scholarly journals Wave Height and Wave Period Derived from a Shipboard Coherent S-Band Wave Radar in the South China Sea

2019 ◽  
Vol 11 (23) ◽  
pp. 2812 ◽  
Author(s):  
Chen ◽  
Chen ◽  
Zhao ◽  
Wang

To expand the scope of ocean wave observations, a shipboard coherent S-band wave radar system was developed recently. The radar directly measures the wave orbital velocity from the Doppler shift of the received radar signal. The sources of this Doppler shift are analyzed. After removing the Doppler shifts caused by the ocean current and platform, the radial velocities of water particles of the surface gravity waves are retrieved. Subsequently, the wavenumber spectrum can be obtained based on linear wave theory. Later, the significant wave height and wave periods (including mean wave period and peak wave period) can be calculated from the wavenumber spectrum. This radar provides a calibration-free way to measure wave parameters and is a novel underway coherent microwave wave radar. From 9 September to 11 September, 2018, an experiment involving radar-derived and buoy-measured wave measurements was conducted in the South China Sea. The Doppler spectra obtained when the ship was in the state of navigation or mooring indicated that the quality of the radar echo was fairly good. The significant wave heights and wave periods measured using the radar are compared with those obtained from the wave buoy. The correlation coefficients of wave heights and mean wave periods between these two instruments both exceed 0.9 while the root mean square differences are respectively less than 0.15 m and 0.25 s, regardless of the state of motion of the ship. These results indicate that this radar has the capability to accurately measure ocean wave heights and wave periods.

2019 ◽  
Author(s):  
Zhuxiao Shao ◽  
Bingchen Liang ◽  
Huajun Li ◽  
Ping Li ◽  
Dongyoung Lee

Abstract. An assessment of extreme significant wave heights is performed in the South China Sea (SCS), which is crucial for the coastal and offshore engineering in this area. Two significant factors influencing the assessment are the initial database and the assessing method. The initial database is a basic for assessment, and the assessing method is used to extrapolate appropriate return significant wave heights based on this database during a period. In this study, a 40-year (1975–2014) hindcasted significant wave height of tropical cyclone waves is adopted as the initial database. Based on this database, the peak significant wave height of every tropical cyclone wave is directly extracted as the initial sample; the independent and identically distributed assumption is satisfied; and the interference for the selection of the sample is avoided. The peak over threshold (POT) method with the generalized Pareto distribution (GPD) model is employed to extract the sufficiently large and high sample for model estimation. The peak excesses over a sufficiently high value (i.e., threshold) are fitted; thus, the return significant wave heights are highly dependent on the threshold. To determine the unique threshold for the POT method, characteristics of tropical cyclone waves are researched. The research results reveal that the separation value shown in the distribution of the initial sample is suitable for sampling in the SCS. Because the separation value is within the stable threshold range and the asymptotic tail approximation and estimation uncertainty are reasonable, the selected threshold is suitable and the corresponding return significant wave height is reliable.


2019 ◽  
Vol 19 (10) ◽  
pp. 2067-2077 ◽  
Author(s):  
Zhuxiao Shao ◽  
Bingchen Liang ◽  
Huajun Li ◽  
Ping Li ◽  
Dongyoung Lee

Abstract. Extreme significant wave heights are assessed in the South China Sea (SCS), as assessments of wave heights are crucial for coastal and offshore engineering. Two significant factors include the initial database and assessment method. The initial database is a basis for assessment, and the assessment method is used to extrapolate appropriate return-significant wave heights during a given period. In this study, a 40-year (1975–2014) hindcast of tropical cyclone waves is used to analyse the extreme significant wave height, employing the peak over threshold (POT) method with the generalized Pareto distribution (GPD) model. The peak exceedances over a sufficiently large value (i.e. threshold) are fitted; thus, the return-significant wave heights are highly dependent on the threshold. To determine a suitable threshold, the sensitivity of return-significant wave heights and the characteristics of tropical cyclone waves are studied. The sample distribution presents a separation that distinguishes the high sample from the low sample, and this separation is within the stable threshold range. Because the variation in return-significant wave heights in this range is generally small and the separation is objectively determined by the track and intensity of the tropical cyclone, the separation is selected as a suitable threshold for extracting the extreme sample in the tropical cyclone wave. The asymptotic tail approximation and estimation uncertainty show that the selection is reasonable.


