![]() ![]() ![]() We have assembled a spectral wave model system comprising WAVEWATCH III and SWAN on a hierarchy of global, regional, and nearshore computational grids. The location on the east shore of Oahu is open to year-round wind waves and seasonal north swells as well as severe seas from subtropical systems and hurricanes. The US Navy Wave Energy Test Site (WETS) is currently operating three grid-connected berths off Marine Corps Base Hawaii in support of technological development through scaled-model testing and pre-commercial prototyping. The nested-grid modeling framework employed in this study provides a powerful and efficient modeling approach for accurately simulating wave climate at regional and long-term temporal scales with sufficiently fine resolutions in the nearshore region. In addition, spectral results were saved at National Data Buoy Center buoy stations and selected virtual buoy locations at hourly intervals. The hindcast results, including resource and bulk parameters, were archived at every model grid point for the entire model domain at three-hour intervals. The hindcast also considers the effect of sea ice on wave growth, which affects the southern Bering Sea. The model hindcast was able to reproduce the seasonal variation of the sea state with large waves that occur in the winter and early spring months when wind forcing is strong and the calm sea state during the summer when wind forcing is weak. Overall, model results, both resource and more » bulk parameters, match observations well. Error statistics of model skills were calculated at all buoy stations. Wave resource and wave bulk parameters were simulated for a 32-year period from 1979 to 2010 and were subsequently validated with wave buoy data in the model domain. This report summarizes modeling efforts for the simulation of the wave climate along southern Alaska, which used an unstructured, nested-grid modeling approach that incorporates a global-regional nested grid using WAVEWATCH III ® and the high-resolution SWAN (Simulating Waves Nearshore) model. Regional long-term wave hindcast with state-of-art third-generation models is essential for characterization of regional wave resources. Water Power Technologies Office USDOE National Nuclear Security Administration (NNSA) OSTI Identifier: 1638491 Report Number(s): PNNL-SA-152704 Journal ID: ISSN 2077-1312 Grant/Contract Number: AC05-76RL01830 NA0003525 Resource Type: Journal Article: Accepted Manuscript Journal Name: Journal of Marine Science and Engineering Additional Journal Information: Journal Volume: 8 Journal Issue: 4 Journal ID: ISSN 2077-1312 Publisher: MDPI Country of Publication: United States Language: English Subject: 16 TIDAL AND WAVE POWER Extreme significant wave height wave hindcast wave energy resource assessment WEC = , Publication Date: Research Org.: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States) Sponsoring Org.: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. North Carolina State Univ., Raleigh, NC (United States).Pennsylvania State Univ., State College, PA (United States). ![]() (SNL-NM), Albuquerque, NM (United States). A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored. However, simple linear corrections can effectively compensate for this bias. ![]() This underbias is dependent on model spatial resolution. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from more » buoy measurements. Large discrepancies are common and increase with return period. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. 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. 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. 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. 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. ![]()
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