Assessment of Offshore Wave Energy Resources in Taiwan Using Long-Term Dynamically Downscaled Winds from a Third-Generation Reanalysis Product

Abstract

In this study, long-term wind fields during 1991–2010 from the Climate Forecast System Reanalysis (CFSR) were dynamically downscaled over Taiwan and its offshore islands at a 5 km horizontal resolution using the Weather Research and Forecasting (WRF) model. Simulations of the 10 m (above sea level) dynamically downscaled winds served as the atmospheric forcing for driving a fully coupled wave-circulation model. The sea states of the waters surrounding Taiwan during 1991–2010 were hindcasted to evaluate the offshore wave energy resources and optimal wave energy hotspots. This study reveals that the southeastern offshore waters of Taiwan and the Central Taiwan Strait exhibited the highest mean wave power density (WPD), exceeding 20 kW/m. The annual mean WPD, incidence of the hourly WPD greater than or equal to 4 kW/m, monthly variability index and coefficient of variation of the WPD indicated that the sea areas located between Green Island and Orchid Island (OH_1), southeast of Orchid Island (OH_2), south of the Hengchun Peninsula (OH_3), and north of the Penghu Islands (OH_4) were the optimal hotspots for deploying wave energy converters. The most energetic months were October for OH_1 and OH_2 and November for OH_3 and OH_4, while the wave power was weak from March to June for OH_1, OH_2 and OH_3 and in May for OH_4. The wave direction is prevailingly east-northeast for OH_1, OH_2 and OH_3 and nearly northeast for OH_4. These phenomena reveal that wave power in the waters offshore Taiwan is induced primarily by the northeast (winter) monsoon. The exploitable annual WPD was estimated to be 158.06, 182.89, 196.39 and 101.33 MWh/m for OH_1, OH_2, OH_3 and OH_4, respectively.

Numerical Analysis of the Effect of Binary Typhoons on Ocean Surface Waves in Waters Surrounding Taiwan

“…The wind speeds and their distributions near the center of the typhoon can accurately be reproduced through parametric cyclone wind models; however, their performances are inferior in regions far from the center of the typhoon. Conversely, the typhoon winds derived from an atmospheric reanalysis are superior in areas outside of the typhoon's center but are generally worse for the maximum typhoon wind speed (Pan et al, 2016;Chen et al, 2019;Hsiao et al, 2019Hsiao et al, , 2020aHsiao et al, ,b, 2021a. To construct a reliable scale for the entire wind field of a typhoon, a direct modification technique proposed by Pan et al (2016) was therefore applied in the present study to take advantage of the combination of a parametric cyclone wind model and reanalysis products:…”

“…The improvement of the coupled model, SCHISM-WWM-III, was accomplished by employing the different time steps in two models, i.e., 120 s for SCHISM-2D and 600 s for WWM-III. The SCHISM-WWM-III system is a two-way, tightly coupled modeling system, i.e., the SCHISM-2D delivers the wind velocities, depth-averaged currents, and water surface elevations to the WWM-III, and then the wave radiation stresses computed by the WWWM-III are used in the SCHISM-2D every 5 hydrodynamic time intervals, and has been used to predict the offshore storm waves and coastal storm tides induced by typhoons and to hindcast the long-term wave parameters in the waters surrounding Taiwan (Chen et al, 2017b(Chen et al, , 2019Shih et al, 2018;Su et al, 2018;Hsiao et al, 2019Hsiao et al, , 2020aHsiao et al, ,b, 2021a.…”

“…To eliminate the effects of the boundary conditions on model simulations, the computational domain for storm surge, storm tide and storm wave modeling must be large enough to accommodate an entire typhoon, including its peripheral circulation (Orton et al, 2012;Zheng et al, 2013;Hsiao et al, 2021a). Hence, the present study created a large computational domain that covers the area from longitudes of 105 • E to 140 • E and latitudes of 15 • N to 31 • N (as shown in Figure 1) and contains 276,639 vertices and 540,510 triangular elements (as shown in Figure 2A).…”

“…GEBCO_2021 provides global coverage of elevation data in meters at a 15 arc-second spatial resolution. Open boundary conditions for SCHISM-WWM-II were not always required, as the three selected super typhoons are completely covered by the large computational domain (Liu et al, 2012;Hsiao et al, 2020aHsiao et al, ,b, 2021a. The tidal elevation and horizontal velocity at the open boundaries of SCHISM-WWM-III were driven by eight main tidal constituents (M 2 , S 2 , N 2 , K 2 , K 1 , O 1 , P 1 , and Q 1 ) extracted from a regional inverse tidal model (China Seas and Indonesia; Zu et al, 2008), and the effects of sea level pressure on the boundary tidal elevations were taken into consideration.…”

Advances in sea state modeling and climate change impacts

“…The wind speeds and their distributions near the center of the typhoon can accurately be reproduced through parametric cyclone wind models; however, their performances are inferior in regions far from the center of the typhoon. Conversely, the typhoon winds derived from an atmospheric reanalysis are superior in areas outside of the typhoon's center but are generally worse for the maximum typhoon wind speed (Pan et al, 2016;Chen et al, 2019;Hsiao et al, , 2020aHsiao et al, ,b, 2021a. To construct a reliable scale for the entire wind field of a typhoon, a direct modification technique proposed by Pan et al (2016) was therefore applied in the present study to take advantage of the combination of a parametric cyclone wind model and reanalysis products:…”