of parameters of the Mellor-Yamada...

The category 5-equivalent tropical Cyclone Gonu (2007) was the strongest cyclone to enter the northern Arabian Sea and Gulf of Oman. The impact of this cyclone on the sea surface temperature (SST) cooling and deepening of the mixed layer was investigated herein using an optimally interpolated (OI) cloud-free sea surface temperature (SST) dataset, climatological profiles of water temperature, and data from Argo profilers. SST data showed a maximum cooling of 1.7–6.5 °C during 1–7 June 2007 over the study area, which is similar to that of slow- to medium-moving cyclones in previous studies. The oceanic heat budget equation with the assumptions of the dominant turbulent mixing effect was used to establish relationships between SST and mixed layer depth (MLD) for regions that were directly affected by cyclone-induced turbulent mixing. The relationships were applied to the SST maps from satellite to obtain maps of MLD for 1–7 June, when Gonu was over the study area. Comparing with the measured MLD from Argo data showed that this approach estimated the MLDs with an average error of 15%, which is an acceptable amount considering the convenience of this approach in estimating MLD and the simplifications applied in the heat budget equation. Some inconsistencies in calculating MLD were attributed to use of climatological temperature profiles that may not have appropriately represented the pre-cyclone conditions due to pre-existing cold/warm core eddies. Estimation of the diapycnal diffusion that quantified the turbulent mixing across the water column showed consistent temporal and spatial variations with the calculated MLDs.