scholarly journals A Comparison of Algorithms for Extracting Significant Wave Height from HF Radar Ocean Backscatter Spectra

1998 ◽  
Vol 15 (5) ◽  
pp. 1157-1163 ◽  
Author(s):  
S. F. Heron ◽  
M. L. Heron
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Hf Radar ◽  
Significant Wave ◽  
Comparison Of Algorithms

scholarly journals A Wave Measurements HF Radar Data Set in the Malta-Sicily Channel: Data Quality, Validation and Gap Filling

10.29007/wg8s ◽  
2018 ◽  
Author(s):  
Marco Picone ◽  
Arianna Orasi ◽  
Aldo Drago ◽  
Fulvio Capodici ◽  
Giuseppe Ciraolo ◽  
...  
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Missing Values ◽  
Hf Radar ◽  
Data Set ◽  
Significant Wave ◽  
Wave Data ◽  
Wave Measurements ◽  
Sicily Channel ◽  
Radar Wave

The CALYPSO HF radar network is a permanent and fully operational observing system currently composed of four CODAR HF stations. The system is providing real- time hourly maps of sea surface currents and wave data in the Malta-Sicily Channel since 2012. Significant wave height derived from the HF radar wave measurements are confirmed to be a reliable source of wave information even in case of extreme events. However, it is noticed that the HF radar wave data are subject to differing interfering noise in the signal from unknown sources that may be competing with transmissions in the same frequency band. These interferences lead to frequent gaps and/or outliers that affect the continuity and reliability of the data set. The aim of this work is to estimate missing values and to detect possible outliers building and fitting a Markov chain mixture model on the significant wave height data collected at the four stations. It is verified that the proposed procedure is sufficiently robust since the model estimates succeed to classify radar observations with a high percentage of missing data and to equally highlight spikes and outliers.

scholarly journals Assessment of Significant Wave Height in the Taiwan Strait Measured by a Single HF Radar System

2019 ◽  
Vol 36 (7) ◽  
pp. 1419-1432 ◽  
Author(s):  
Linghui Cai ◽  
Shaoping Shang ◽  
Guomei Wei ◽  
Zhigang He ◽  
Yanshuang Xie ◽  
...  
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Model ◽  
Absolute Error ◽  
Taiwan Strait ◽  
Radar System ◽  
Hf Radar ◽  
Study Region ◽  
Significant Wave ◽  
Wave Measurements

AbstractDual high-frequency (HF) radar systems are often used to provide measurements of waves, winds, and currents. In this study, the accuracy of wave measurements using a single HF radar system (OS081H-A) was explored using datasets obtained during 5–27 January 2014 in the southwestern Taiwan Strait. We selected the study region as an area with >90% coverage (i.e., the range was <100 km). Qualitative and quantitative intercomparison of wave measurements (by the radar and five buoys) and wave model products [from the Simulating Wave Nearshore (SWAN) model] were conducted. Intercomparison of the modeled and in situ significant wave height Hs showed that the model-predicted Hs could be considered to be acceptable for use as “sea truth” to evaluate the radar-derived Hs, with mean bias from −0.45 to −0.16 m, mean absolute error (MAE) of 0.24–0.45 m, and root-mean-square error of 0.31–0.54 m. It was found that the MAE of radar-derived Hs was ≤ 1 m for 86% of the sector (except at the edge of sector) when the model-predicted Hs was ≥ 1.5 m. In particular, the MAE was less than 0.6 m for 63% of the sector, which was mainly distributed in the area with a bearing from −50° to +70° and a range of 20–70 km. The results are promising, but more work is needed. We employed a spatial distribution function for the MAE of the radar-derived Hs over the sample duration based on range, bearing, and mean radar-derived Hs.

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.

Sea State Estimation Based on Ship Motions Measurements and Data Fusion

2013 ◽  
Author(s):  
Céline Drouet ◽  
Nicolas Cellier ◽  
Jérémie Raymond ◽  
Denis Martigny
Keyword(s):  
Data Fusion ◽  
State Estimation ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Ship Motions ◽  
Sea State ◽  
Significant Wave ◽  
X Band

In-service monitoring can help to increase safety of ships especially regarding the fatigue assessment. For this purpose, it is compulsory to know the environmental conditions encountered: wind, but also the full directional wave spectrum. During the EU TULCS project, a full scale measurements campaign has been conducted onboard the CMA-CGM 13200 TEU container ship Rigoletto. She has been instrumented to measure deformation of the ship as well as the sea state encountered during its trip. This paper will focus on the sea state estimation. Three systems have been installed to estimate the sea state encountered by the Rigoletto: An X-band radar from Ocean Waves with WAMOS® system and two altimetric wave radars from RADAC®. Nevertheless, the measured significant wave height can be disturbed by several external elements like bow waves, sprays, sea surface ripples, etc… Furthermore, ship motions are also measured and can provide another estimation of the significant wave height using a specific algorithm developed by DCNS Research for the TULCS project. As all those estimations are inherently different, it is necessary to make a fusion of those data to provide a single estimation (“best estimate”) of the significant wave height. This paper will present the data fusion process developed for TULCS and show some first validation results.

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