2018 ◽  
Vol 147 ◽  
pp. 05001
Author(s):  
Rima Rachmayani ◽  
Nining Sari Ningsih ◽  
Hani Ramadhan ◽  
Suliskania Nurfitri

Understanding the characteristics of the ocean wave in Indonesian Seas particularly in western Indonesian Seas is crucial to establish secured marine activities in addition to construct well-built marine infrastructures. Three-years-data (July 1996 - 1999) simulated from Simulating Waves Nearshore (SWAN) model were used to analyze the ocean wave characteristics and variabilities in eastern Indian Ocean, Java Sea, and South China Sea. The interannual or seasonal variability of the significant wave height is affected by the alteration of wind speed and direction. Interactions between Indian Ocean Dipole Mode (IODM), El Niño Southern Oscillation (ENSO) and monsoon result in interannual ocean wave variability in the study areas. Empirical Orthogonal Functions (EOF) analysis produces 6 modes represents 95% of total variance that influence the wave height variability in the entire model domain. Mode 1 was dominated by annual monsoon and has spatial dominant contribution in South China Sea effected by ENSO and Indian Ocean influenced by IODM. Java Sea was influenced by Mode 2 which is controlled by semi-annual monsoon and IODM. A positive (negative) IODM strengthens (weakens) the winds speed in Java Sea during the East (West) season and hence contributes to Mode 2 in increasing (decreasing) the significant wave in Java Sea.


Author(s):  
Andreas Sterl ◽  
Sofia Caires

The European Centre for Medium Range Weather Forecasts (ECMWF) has recently finished ERA-40, a reanalysis covering the period September 1957 to August 2002. One of the products of ERA-40 consists of 6-hourly global fields of wave parameters like significant wave height and wave period. These data have been generated with the Centre’s WAM wave model. From these results the authors have derived climatologies of important wave parameters, including significant wave height, mean wave period, and extreme significant wave heights. Particular emphasis is on the variability of these parameters, both in space and time. Besides for scientists studying climate change, these results are also important for engineers who have to design maritime constructions. This paper describes the ERA-40 data and gives an overview of the results derived. The results are available on a global 1.5° × 1.5° grid. They are accessible from the web-based KNMI/ERA-40 Wave Atlas at http://www.knmi.nl/waveatlas.


2013 ◽  
Vol 726-731 ◽  
pp. 833-841 ◽  
Author(s):  
Liang Pang ◽  
Xuan Chen ◽  
Yu Long Li

The sea state of the South China Sea is influenced by tropical cyclone obviously. It is important to carry out the long-term prediction and probability analysis of typhoon wind, wave height and wave period for the coastal and offshore engineering. In this paper the measured wind and wave data during typhoon processes from 1964-1989 are used to predict the long-term extreme sea states by using Grey Markov Chain Model. And the joint probability analysis of extreme wave height with concomitant wave period and wind speed is performed by using Multivariate Compound Extreme Distribution model which involves typhoon occurrence frequency and corresponding joint probability distribution of typhoon induced extreme sea environmental events. The proposed model shows that the mean value of typhoon occurring frequency per year plays the significant role in long term prediction of typhoon induced joint return values of extreme sea events.


2016 ◽  
Vol 2016 ◽  
pp. 1-21 ◽  
Author(s):  
Adekunle Osinowo ◽  
Xiaopei Lin ◽  
Dongliang Zhao ◽  
Zhifeng Wang

This paper describes long-term spatiotemporal trends in extreme significant wave height (SWH) in the South China Sea (SCS) based on 30-year wave hindcast. High-resolution reanalysis wind field data sets are employed to drive a spectral wave model WAVEWATCH III™ (WW3). The wave hindcast information is validated using altimeter wave information (Topex/Poseidon). The model performance is satisfactory. Subsequently, the trends in yearly/seasonal/monthly mean extreme SWH are analyzed. Results showed that trends greater than 0.05 m yr−1are distributed over a large part of the central SCS. During winter, strong positive trends (0.07–0.08 m yr−1) are found in the extreme northeast SCS. Significant trends greater than 0.01 m yr−1are distributed over most parts of the central SCS in spring. In summer, significant increasing trends (0.01–0.05 m yr−1) are distributed over most regions below latitude 16°N. During autumn, strong positive trends between 0.02 and 0.08 m yr−1are found in small regions above latitude 12°N. Increasing positive trends are found to be generally significant in the central SCS in December, February, March, and July. Furthermore, temporal trend analysis showed that the extreme SWH exhibits a significant increasing trend of 0.011 m yr−1. The extreme SWH exhibits the strongest increasing trend of 0.03 m yr−1in winter and showed a decreasing trend of −0.0098 m yr−1in autumn.


Sign in / Sign up

Export Citation Format

Share Document