scholarly journals Predicting Ocean Waves along the U.S. East Coast During Energetic Winter Storms: sensitivity to Whitecapping parameterizations

2018 ◽  
Author(s):  
Mohammad Nabi Allahdadi ◽  
Ruoying He ◽  
Vincent S. Neary
Keyword(s):  
East Coast ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Spectral Energy ◽  
Frequency Spectra ◽  
Winter Storms ◽  
Wave Parameters ◽  
Wind Input ◽  
Simulation Results ◽  
The U.S

Abstract. The performance of two methods for quantifying whitecapping dissipation incorporated in the SWAN wave model is evaluated for waves generated along and off the U.S. East Coast under energetic winter storms with a predominantly westerly wind. Parameterizing the whitecapping effect can be done using the Komen-type schemes, which are based on mean spectral parameters, or the saturation-based (SB) approach of van der Westhuysen (2007), which is based on local wave parameters and the saturation level concept of the wave spectrum (we use Komen and Westhuysen to denote these two approaches). Observations of wave parameters and frequency spectra at four NDBC buoys are used to evaluate simulation results. Model-data comparisons show that when using the default parameters in SWAN, both Komen and Westhuysen methods underestimate wave height. Simulations of mean wave period using the Komen method agree with observations, but those using the Westhuysen method are substantially lower. Examination of source terms shows that the Westhuysen method underestimates the total energy transferred into the wave action equations, especially in the lower frequency bands that contain higher spectral energy. Several causes for this underestimation are identified. The primary reason is the difference between the wave growth conditions along the East Coast during winter storms and the conditions used for the original whitecapping formula calibration. In addition, some deficiencies in simulation results are caused along the coast by the slanting fetch effect that adds low-frequency components to the 2-D wave spectra. These components cannot be simulated partly or entirely by available wind input formulations. Further, the effect of boundary layer instability that is not considered in the Komen and Westhuysen whitecapping wind input formulas may cause additional underestimation.

scholarly journals Predicting ocean waves along the US east coast during energetic winter storms: sensitivity to whitecapping parameterizations

Ocean Science ◽  
2019 ◽  
Vol 15 (3) ◽  
pp. 691-715 ◽  
Author(s):  
Mohammad Nabi Allahdadi ◽  
Ruoying He ◽  
Vincent S. Neary
Keyword(s):  
East Coast ◽  
Ocean Waves ◽  
Source Terms ◽  
Frequency Spectra ◽  
Winter Storms ◽  
Wave Parameters ◽  
The Us ◽  
Wind Input ◽  
Simulation Results ◽  
Us East Coast

Abstract. The performance of two methods for quantifying whitecapping dissipation incorporated in the Simulating Waves Nearshore (SWAN) wave model is evaluated for waves generated along and off the US east coast under energetic winter storms with a predominantly westerly wind. Parameterizing the whitecapping effect can be done using the Komen-type schemes, which are based on mean spectral parameters, or the saturation-based (SB) approach of van der Westhuysen (2007), which is based on local wave parameters and the saturation level concept of the wave spectrum (we use “Komen” and “Westhuysen” to denote these two approaches). Observations of wave parameters and frequency spectra at four National Data Buoy Center (NDBC) buoys are used to evaluate simulation results. Model–data comparisons show that when using the default parameters in SWAN, both Komen and Westhuysen methods underestimate wave height. Simulations of mean wave period using the Komen method agree with observations, but those using the Westhuysen method are substantially lower. Examination of source terms shows that the Westhuysen method underestimates the total energy transferred into the wave action equations, especially in the lower frequency bands that contain higher spectral energy. Several causes for this underestimation are identified. The primary reason is the difference between the wave growth conditions along the east coast during winter storms and the conditions used for the original whitecapping formula calibration. In addition, some deficiencies in simulation results are caused along the coast by the “slanting fetch” effect that adds low-frequency components to the 2-D wave spectra. These components cannot be simulated partly or entirely by available source terms (wind input, whitecapping, and quadruplet) in models and their interaction. Further, the effect of boundary layer instability that is not considered in the Komen and Westhuysen whitecapping wind input formulas may cause additional underestimation.

scholarly journals DIRECTIONAL SPECTRA OF OCEAN SURFACE WAVES

1976 ◽  
Vol 1 (15) ◽  
pp. 18 ◽  
Author(s):  
H. Mitsuyasu ◽  
S. Mizuno
Keyword(s):  
Angular Distribution ◽  
Frequency Spectrum ◽  
Wind Waves ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Peak Frequency ◽  
Spectral Peak ◽  
Energy Concentration ◽  
Spectral Energy ◽  
Directional Spectrum

