scholarly journals Wave Height Distributions and Rogue Waves in the Eastern Mediterranean

2021 ◽  
Vol 9 (6) ◽  
pp. 660
Author(s):  
Sagi Knobler ◽  
Daniel Bar ◽  
Rotem Cohen ◽  
Dan Liberzon
Keyword(s):  
Wave Height ◽  
Eastern Mediterranean ◽  
Rogue Waves ◽  
Distribution Model ◽  
Storm Events ◽  
Order Model ◽  
Deep Seawater ◽  
Wave Heights ◽  
Storm Characteristics ◽  
Buoy Data

There is a lack of scientific knowledge about the physical sea characteristics of the eastern part of the Mediterranean Sea. The current work offers a comprehensive view of wave fields in southern Israel waters covering a period between January 2017 and June 2018. The analyzed data were collected by a meteorological buoy providing wind and waves parameters. As expected for this area, the strongest storm events occurred throughout October–April. In this paper, we analyze the buoy data following two main objectives—identifying the most appropriate statistical distribution model and examining wave data in search of rogue wave presence. The objectives were accomplished by comparing a number of models suitable for deep seawater waves. The Tayfun—Fedele 3rd order model showed the best agreement with the tail of the empirical wave heights distribution. Examination of different statistical thresholds for the identification of rogue waves resulted in the detection of 99 unique waves, all of relatively low height, except for one wave that reached 12.2 m in height which was detected during a powerful January 2018 storm. Characteristics of the detected rogue waves were examined, revealing the majority of them presenting crest to trough symmetry. This finding calls for a reevaluation of the crest amplitude being equal to or above 1.25 the significant wave height threshold which assumes rogue waves carry most of their energy in the crest.

Measured Metocean Characteristics of Gulf of Mexico Hurricanes

2015 ◽  
Author(s):  
George Z. Forristall ◽  
Jason McConochie
Keyword(s):  
Gulf Of Mexico ◽  
Wave Height ◽  
Storm Track ◽  
Significant Wave ◽  
Wind Speeds ◽  
Hurricane Wind ◽  
Wave Parameters ◽  
Wave Heights ◽  
Significant Wave Heights ◽  
Buoy Data

A wealth of Gulf of Mexico hurricane wind and wave data has been measured in recent years. We have constructed a database that combines HURDAT storm track information with NDBC buoy data for the years 1978–2010. HURDAT contains 141 storms for that period of which 67 had measured significant wave heights greater than 5 m. Industry measurements in Hurricanes Camille, Lili, Ivan, Katrina, Rita, Gustav and Ike have been added to the buoy data. We have used this data base to study the relationships between wind and wave parameters in hurricanes. Specifically, we have calculated regressions and equal probability contours for significant wave height and peak spectral periods, first and second moment periods, wave height and Jonswap gamma values, wind speeds and wave heights, and wave and wind directions. All of these calculations have been done for azimuthal quadrants of the storm and radial distances near and far from the storm center.

Error Estimation of Buoy, Satellite, and Model Wave Height Data

2007 ◽  
Vol 24 (9) ◽  
pp. 1665-1677 ◽  
Author(s):  
Peter A. E. M. Janssen ◽  
Saleh Abdalla ◽  
Hans Hersbach ◽  
Jean-Raymond Bidlot
Keyword(s):  
Collocation Method ◽  
Wave Height ◽  
Wave Model ◽  
Weather Forecasts ◽  
Model Wave ◽  
Analysis Scheme ◽  
Wave Heights ◽  
Forecasting System ◽  
Buoy Data ◽  
Height Data

