scholarly journals Numerical Simulations and Observations of Surface Wave Fields under an Extreme Tropical Cyclone

2009 ◽  
Vol 39 (9) ◽  
pp. 2097-2116 ◽  
Author(s):  
Yalin Fan ◽  
Isaac Ginis ◽  
Tetsu Hara ◽  
C. Wayne Wright ◽  
Edward J. Walsh
Keyword(s):  
Surface Wave ◽  
Tropical Cyclone ◽  
Drag Coefficient ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Spectrum ◽  
Ocean Current ◽  
Radar Altimeter ◽  
Dominant Wavelength ◽  
Significant Wave

Abstract The performance of the wave model WAVEWATCH III under a very strong, category 5, tropical cyclone wind forcing is investigated with different drag coefficient parameterizations and ocean current inputs. The model results are compared with field observations of the surface wave spectra from an airborne scanning radar altimeter, National Data Buoy Center (NDBC) time series, and satellite altimeter measurements in Hurricane Ivan (2004). The results suggest that the model with the original drag coefficient parameterization tends to overestimate the significant wave height and the dominant wavelength and produces a wave spectrum with narrower directional spreading. When an improved drag parameterization is introduced and the wave–current interaction is included, the model yields an improved forecast of significant wave height, but underestimates the dominant wavelength. When the hurricane moves over a preexisting mesoscale ocean feature, such as the Loop Current in the Gulf of Mexico or a warm- and cold-core ring, the current associated with the feature can accelerate or decelerate the wave propagation and significantly modulate the wave spectrum.

Wave Probabilities Consistent with Official Tropical Cyclone Forecasts

2016 ◽  
Vol 31 (6) ◽  
pp. 2035-2045 ◽  
Author(s):  
Charles R. Sampson ◽  
James A. Hansen ◽  
Paul A. Wittmann ◽  
John A. Knaff ◽  
Andrea Schumacher
Keyword(s):  
Surface Wave ◽  
Wind Speed ◽  
Tropical Cyclone ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Model ◽  
Significant Wave ◽  
Wave Heights ◽  
Significant Wave Heights ◽  
Ocean Surface Wave

Abstract Development of a 12-ft-seas significant wave height ensemble consistent with the official tropical cyclone intensity, track, and wind structure forecasts and their errors from the operational U.S. tropical cyclone forecast centers is described. To generate the significant wave height ensemble, a Monte Carlo wind speed probability algorithm that produces forecast ensemble members is used. These forecast ensemble members, each created from the official forecast and randomly sampled errors from historical official forecast errors, are then created immediately after the official forecast is completed. Of 1000 forecast ensemble members produced by the wind speed algorithm, 128 of them are selected and processed to produce wind input for an ocean surface wave model. The wave model is then run once per realization to produce 128 possible forecasts of significant wave height. Probabilities of significant wave height at critical thresholds can then be computed from the ocean surface wave model–generated significant wave heights. Evaluations of the ensemble are provided in terms of maximum significant wave height and radius of 12-ft significant wave height—two parameters of interest to both U.S. Navy meteorologists and U.S. Navy operators. Ensemble mean errors and biases of maximum significant wave height and radius of 12-ft significant wave height are found to be similar to those of a deterministic version of the same algorithm. Ensemble spreads capture most verifying maximum and radii of 12-ft significant wave heights.

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.

scholarly journals A Simple Method for Retrieving Significant Wave Height from Dopplerized X-Band Radar

2016 ◽  
Author(s):  
Ruben Carrasco ◽  
Michael Streßer ◽  
Jochen Horstmann
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Spectrum ◽  
Doppler Velocity ◽  
Modulation Transfer ◽  
Simple Method ◽  
Backscatter Intensity ◽  
Significant Wave ◽  
X Band ◽  
Variance Spectrum

Abstract. Retrieving spectral wave parameters such as the peak wave direction and wave period from marine radar backscatter intensity is very well developed. However, the retrieval of significant wave height is difficult because the radar image spectrum (a backscatter intensity variance spectrum) has to be transferred to a wave spectrum (a surface elevation variance spectrum) using a modulation transfer function (MTF) which requires extensive calibration for each individual radar setup. In contrast to the backscatter intensity, the Doppler velocity measured by a coherent radar is induced by the radial velocity of the surface scattering and its periodic component is mainly the contribution of surface waves. Therefore, the variance of the Doppler velocity can be utilized to retrieve the significant wave height. Analysing approximately 100 days of Doppler velocity measurements of a coherent on receive radar operating at X-band with vertical polarization in transmit and receive, a simple relation was derived and validated to retrieve significant wave heights. Comparison to wave measurements of a wave rider buoy as well as an acoustic wave and current profiler resulted in a root mean square error of 0.24 m with a bias of 0.08 m. Furthermore, the different sources of error are discussed and investigated.

scholarly journals Wave spectral shapes in the coastal waters based on measured data off Karwar, west coast of India

