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wave hindcasting
Latest Past Events
MS Plan A Defense: The Relationship Between Hydrodynamic and Morphologic Changes at Sunset Beach
Zoom Meeting ID: 970 3827 6831Merritt Shepherd Master’s Student Department of Ocean and Resources Engineering University of Hawai’i at Mānoa **This defense will be held over Zoom** Meeting ID: 970 3827 6831 Passcode: MerrittMS https://hawaii.zoom.us/j/97038276831 In recent years, Sunset Beach on O'ahu’s North Shore has experienced multiple erosion events. Consequently, the US Army Crops of Engineers has collected datasets describing Sunset Beach through aerial photographic surveys and beach cameras to resolve the coastline variability from 2020-2021. The aerial and coastline imagery were processed to determine beach area and volume time series. The constructed beach time series indicates large seasonal variations and year-to-year variations, driven by
Integrated modeling to support marine energy resource characterization and coastal resilience
Watanabe 112 2505 Correa Rd, HonoluluDr. Zhaoqing Yang Chief Scientist Coastal Sciences Division Northwest National Laboratory Location Information **This seminar will be held both in person (Watanabe Hall 112) and over Zoom** Meeting ID: 961 6222 2366 Passcode: OREseminar https://hawaii.zoom.us/j/96162222366 This seminar will cover two major research areas carrying out in the Ocean Dynamics Modeling Group in PNNL 1) Marine energy resource characterization and 2) Coastal storm surge and resilience. Marine renewable energy can play an important role in mitigating climate change and enhancing national energy security. PNNL is leading the modeling effort in marine energy resource characterization including wave, tidal stream,
MS Plan B Defense: Extreme wave height estimation from a global wave hindcast ensemble
Zoom Meeting ID______ 947 5656 0724 Passcode: OREAndi Erickson Graduate Student Department of Ocean and Resources Engineering University of Hawai’i at Mānoa Across the oceans, strong storms generate powerful waves that impact human activities such as commerce and design of coastal and offshore structures. To mitigate damages to these activities and to properly design infrastructures, it is imperative to understand the extreme wave climate. Previous works typically use a single dataset to describe the extreme wave climate. Here we analyze a comprehensive ensemble of 11 wave hindcasts most covering 30 years (1979-2016) to estimate extreme wave conditions at a commonly used return period of 100 years. To