Wind-wave Relationship Research Articles

Simplified models of wind-wave relationships in China's shallow-water coasts based on SWAN+ADCIRC simulations

The study of the shallow-water wind-wave relationship holds considerable importance in the realm of coastal engineering construction. However, existing empirical formulas for China's coastal areas face predictive accuracy challenges due to the discontinuity and insufficient temporal and spatial resolution of conventional observations, such as buoy and satellite data. Therefore, this study emphasizes two representative shallow-water areas along China's coast, the Pearl River Estuary and Bohai Bay. Based on the advanced SWAN + ADCIRC wave-current coupling model, numerical models for calculating wave evolution are established, calibrated and validated by real observation data. From these numerical foundations, a new model capturing shallow-water wind-wave relationship is proposed, demonstrating substantive applicability specifically tailored to the estuary and bay regions. The accuracy and applicability of the model are validated by comparing with real observation data. In addition, probabilistic models are introduced in this study accounting for the randomness of the significant wave height. These enhancements allow for refined quantification of significant wave height occurrence probabilities relative to specified wind speeds, offering informed predictive parameters, including upper and lower limits.

Ensemble Hindcasting of Coastal Wave Heights

Long records of wave parameters are central to the estimation of coastal flooding risk and the causes of coastal erosion. This paper leverages the predictive power of wave height history and correlations with wind speed and direction to build statistical models for time series of wave heights to develop a method to fill data-gaps and extend the record length of coastal wave observations. A threshold regression model is built where the threshold parameter, based on lagged wind speed, explains the nonlinear associations, and the lagged predictors in the model are based on a well-established empirical wind-wave relationship. The predictive model is completed by addressing the residual conditional heteroscedasticity using a GARCH model. This comprehensive model is trained on time series data from 2005 to 2013, using wave height and wind data both observed from a buoy in Long Island Sound. Subsequently, replacing wind data with observations from a nearby coastal station provides a similar level of predictive accuracy. This approach can be used to hindcast wave heights for past decades given only wind information at a coastal station. These hindcasts are used as a representative of the unobserved past to carry out extreme value analysis by fitting Generalized Pareto (GP) distribution in a peaks over threshold (POT) framework. By analyzing longer periods of data, we can obtain reliable return value estimates to help design better coastal protection structures.

Wind-Wave Relationship Model and Analysis of Typhoon Wave Fields in the South China Sea From HY-2A Satellite Observations

Significant wave height is an important parameter for characterizing ocean surface waves. With the development of remote sensing technology, satellite radar altimetry has become an essential tool for obtaining significant wave height estimations. However, its measurement only covers the satellite track on the ground and cannot be applied to large regions or areas. In this study, we obtained significant wave height from the Hai Yang-2A (HY-2A) radar altimeter and sea surface wind speed at a 10-m height from the HY-2A microwave scatterometer for October 2013, and then proposed a wind-wave relationship model for the South China Sea using linear/nonlinear regression analysis at high/low wind speeds (0–40 m s–1). By comparison with two other wind-wave models and validation with HY-2A observations in November 2013, our results show that the proposed wind-wave relationship model is credible, and at low wind speed exhibited good consistency with the wind-wave model from in situ observations. According to the proposed model, significant wave height from the HY-2A microwave scatterometer-retrieved wind speed and ocean wind wave analysis during the “1329” Typhoon Krosa were successfully obtained and determined. Data coverage of the computed significant wave height was far wider than that of the satellite radar altimeter observations and demonstrated development of typhoon wave fields over a large region. Overall, this study and proposed model provide useful information for the analysis and forecast of typhoon waves and potential storm surge disasters.

A quantitative model of paleowind reconstruction using subsurface lacustrine longshore bar deposits – An attempt

