Multi-scale wavelet analysis of TOPEX/Poseidon altimeter significant wave height in eastern China seas

2006 ◽  
Vol 24 (1) ◽  
pp. 81-86 ◽  
Author(s):  
Guo Yanyou ◽  
Hou Yijun ◽  
Li Mingkui
Keyword(s):  
Wavelet Analysis ◽  
Wave Height ◽  
Significant Wave Height ◽  
Eastern China ◽  
China Seas ◽  
Significant Wave ◽  
Multi Scale ◽  
Eastern China Seas

Heat budget responses of the eastern China seas to global warming in a coupled atmosphere-ocean model

2019 ◽  
Vol 79 (2) ◽  
pp. 109-126
Author(s):  
D Tian ◽  
J Su ◽  
F Zhou ◽  
B Mayer ◽  
D Sein ◽  
...  
Keyword(s):  
Global Warming ◽  
Heat Budget ◽  
Eastern China ◽  
Ocean Model ◽  
China Seas ◽  
Eastern China Seas

On the Sensitivity of Passive Multistatic Radar Amplitude and Doppler Measurements to Significant Wave Height

2021 ◽  
pp. 1-5
Author(s):  
Jeffrey D. Ouellette ◽  
William T. Bounds ◽  
David J. Dowgiallo ◽  
Jakov V. Toporkov ◽  
Paul A. Hwang
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Significant Wave ◽  
Multistatic Radar

scholarly journals Estimation of Significant Wave Heights from ASCAT Scatterometer Data via Deep Learning Network

2021 ◽  
Vol 13 (2) ◽  
pp. 195
Author(s):  
He Wang ◽  
Jingsong Yang ◽  
Jianhua Zhu ◽  
Lin Ren ◽  
Yahao Liu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Wave Height ◽  
Significant Wave Height ◽  
Incidence Angle ◽  
Ocean Waves ◽  
Global Scale ◽  
Learning Technology ◽  
Sea State ◽  
Significant Wave ◽  
Wave Heights

Sea state estimation from wide-swath and frequent-revisit scatterometers, which are providing ocean winds in the routine, is an attractive challenge. In this study, state-of-the-art deep learning technology is successfully adopted to develop an algorithm for deriving significant wave height from Advanced Scatterometer (ASCAT) aboard MetOp-A. By collocating three years (2016–2018) of ASCAT measurements and WaveWatch III sea state hindcasts at a global scale, huge amount data points (>8 million) were employed to train the multi-hidden-layer deep learning model, which has been established to map the inputs of thirteen sea state related ASCAT observables into the wave heights. The ASCAT significant wave height estimates were validated against hindcast dataset independent on training, showing good consistency in terms of root mean square error of 0.5 m under moderate sea condition (1.0–5.0 m). Additionally, reasonable agreement is also found between ASCAT derived wave heights and buoy observations from National Data Buoy Center for the proposed algorithm. Results are further discussed with respect to sea state maturity, radar incidence angle along with the limitations of the model. Our work demonstrates the capability of scatterometers for monitoring sea state, thus would advance the use of scatterometers, which were originally designed for winds, in studies of ocean waves.

scholarly journals Physical Modelling of the Effect on the Wave Field of the WaveCat Wave Energy Converter

2021 ◽  
Vol 9 (3) ◽  
pp. 309
Author(s):  
James Allen ◽  
Gregorio Iglesias ◽  
Deborah Greaves ◽  
Jon Miles
Keyword(s):  
Wave Height ◽  
Wave Energy ◽  
Significant Wave Height ◽  
Wedge Angle ◽  
Wave Energy Converter ◽  
Wave Period ◽  
Surface Elevation ◽  
Energy Converter ◽  
Significant Wave ◽  
Model Scale

The WaveCat is a moored Wave Energy Converter design which uses wave overtopping discharge into a variable v-shaped hull, to generate electricity through low head turbines. Physical model tests of WaveCat WEC were carried out to determine the device reflection, transmission, absorption and capture coefficients based on selected wave conditions. The model scale was 1:30, with hulls of 3 m in length, 0.4 m in height and a freeboard of 0.2 m. Wave gauges monitored the surface elevation at discrete points around the experimental area, and level sensors and flowmeters recorded the amount of water captured and released by the model. Random waves of significant wave height between 0.03 m and 0.12 m and peak wave periods of 0.91 s to 2.37 s at model scale were tested. The wedge angle of the device was set to 60°. A reflection analysis was carried out using a revised three probe method and spectral analysis of the surface elevation to determine the incident, reflected and transmitted energy. The results show that the reflection coefficient is highest (0.79) at low significant wave height and low peak wave period, the transmission coefficient is highest (0.98) at low significant wave height and high peak wave period, and absorption coefficient is highest (0.78) when significant wave height is high and peak wave period is low. The model also shows the highest Capture Width Ratio (0.015) at wavelengths on the order of model length. The results have particular implications for wave energy conversion prediction potential using this design of device.

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