Abstract Triple collocation is a powerful method to estimate the rms error in each of three collocated datasets, provided the errors are not correlated. Wave height analyses from the operational European Centre for Medium-Range Weather Forecasts (ECMWF) wave forecasting system over a 4-yr period are compared with independent buoy data and dependent European Remote Sensing Satellite-2 (ERS-2) altimeter wave height data, which have been used in the wave analysis. To apply the triple-collocation method, a fourth, independent dataset is obtained from a wave model hindcast without assimilation of altimeter wave observations. The seasonal dependence of the respective errors is discussed and, while in agreement with the properties of the analysis scheme, the wave height analysis is found to have the smallest error. In this comparison the altimeter wave height data have been obtained from an average over N individual observations. By comparing model wave height with the altimeter superobservations for different values of N, alternative estimates of altimeter and model error are obtained. There is only agreement with the estimates from the triple collocation when the correlation between individual altimeter observations is taken into account. The collocation method is also applied to estimate the error in Environmental Satellite (ENVISAT), ERS-2 altimeter, buoy, model first-guess, and analyzed wave heights. It is shown that there is a high correlation between ENVISAT and ERS-2 wave height error, while the quality of ENVISAT altimeter wave height is high.

scholarly journals Validation of Jason-1 and Envisat Remotely Sensed Wave Heights

2009 ◽  
Vol 26 (1) ◽  
pp. 123-134 ◽  
Author(s):  
Tom H. Durrant ◽  
Diana J. M. Greenslade ◽  
Ian Simmonds
Keyword(s):  
Wave Height ◽  
Systematic Difference ◽  
Environmental Data ◽  
Altimeter Data ◽  
Wave State ◽  
Common Reference ◽  
State Dependent ◽  
Linear Correction ◽  
Wave Heights ◽  
Buoy Data

Abstract Satellite altimetry provides an immensely valuable source of operational significant wave height (Hs) data. Currently, altimeters on board Jason-1 and Envisat provide global Hs observations, available within 3–5 h of real time. In this work, Hs data from these altimeters are validated against in situ buoy data from the National Data Buoy Center (NDBC) and Marine Environmental Data Service (MEDS) buoy networks. Data cover a period of three years for Envisat and more than four years for Jason-1. Collocation criteria of 50 km and 30 min yield 3452 and 2157 collocations for Jason-1 and Envisat, respectively. Jason-1 is found to be in no need of correction, performing well throughout the range of wave heights, although it is notably noisier than Envisat. An overall RMS difference between Jason-1 and buoy data of 0.227 m is found. Envisat has a tendency to overestimate low Hs and underestimate high Hs. A linear correction reduces the RMS difference by 7%, from 0.219 to 0.203 m. In addition to wave height–dependent biases in the altimeter Hs estimate, a wave state–dependent bias is also identified, with steep (smooth) waves producing a negative (positive) bias relative to buoys. A systematic difference in the Hs being reported by MEDS and NDBC buoy networks is also noted. Using the altimeter data as a common reference, it is estimated that MEDS buoys are underestimating Hs relative to NDBC buoys by about 10%.

scholarly journals PREDICTION METHOD FOR THE WAVE HEIGHT DISTRIBUTION OEF THE WESTERN COAST OE TAIWAN

1984 ◽  
Vol 1 (19) ◽  
pp. 31 ◽  
Author(s):  
Frederick L.W. Tang ◽  
Jea-Tzyy Juang
Keyword(s):  
Wave Height ◽  
Prediction Method ◽  
Distribution Model ◽  
Western Coast ◽  
Height Distribution ◽  
North West ◽  
The North ◽  
Wave Height Distribution ◽  
Wave Heights ◽  
The Western Pacific