2017 ◽  
Author(s):  
M. Anjali Nair ◽  
V. Sanil Kumar
Keyword(s):  
Wave Height ◽  
Coastal Waters ◽  
High Frequency ◽  
Significant Wave Height ◽  
Wave Spectrum ◽  
Temporal Variations ◽  
Wave Spectra ◽  
Monsoon Period ◽  
Significant Wave ◽  
Spectral Shapes

Abstract. Understanding of the wave spectral shapes is of primary importance for the design of marine facilities. In this paper, the wave spectra collected from January 2011 to December 2015 in the coastal waters are examined to know the temporal variations in the wave spectral shape. For 31.15 % of the time, peak frequency is between 0.08 and 0.10 Hz and the significant wave height is also relatively high (~ 1.55 m) for waves in this class. The slope of the high-frequency tail of the monthly average wave spectra is high during the Indian summer monsoon period (June–September) compared to other months and it increases with increase in significant wave height. There is no much interannual variation in slope for swell dominated spectra during the monsoon, while in the non-monsoon period when wind-seas have much influence, the slope varies significantly. Since the high-frequency slope of the wave spectrum is within the range 3–4 during the monsoon period, Donelan spectrum shows better fit for the wave spectra in monsoon months compared to other months.

Gap-Filling and Predicting Wave Parameters Using Support Vector Regression Method

2011 ◽  
Author(s):  
Maziar Golestani ◽  
Mostafa Zeinoddini
Keyword(s):  
Support Vector Regression ◽  
Wave Height ◽  
Significant Wave Height ◽  
Rational Design ◽  
Wave Spectrum ◽  
Support Vector ◽  
Wave Spectra ◽  
Significant Wave ◽  
Wave Parameters ◽  
Data Gaps

Knowledge of relevant oceanographic parameters is of utmost importance in the rational design of coastal structures and ports. Therefore, an accurate prediction of wave parameters is especially important for safety and economic reasons. Recently, statistical learning methods, such as Support Vector Regression (SVR) have been successfully employed by researchers in problems such as lake water level predictions, and significant wave height prediction. The current study reports potential application of a SVR approach to predict the wave spectra and significant wave height. Also the capability of the model to fill data gaps was tested using different approaches. Concurrent wind and wave records (standard meteorological and spectral density data) from 4 stations in 2003, 2007, 2008 and 2009 were used both for the training the SVR system and its verification. The choice of these four locations facilitated the comparison of model performances in different geographical areas. The SVR model was then used to obtain predictions for the wave spectra and also time series of wave parameters (separately for each station) such as its Hs and Tp from spectra and wind records. New approach was used to predict wave spectra comparing to similar studies. Reasonably well correlation was found between the predicted and measured wave parameters. The SVR model was first trained and tested using various methods for selecting training data. Also different values for SVM parameters (e.g. tolerance of termination criterion, cost, and gamma in kernel function) were tested. The best possible results were obtained using a Unix shell script (in Linux) which automatically implements different values for different input parameters and finds the best regression by calculating statistical scores like correlation of coefficient, RMSE, bias and scatter index. Finally for a better understanding of the results, Quantile-Quantile plots were produced. The results show that SVR can be successfully used for prediction of Hs and wave spectrum out of a series of wind and spectral wave parameters inputs. Also it was noticed that SVR is an efficient tool to be used when data gaps are present in the data.

The corrections for significant wave height and attitude effects in the TOPEX radar altimeter

1994 ◽  
Vol 99 (C12) ◽  
pp. 24941 ◽  
Author(s):  
G. S. Hayne ◽  
D. W. Hancock ◽  
C. L. Purdy ◽  
P. S. Callahan
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Radar Altimeter ◽  
Significant Wave

scholarly journals Atmospheric Cold Front-Generated Waves in the Coastal Louisiana

2020 ◽  
Vol 8 (11) ◽  
pp. 900
Author(s):  
Yuhan Cao ◽  
Chunyan Li ◽  
Changming Dong
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Cold Front ◽  
Wave Spectrum ◽  
Low Frequency ◽  
Wave Direction ◽  
Significant Wave ◽  
Cold Fronts ◽  
Directional Wave ◽  
Coastal Louisiana

Atmospheric cold front-generated waves play an important role in the air–sea interaction and coastal water and sediment transports. In-situ observations from two offshore stations are used to investigate variations of directional waves in the coastal Louisiana. Hourly time series of significant wave height and peak wave period are examined for data from 2004, except for the summer time between May and August, when cold fronts are infrequent and weak. The intra-seasonal scale variations in the wavefield are significantly affected by the atmospheric cold frontal events. The wave fields and directional wave spectra induced by four selected cold front passages over the coastal Louisiana are discussed. It is found that significant wave height generated by cold fronts coming from the west change more quickly than that by other passing cold fronts. The peak wave direction rotates clockwise during the cold front events. The variability of the directional wave spectrum shows that the largest spectral density is distributed at low frequency in the postfrontal phase associated with migrating cyclones (MC storms) and arctic surges (AS storms).

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