Theoretical study and experimental verification of wind wave generation and evolution focus generally on ideal conditions of steady state and quiescent initial background, of which the ideal fetch-limited wind wave growth is an important benchmark. In nature, unsteady winds and swell presence are more common. Here, the observations of wind wave development in mixed seas under unsteady and quasi-steady wind forcing are presented. With reference to the ideal fetch-limited growth functions established under steady wind forcing in the absence of swell, the analysis shows that the wind-steadiness factor impacts wave growth. The wind wave variance in mixed sea is enhanced in both accelerating and decelerating phases of an unsteady wind event, with a larger enhancement in the accelerating phase than in the decelerating phase. Spatial and temporal wind wave measurements under similar environmental conditions are also compared; the quantifiable differences in the wave development are attributable to the wind-steadiness factor. Coupled with the empirical observation that the average wind stress is decreased in mixed sea, these results suggest that wind wave generation and development are more efficient in mixed sea than in wind sea. Possible causes include (i) oscillatory modulation of surface roughness increases air–sea exchanges, (ii) background surface motion reduces energy waste for cold start of wind wave generation from a quiescent state, and (iii) breaking of short waves redistributes wind input and allows more of the available wind power to be directed to the longer waves for their continuous growth.

In an earlier paper by Wang and Hwang, a wave steepness method was introduced to separate the wind sea and swell of the 1D wave spectrum without relying on external information, such as the wind speed. Later, the method was found to produce the unreasonable result of placing the swell–sea separation frequency higher than the wind sea peak frequency. Here, the following two factors causing the erratic performance are identified: (a) the wave steepness method defines the swell–sea separation frequency to be equal to the wind sea peak frequency with a wave age equal to one, and, (b) for more mature wave conditions, the peak frequency of the wave steepness function may not continue monotonic downshifting in high winds if the high-frequency portion of the wave spectrum has a spectral slope milder than −5. Conceptually, the swell–sea separation frequency should be placed between the swell and wind sea peak frequencies rather than at the wind sea peak frequency. Furthermore the wind sea wave age can vary over a considerable range, thus factor a above can lead to incorrect results. Also, because the slope of the wind sea equilibrium spectrum is typically close to −4, factor b becomes a serious restriction in more mature wave conditions. A spectrum integration method generalized from the wave steepness method is presented here for wind sea and swell separation of the 1D wave spectrum without requiring external information. The new spectrum integration method works very well over a wide range of wind wave development stages in the ocean.

[1] Wind stress is a key parameter for oceanic and atmospheric modeling, forecasting, and hydrodynamic studies. It is generally accepted that wind stress depends on the sea state. In particular, it has been shown that the presence of swell can modify both magnitude and direction of the wind stress. The presence of swell enhances momentum flux when swell propagates opposite to the wind direction and reduces it when it travels along the wind direction. However, those conclusions are mainly based on data acquired in low wind speed conditions and it is not clear to what extent an effect of swell persists at higher winds. Here simultaneous measurements of wind stress and waves, carried out in an area characterized by the occurrence of strong offshore winds with counter long-period swell, are presented and analyzed. The observations indicate that swell causes substantial changes to the wind stress at all observed wind conditions, including wind speeds as high as 20 ms À1 . It is believed that in low wind conditions swell increases drag by directly interacting with the air flow, whereas at higher winds, swell reduces drag by modifying the wind-sea-associated roughness.Citation: García-Nava, H., F. J. Ocampo-Torres, P. Osuna, and M. A. Donelan (2009), Wind stress in the presence of swell under moderate to strong wind conditions,

Directional wave spectra acquired in hurricane reconnaissance missions are compared with wind-wave spectral models. The comparison result is quantified with two indices of model–measurement spectral agreement. In the main region of hurricane coverage, the indices vary sinusoidally with the azimuth angle referenced to the hurricane heading while showing a weak dependence on the radial distance from the hurricane center. The measured spectra agree well with three models evaluated in the back and right quarters, and they are underdeveloped in the front and left quarters. The local wind and wave directions also show a weak radial dependence and sinusoidal variation along the azimuth. The wind and wave vectors are almost collinear in the back and right quarters; they diverge azimuthally and become almost perpendicular in the left quarter. The azimuthally cyclical correlation between the indices of spectral agreement and the wind-wave directional difference is well described by the sinusoidal variations. Also discussed is the wide range of the spectral slopes observed in both hurricane and nonhurricane field data. It is unlikely that the observed spectral slope variation is caused by Doppler frequency shift from background currents. No clear correlation is found between spectral slope and various wind and wave parameters. The result suggests that the spectral slope needs to be treated as a stochastic random variable. Complementing the existing wind-wave spectral models that prescribe a fixed spectral slope of either −4 or −5, a general spectral model with its spectral parameters accommodating a variable spectral slope is introduced.

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