Taiwan Strait locates on the continental shelf of the western Pacific Ocean. The water depth is less than 100 meters. Furthermore, the bathemetry of the eastern side namely the offing of western coast of Taiwan shoals gradually. In consequence, in case of the wind "blows from the north to south, waves in the deeper part of the strait refract to he north west direction while they are approaching the shore and local waves directly generated by the wind still keep the same direction of the wind. The situation is shown in Figure 1. Erom September to April of the next year, anticyclones come from Mongolia causes monsoon in this area. The wind velocity in the monsoon sometimes exceeds 20 meters per second, but it is arround 10 meters per second in general. Howerer, the duration of winds over 5 meters per second has been recorded more than 50 days. Engineering works such as towing caissons for building breakwater as well as dredging offshore have to be done in these days. Furthermore, navigation operations should not be stopped unless the wind is too strong. Of course, waves are forecast every day, however, more precise information about the probability of the occurrence of certain wave height is of great significance. In last conference, the authors submitted a probability density function of wave heights in this area. This distribution model is to be remended by considering energy loss in this paper, and concrete forecasting procedure is submitted for engineering and navigation practice.

scholarly journals Study of Directional Declustering for Estimating Extreme Wave Heights in the Yellow Sea

2020 ◽  
Vol 8 (4) ◽  
pp. 236 ◽  
Author(s):  
Huijun Gao ◽  
Zhuxiao Shao ◽  
Guoxiang Wu ◽  
Ping Li
Keyword(s):  
Wave Height ◽  
Yellow Sea ◽  
Significant Wave Height ◽  
Extreme Values ◽  
The Yellow Sea ◽  
Distribution Model ◽  
Significant Wave ◽  
Window Method ◽  
Wave Heights ◽  
Significant Wave Heights

The study of extreme waves is important for the protection of coastal and ocean structures. In this work, a 22-year (1990–2011) wave hindcast in the Yellow Sea is employed to perform the assessment of extreme significant wave heights in this area. To extract the independent sample from this database, the fixed window method is used, which takes the peak significant wave height within five d. With the selected samples, directional declustering is studied to extract the homogenous sample. The results show that most of the independent samples (especially large samples) are observed in the North. In this direction, the peak over threshold (POT) method is used to extract the extreme sample from the homogenous sample, and then the generalized Pareto distribution model is used to extrapolate the extreme significant wave height. In addition to this combination, the annual maxima method with the Gumbel model is also used for estimating extreme values. The comparisons show that the return significant wave heights of the first combination are reliable, resulting from a flexible sampling window in the POT method. With this conclusion, the extreme significant wave height is extrapolated from the Yellow Sea, which can be used to protect the structure in the main directional bin.

scholarly journals The Wave Heights Distribution of Random Wave Based on Ocean Basin

Kapal ◽  
2020 ◽  
Vol 17 (3) ◽  
pp. 114-122
Author(s):  
Nurman Firdaus ◽  
Baharuddin Ali ◽  
Mochammad Nasir ◽  
M Muryadin
Keyword(s):  
Wave Height ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Ocean Basin ◽  
Distribution Model ◽  
Exceedance Probability ◽  
Random Wave ◽  
Theoretical Spectrum ◽  
Sea State ◽  
Wave Heights

The wave height parameter in ocean waves is one of the important information for a marine structure design. The present paper investigates the results of wave heights distribution from laboratory-generated for single sea state. Data of the random wave time series collected at the ocean basin are analyzed using the wave spectrum and compared with the theoretical spectrum in this study. The random wave data is varied with four sea states consisting of sea states 3, 4, 5 and 6 obtained from laboratory measurements. The parameter conditions of generated sea waves are represented by a value of significant wave height and wave peak period in the range of sea states. The individual wave heights data in each sea state are presented in the form of exceedance probability distribution and the predictions using a linear model. This study aims to estimate the wave heights distribution using the Rayleigh and Weibull distribution model. Furthermore, the accuracy of the wave heights distribution data's prediction results in each sea state has been compared and examined for both models. The applied linear models indicate similar and reasonable estimations on the observed data trends.

scholarly journals On Correlation between Wind and Wave Storms

2021 ◽  
Vol 9 (12) ◽  
pp. 1426
Author(s):  
Valentina Laface ◽  
Felice Arena
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Significant Wave Height ◽  
The United States ◽  
Storm Events ◽  
Significant Wave ◽  
Wind Speeds ◽  
Wave Heights ◽  
Significant Wave Heights ◽  
Sea Storm

