2021
Knobler, Sagi; Bar, Daniel; Cohen, Rotem; Liberzon, Dan
Wave Height Distributions and Rogue Waves in the Eastern Mediterranean Journal Article
In: Journal of Marine Science and Engineering, 9 (6), pp. 660, 2021, ISSN: 2077-1312.
@article{jmse9060660,
title = {Wave Height Distributions and Rogue Waves in the Eastern Mediterranean},
author = {Knobler, Sagi and Bar, Daniel and Cohen, Rotem and Liberzon, Dan},
editor = {Takuji Waseda, Ian Young, Alfred Osborne and Sonia Ponce de León},
url = {https://www.mdpi.com/2077-1312/9/6/660},
doi = {10.3390/jmse9060660},
issn = {2077-1312},
year = {2021},
date = {2021-07-14},
journal = {Journal of Marine Science and Engineering},
volume = {9},
number = {6},
pages = {660},
abstract = {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.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
2019
Liberzon, Dan; Vreme, Alexandru; Knobler, Sagi; Bentwich, Itamar
Detection of Breaking Waves in Single Wave Gauge Records of Surface Elevation Fluctuations Journal Article
In: Journal of Atmospheric and Oceanic Technology, 36 (9), pp. 1863-1879, 2019, ISSN: 0739-0572.
@article{10.1175/JTECH-D-19-0011.1b,
title = {Detection of Breaking Waves in Single Wave Gauge Records of Surface Elevation Fluctuations},
author = {Dan Liberzon and Alexandru Vreme and Sagi Knobler and Itamar Bentwich},
url = {https://doi.org/10.1175/JTECH-D-19-0011.1},
doi = {10.1175/JTECH-D-19-0011.1},
issn = {0739-0572},
year = {2019},
date = {2019-01-01},
journal = {Journal of Atmospheric and Oceanic Technology},
volume = {36},
number = {9},
pages = {1863-1879},
abstract = {We report the development of a new method for accurate detection of breaking water waves that addresses the need for an accurate and cost-effective method that is independent of human decisions. The new detection method, which enables the detection of breakers using only surface elevation fluctuation measurements from a single wave gauge, supports the development of a new method for research relating to water waves and wind–wave interactions. According to the proposed method, detection is based on the use of the phase-time method to identify breaking-associated patterns in the instantaneous frequency variations of surface elevation fluctuations. A wavelet-based pattern recognition algorithm is devised to detect such patterns and provide accurate detection of breakers in the examined records. Validation and performance tests, conducted using both laboratory and open-sea data, including mechanically generated and wind-forced waves, are reported as well. These tests allow us to derive a set of parameters that assure high detection accuracy rates. The method is shown to be capable to achieve a positive detection rate exceeding 90%.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We report the development of a new method for accurate detection of breaking water waves that addresses the need for an accurate and cost-effective method that is independent of human decisions. The new detection method, which enables the detection of breakers using only surface elevation fluctuation measurements from a single wave gauge, supports the development of a new method for research relating to water waves and wind–wave interactions. According to the proposed method, detection is based on the use of the phase-time method to identify breaking-associated patterns in the instantaneous frequency variations of surface elevation fluctuations. A wavelet-based pattern recognition algorithm is devised to detect such patterns and provide accurate detection of breakers in the examined records. Validation and performance tests, conducted using both laboratory and open-sea data, including mechanically generated and wind-forced waves, are reported as well. These tests allow us to derive a set of parameters that assure high detection accuracy rates. The method is shown to be capable to achieve a positive detection rate exceeding 90%.