The paleo-atmospheric flow field is an important component of climate. However, the difficulty of constraining paleowind fields using geological information hinders quantification of paleo-atmospheric conditions. In this paper, it is proposed that the geometric characteristics of lacustrine longshore bars, widespread in both modern and ancient shallow lakes, can be used as proxies for paleowind fields. The self-organizational model of longshore bar formation indicates that bar geometry and dimensions are determined by breaking waves. Accordingly, a simple geometric model is proposed that incorporates empirical constraints, including: 1) the ratio of paleowater depths between bar crest and adjacent landward trough is constant, and 2) the bar landward slope reaches the angle of repose. The model suggests that the parameters longshore bar thickness (t), topographic slope of the bar-basement (α) and paleo-fetch of the basin (F) are sufficient to constrain paleowave conditions, and hence, based on wave statistics and wind-wave relationships, paleowind conditions. The method is then applied to an ancient example, the Dongying Depression in East China, to determine wind direction and strength during part of the Eocene (~45.0–44.2 Ma). The results show that contemporaneous northerly and southeasterly winds existed, with highest wind speeds of 6.9–13.5 m s−1 and 7.5–18.2 m s−1, respectively. These findings provide a new perspective on delineating paleowind conditions. Error analyses reveal that for a sufficiently large lake (fetch exceeding 30 km), calculation errors will be small to negligible, if longshore bar thickness is determined as precisely as possible. The method is applicable only for bars whose formation conforms to the self-organizational model.

A method to define the palaeowind strength from lacustrine parameters

AbstractGravelly beach ridges, which are formed solely by swash processes, may accurately reflect past wave conditions. The thickness (or height) of a gravelly beach ridge approximately equals the height of wave inundation, which is the sum of the surge and wave run‐up. Their ancient counterparts, if well‐preserved and identified, can be used to estimate palaeowave conditions, which can later be converted to palaeowind intensities based on wind–wave relationships. A technique is described for estimating the palaeowind speed in this paper, which is referred to as the gravelly beach‐ridge thickness technique. By comparing these estimates with instrumental wind records obtained at a modern lake, Qinghai Lake in north‐western China, the beach‐ridge thickness technique is shown to be useful for estimating the average wind speed (Vavg). When applying this method to ancient fetch‐limited basins, five parameters are necessary: (i) the thickness of the isolated gravelly beach ridge; (ii) the average depth of the water body; (iii) the palaeofetch; (iv) the angle between the palaeowind direction and the normal to the shoreline; and (v) the particle size. This technique was applied to an ancient example in the Eocene Dongying Depression, located in eastern China. The results indicate that the average wind speed of the northern wind ranged between 2·27 m sec−1 and 8·36 m sec−1 from 45·0 Ma to 42·0 Ma, and displayed a generally decreasing trend that included early strengthening followed by weakening and later strengthening during this period. The beach‐ridge thickness technique provides a new perspective on delineating palaeowind conditions and can be applied to ancient fetch‐limited basins with gravelly beach ridges worldwide. Generally, if a water body is sufficiently large (fetch exceeding 40 km), deep (average depth exceeding 10 m) and waves (or winds) are determined to approach the shoreline with high angles (angle of incidence <35°), then the calculation errors will be small to negligible.

Wind Speed Inversion in High Frequency Radar Based on Neural Network

Wind speed is an important sea surface dynamic parameter which influences a wide variety of oceanic applications. Wave height and wind direction can be extracted from high frequency radar echo spectra with a relatively high accuracy, while the estimation of wind speed is still a challenge. This paper describes an artificial neural network based method to estimate the wind speed in HF radar which can be trained to store the specific but unknown wind-wave relationship by the historical buoy data sets. The method is validated by one-month-long data of SeaSonde radar, the correlation coefficient between the radar estimates and the buoy records is 0.68, and the root mean square error is 1.7 m/s. This method also performs well in a rather wide range of time and space (2 years around and 360 km away). This result shows that the ANN is an efficient tool to help make the wind speed an operational product of the HF radar.

Influence of wind, wave, and water level dynamics on walleye eggs in a north temperate lake

Walleye (Sander vitreus) populations are cyclic because of biotic and abiotic factors, and wind activity, wave energy, and water levels may be influential given walleye spawn close to shore. We installed an anemometer and tridirectional velocimeter on a spawning reef in Big Crooked Lake, Wisconsin, in 2005 to determine wind–wave relationships and wave energy exceedance of critical velocities of both egg (affecting transport) and substrates (affecting abrasion or burial). To evaluate egg movement, we delineated egg locations at adhesive, postspawn, and black-eyed stages and surveyed on-shore for stranded eggs. We monitored water level with a staff gauge. Wind and wave velocities were significantly (p < 0.01) correlated, and wave velocities were significantly higher (p < 0.01) nearshore (2.0 m) than further from shore (4.6 m). Mean nearshore wave velocities were often sufficient to initiate movement of nonadhesive eggs (45% of records) and fine sand (39%) during egg incubation. Surveys indicated waves moved eggs closer to shore and some onto shore. Water level fluctuations (range = 2.4 cm) likely did not strand or desiccate eggs. We documented that wind and wave activity transports eggs and substrates and should be considered a critical factor in annual walleye egg survival and year-class strength.