The paper is focused on the formulation of an adequate criterion for associating wave storm events to the generating wind storm ones, and on the study of correlation between their characteristic parameters. In this context, the sea storm definition commonly used for storm identification from significant wave height data is adapted for wind storm, by processing wind speed data. A sensitivity analysis is proposed as function of the storm thresholds aiming at identifying optimal combination of wind speed and significant wave height thresholds allowing the association of relatively large number of events ensuring high correlation between wind and wave storm parameters. The analysis is carried out using as input data wind speeds and significant wave heights from four meteorological (buoys and anemometers) stations of the National Data Buoy Center moored off the East Coast of the United States. Results reveal that an optimal threshold combination is achieved assuming both wind speed and significant wave height threshold as 1.5 time their respective averages.

scholarly journals Validation of Sentinel-3A/3B Satellite Altimetry Wave Heights with Buoy and Jason-3 Data

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2914 ◽  
Author(s):  
Jungang Yang ◽  
Jie Zhang
Keyword(s):  
Wave Height ◽  
Wave Climate ◽  
Global Ocean ◽  
National Data ◽  
M Wave ◽  
Wave Heights ◽  
Slight Upward Trend ◽  
Buoy Data ◽  
Climate Studies ◽  
Better Than

The validation of significant wave height (SWH) data measured by the Sentinel-3A/3B SAR Altimeter (SRAL) is essential for the application of the data in ocean wave monitoring, forecasting and wave climate studies. Sentinel-3A/3B SWH data are validated by comparisons with U. S. National Data Buoy Center (NDBC) buoys, using a spatial scale of 25 km and a temporal scale of 30 min, and with Jason-3 data at their crossovers, using a time difference of less than 30 min. The comparisons with NDBC buoy data show that the root-mean-square error (RMSE) of Sentinel-3A SWH is 0.30 m, and that of Sentinel-3B is no more than 0.31 m. The pseudo-Low-Resolution Mode (PLRM) SWH is slightly better than that of the Synthetic Aperture Radar (SAR) mode. The statistical analysis of Sentinel-3A/3B SWH in the bin of 0.5 m wave height shows that the accuracy of Sentinel-3A/3B SWH data decreases with increasing wave height. The analysis of the monthly biases and RMSEs of Sentinel-3A SWH shows that Sentinel-3A SWH are stable and have a slight upward trend with time. The comparisons with Jason-3 data show that SWH of Sentinel-3A and Jason-3 are consistent in the global ocean. Finally, the piecewise calibration functions are given for the calibration of Sentinel-3A/3B SWH. The results of the study show that Sentinel-3A/3B SWH data have high accuracy and remain stable.

scholarly journals Wind Speed Dependence of Single-Site Wave-Height Retrievals from High-Frequency Radars

2010 ◽  
Vol 27 (8) ◽  
pp. 1381-1394 ◽  
Author(s):  
Brian K. Haus ◽  
Lynn K. Shay ◽  
Paul A. Work ◽  
George Voulgaris ◽  
Rafael J. Ramos ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
High Frequency ◽  
Hf Radar ◽  
Single Site ◽  
Scale Separation ◽  
Peak Energy ◽  
Wave Heights ◽  
Acoustic Doppler Profiler ◽  
Buoy Data

Abstract Wave-height observations derived from single-site high-frequency (HF) radar backscattered Doppler spectra are generally recognized to be less accurate than overlapping radar techniques but can provide significantly larger sampling regions. The larger available wave-sampling region may have important implications for observing system design. Comparison of HF radar–derived wave heights with acoustic Doppler profiler and buoy data revealed that the scale separation between the Bragg scattering waves and the peak energy-containing waves may contribute to errors in the single-site estimates in light-to-moderate winds. A wave-height correction factor was developed that explicitly considers this scale separation and eliminates the trend of increasing errors with increasing wind speed.

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.

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