From 1971-74 seven cruises were made to measure the directional spectrum of ocean waves by using a cloverleaf buoy. Typical sets of wave data measured both in open seas and in a bay under relatively simple conditions have been analyzed to clarify the fundamental properties of the directional spectrum of ocean waves in deep water. It is shown that the directional wave spectrum can be approximated by the product of the frequency spectrum and a unimodal angular distribution with mean direction approximately equal to that of the wind. The normalized forms of the frequency spectrum show various forms lying between the Pierson-Moskowitz spectrum and the spectrum of laboratory wind wave which has a very sharp energy concentration near the spectral peak frequency. The form of the JONSWAP spectrum is very close to that of laboratory wind waves. The concentration of the spectral energy near the spectral peak frequency seems to decrease with increasing the dimensionless fetch and the spectral form finally approaches to the Pierson-Moskowitz spectrum which can be considered as the spectrum with the least concentration of the normalized spectral energy. However, the definite relation between the shape of the normalized spectrum and the dimensionless fetch has not been obtained. Concerning the angular distribution, it is shown that the shape of angular distribution of the single-peaked wave spectrum in a generating area can be approximated by the function G(6,f) = G'(s) | cos (6-6)/2 | ** proposed originally by Longuet=Higgins et al. (1963). Here G'(s) is a normalizing function, 6 is the mean direction of the spectral component, and s is a parameter which controls the concentration of the angular distribution function.

scholarly journals Correlation Analysis between Wave Parameters using Wave Data Observed in HeMOSU-1&2

2021 ◽  
Vol 33 (4) ◽  
pp. 139-147
Author(s):  
Uk-Jae Lee ◽  
Dong-Hui Ko ◽  
Hong-Yeon Cho ◽  
Nam-Sun Oh
Keyword(s):  
Correlation Analysis ◽  
Wave Height ◽  
Wave Train ◽  
Wave Spectrum ◽  
Correlation Coefficients ◽  
Spectral Energy ◽  
Analysis Method ◽  
Peak Period ◽  
Wave Parameters ◽  
Elevation Data

In this study, waves were defined using the water surface elevation data observed from the HeMOSU-1 and 2 marine meteorological observation towers installed on the west coast of Korea, and correlation analysis was performed between wave parameters. The wave height and wave period were determined using the wave-train analysis method and the wave spectrum analysis method, and the relationship between the wave parameters was calculated and compared with the previous study. In the relation between representative wave heights, most of the correlation coefficients between waves showed a difference of less than 0.1% in error rate compared to the previous study, and the maximum wave height showed a difference of up to 29%. In addition, as a result of the correlation analysis between the wave periods, the peak period was estimated to be abnormally large at rates of 2.5% and 1.3% in HeMOSU-1&2, respectively, due to the effect of the bimodal spectrum that occurs when the spectral energy density is small.

The Numerical Simulation Research of Three Dimensional Irregular Wave Based on Wave Spectrum

2013 ◽  
Vol 397-400 ◽  
pp. 643-647
Author(s):  
Ying Fei Zan ◽  
Zhi Hui Dong ◽  
Lei Song ◽  
Wei Sun
Keyword(s):  
Numerical Simulation ◽  
Spectral Energy Distribution ◽  
Wave Spectrum ◽  
Three Dimensional ◽  
Spectral Energy ◽  
Frequency Division ◽  
Simulation Research ◽  
Irregular Wave ◽  
Simulation Results ◽  
Temporal And Spatial

Starting from observation statistics that oceanography has existed now and based on wave spectrum and the direction spectrum function, the three-dimensional irregular wave mathematical model is built with the method of halving frequency, and according to the wave spectral energy distribution, the number of frequency division and direction segmentation is studied. Last numerical simulation of three dimensional irregular wave is studied by using Matlab, the temporal and spatial wave simulation waveform is obtained. The simulation results show that this method can simulate three dimensional irregular wave accurately and fast.

scholarly journals A Meteotsunami Climatology along the U.S. East Coast

2019 ◽  
Vol 100 (7) ◽  
pp. 1329-1345 ◽  
Author(s):  
Gregory Dusek ◽  
Christopher DiVeglio ◽  
Louis Licate ◽  
Lorraine Heilman ◽  
Katie Kirk ◽  
...  
Keyword(s):  
South Carolina ◽  
Rhode Island ◽  
East Coast ◽  
Ocean Waves ◽  
Atlantic City ◽  
Tide Gauges ◽  
Myrtle Beach ◽  
Wave Heights ◽  
Work Supports ◽  
The U.S

AbstractMeteotsunamis are atmospherically forced ocean waves with characteristics similar to seismic tsunamis. Several recent hazardous meteotsunamis resulted in damage and injuries along U.S. coastlines, such that the National Oceanic and Atmospheric Administration (NOAA) is investigating ways to detect and forecast meteotsunamis to provide advance warning. Better understanding meteotsunami occurrence along U.S. coastlines is a necessary step to pursue these objectives. Here a meteotsunami climatology of the U.S. East Coast is presented. The climatology relies on a wavelet analysis of 6-min water-level observations from 125 NOAA tide gauges from 1996 to 2017. A total of 548 meteotsunamis, or about per year, were identified and assessed using this approach along the U.S. East Coast. There were a total of 30 instances when gauges observed waves of more than 0.6 m, which is assumed to be a potentially impactful event, and several cases with wave heights more than 1 m. Tide gauges along the open coast observed the most frequent events, including more than five events per year at Atlantic City, New Jersey; Duck, North Carolina; and Myrtle Beach, South Carolina. The largest waves were observed by gauges in estuaries that amplified the meteotsunami signal, such as those in Providence, Rhode Island, and Port Canaveral, Florida. Seasonal trends indicate that meteotsunamis occur most frequently in the winter and summer months, especially July. This work supports future meteotsunami detection and warning capabilities at NOAA, including the development of an impact catalog to aid National Weather Service forecasters.

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