Inverse modeling to derive wind parameters from wave measurements

The problem of deriving wind parameters from measured waves is discussed in this paper. Such a need reportedly arises in the field when the wind sensor attached to a wave rider buoy at high elevation from the sea level gets disconnected during rough weather, or otherwise needs repairs. This task is viewed as an inverse modeling approach as against the direct and common one of evaluating the wind-wave relationship. Two purely nonlinear approaches of soft computing, namely genetic programming (GP) and artificial neural network (ANN) have been used. The study is oriented towards measurements made at five different offshore locations in the Arabian Sea and around the western Indian coastline. It is found that although the results of both soft approaches rival each other, GP has a tendency to produce more accurate results than the adopted ANN. It was also noticed that the equation-based GP model could be equally useful as the one based on computer programs, and hence for the sake of simplicity in implementation, the former can be adopted. In case the entire wave rider buoy does not function for some period, a common regional GP model prescribed in this work can still produce the desired wind parameters with the help of wave observations available from anywhere in the region. A graphical user interface is developed that puts the derived models to their actual use in the field.

Wind-wave relationship for bay of Bengal from GEOSAT data

Stellite Remote Sensing is an emerging technique for observation of oceans. The important oceanic parameters, wave heights and wind speeds derived fron GEOSAT Altimeter data, are analysed in the present paper. Relation between wind speed and height of ‘sea waves’ are obtained for southwest monsoon, northeast monsoon and nonmonsoon seasons, and regression equations are arrived at for each case. Good correlation and high accuracy are observed for all the seasons. This assures the usage of remotely sensed data for oceanic studies.

Wind-wave relationship from SEASAT radar altimeter data

We present a nonlinear relationship between ocean surface wind at 10 m height (U 10 ) and significant wave height of wind-generated gravity waves, (H 1/3)gw, over the open oceans using SEASAT radar altimeter data. The data represent a variety of fetches, durations and strength of winds. Concurrent measurement of significant wave height, (H 1/3 ), which may contain a measure of swell and U 10 obtained from the processed geophysical data record (GDR) of the SEASAT radar altimeter were used in the analysis. The total wave energy, E alt, characterised by altimeter H 1/3 measurements was compared with the energy of a fully developed sea, E fd derived from U 10 measurements using the Pierson-Moskowitz model. The criteria E alt ≤ E fd was used in data selection to minimise the influence of swell. (H 1/3)gw thus obtained was used in a regression in terms of U 10 in a second-degree polynomial. Verification with independent radar altimeter data confirmed the validity of the proposed wind-wave model, which could be used for operational wave forecasting.

Wind-wave relationships for a coastal site in the Central English Channel

Waves have been recorded at a coastal site in the Central English Channel over a period of two years. By correlating wind and wave height data, empirical relationships have been derived which have been extrapolated to take account of the significantly longer period of wind data. By this means both the long term wave climate and the wave heights associated with storm conditions may be predicted for the more exposed wind sector. The method is relatively straightforward and capable of general application.

Numerical prediction of ocean waves in the North Atlantic for December, 1959

A severe storm of December 15–18, 1959, over the North Atlantic, covering great areas of ocean with high winds, was responsible for high seas which were measured by a ship-borne wave recorder on the OWS “Weather Reporter”, while proceeding from Northern Ireland to Station “J” at lat. 52 1/2°N, long. 20°W. The wave records were calibrated and analyzed for determination of significant wave heights and wave energy spectra. The present paper is an attempt to predict (for comparison) the wave conditions that would have been encountered by the moving ship from analysis of the oceanwide weather records and the use of a high-speed digital computer process for forecasting waves in moving, variable wind systems. The wave prediction technique is dependent on generalizations of emprical laws derived from observed wind-wave relationships. The proverbial non-uniformity of the latter makes possible several versions of supposedly best—fit empirical laws. Trial is made of two different generalizations, of which the second was found to yield predicted significant wave heights in fair agreement with the measurements over a period of several days. Further improvement, however, is possible and the forms of the empirical wind-wave generation laws, likely to be most nearly in agreement with the natural laws, are derived.