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This study examines the dependence of the computed drag coefficient on wind speed, stability, fetch, flux sampling problems, and method of calculation of the drag coefficient. The analysis is applied to data collected at a tower 2 km off the coast of Denmark during the Risc Air Sea Experiment (RASEX). Various flux sampling problems are evaluated to eliminate unreliable fluxes. Large drag coefficients are observed with weak large-scale flow. However, the value of the computed drag coefficient at weak wind speeds is sensitive to flux sampling problems and the method of calculation of the drag coefficient which might be a general characteristic of weak winds. The drag coefficient is significantly larger for short fetch conditions, particularly at strong wind speeds. IntroductionThe drag coefficient over the sea is thought to increase as the wind speed becomes weak. Recently, Wu [1994] has suggested that closely packed capillary waves associated with surface tension partly explain the large drag coefficients at weak winds observed by Geernaert et al. [1988] and Bradley et al. [1991]. Greenhut and Khalsa [1995] have observed a similar increase of the drag coefficient at low wind speeds. In addition to wind speed and surface tension the drag coefficient depends on a number of other factors. For a given wind speed the stress is expected to be greater with young developing waves and smaller with decaying waves [Kitaigorodskii, 1973; Nordeng, 1991; Geernaert et al., 1987, 1988; Donelan, 1990; Maat et al., 1991] even after accounting for built-in correlation associated with the usual method of relating the drag coefficient to wave age [Smith et al., 1992]. Young waves are steeper, leading to larger stress. Since the drag coefficient for a given wind speed is larger with young developing waves, the drag coefficient is expected to be larger with flow acceleration, as observed by Large and Pond [1981] and Smith [1980]. In fact, the stress may become very small or even reverse sign with significant deceleration implying small or negative drag coefficients [Smedman et al., 1994]. Unfortunately, during rapid acceleration the stress is nonstationary, and the calculated stress is sensitive to choice of averaging scales. The drag coefficient is also influenced by changing wind direction, fetch [Geernaert et al., 1988], water depth, and wave breaking [Banner, 1990]. Shoaling processes can cause changes of wave shape and wave breaking in shallow water [Freilich and Guza, 1984; Freilich et.al., 1990], leading to increased stress, while limited fetch can enhance the stress through wave growth. The choice of averaging length used to compute the flux and

This study addresses the relationship between thermal microfronts and coherent vortex structures in homogeneous turbulence. The turbulence is created by mean shear in a weakly stratified flow. The data set is generated by direct numerical simulation providing highly resolved instantaneous three-dimensional fields of fluctuating velocity and temperature (160 3 data points for each field). Vertically inclined large-scale horseshoe vortices develop due to stretching and rotation by the mean shear rate, as would also occur in neutrally stratified flow. In a homogeneous shear flow, the structures on the tilted plane are oriented both upward and downward with equal probability, and are referred to as "head-up" and "head-down" horseshoe eddies. Vorticity structures are sampled in those regions of the flow where the strongest coherent local temperature gradients occur. The sampled fields are composited. It is found that the microfronts are caused by the local outflow between the legs of the horseshoe eddies. A head-up eddy always forms a cold microfront (moving toward warmer fluid) and a head-down eddy forms a warm microfront. In most of the sampled cases, the two vortex structures occur in pairs, such that the head-down vortex always lies above the head-up vortex. Therefore, local shear layers with enhanced cross-stream vorticity form between the outflows of the structures. The strongest temperature gradients also occur at this location. Typical length, width, and thickness of a coherent vortex structure are found to be 1.4/, 1.4/, and 0.72/, respectively, where I is the integral length scale (based on the three-dimensional energy-density spectrum). The typical distance between two vortices forming a pair is about one integral length.

This study examines the influence of coherent structures and attendant microfronts on scaling laws. Toward this goal, we analyse atmospheric observations of turbulence collected 45 m above a flat surface during the Lammefjord Experiment in Denmark. These observations represent more than 40 hours of nearly stationary strong wind conditions and include more than 1600 samples of the main coherent structures. These samples occupy about 40% of the total record and explain the majority of the Reynolds stress.To study the dependence of the scaling laws on the choice of basis set, the time series of velocity fluctuations are decomposed into Fourier modes, the local Haar basis set and eigenvectors of the lagged covariance matrix. The three decompositions are compared by formulating joint projections. The decompositions are first applied to the samples of phased-locked coherent structures centred about eddy microfronts. The eigenvector decomposition is able to partially separate the small-scale variances due to the coherent eddy microfronts from that due to the small-scale structure with random phase. In the Fourier spectrum, both of these contributions to the variance appear together at the higher wavenumbers and their individual contributions cannot be separated. This effect is relatively minor for the scale distribution of energy but exerts an important influence on higher-moment statistics. Deviations from the −$\frac53$ scaling are observed to be slight and depend on choice of basis set.The microfronts strongly influence the higher-order statistics such as the sixth-order structure function traditionally used to estimate the energy transfer variance. The intermittency of fine-scale structure, energy transfer variance and dissipation are not completely characterized by random phase, as often assumed, but are partly associated with microfronts characterized by systematic phase with respect to the main transporting eddies. These conclusions are supported by both the higher-order structure function and the higher-order Haar transform.The Fourier and Haar spectra are also computed for the entire record. The peak of the Haar energy spectrum occurs at smaller scales than those of the Fourier spectrum. The Haar transform is local and emphasizes the width of the events. The Fourier spectrum peaks at the scale of the main periodicity, if it exists, which includes the spacing between the events.