A semiempirical determination of the spectral dependence of the energy dissipation due to surface wave breaking is presented and then used to propose a model for the spectral dependence of the breaking strength parameter b, defined in the O. M. Phillips's statistical formulation of wave breaking dynamics. The determination of the spectral dissipation is based on closing the radiative transport equation for fetch-limited waves, measured in the Gulf of Tehuantepec Experiment, by using the measured evolution of the directional spectra with fetch, computations of the four-wave resonant interactions, and three models of the wind input source function. The spectral dependence of the breaking strength is determined from the Kleiss and Melville measurements of the breaking statistics and the semiempirical spectral energy dissipation, resulting in ö = b(k, Cplu^), where k is the wavenumber and the parametric dependence is on the wave age, Cplu¡^. Guided by these semiempirical results, a model for b{k, Cplu^,) is proposed that uses laboratory data from a variety of sources, which can be represented by i = a{S -So)", where 5 is a measure of the wave slope at breaking, a is a constant, 5o is a threshold slope for breaking, and 2.5 < n <3 is a power law consistent with inertial wave dissipation scaling and laboratory measurements. The relationship between b{S) in the laboratory and b{k) in the field is based on the relationship between the saturation and mean square slope of the wave field. The results are discussed in the context of wind wave modeling and improved measurements of breaking in the field.

Breaking waves play an important role in air–sea interaction, enhancing momentum flux from the atmosphere to the ocean, dissipating wave energy that is then available for turbulent mixing, injecting aerosols and sea spray into the atmosphere, and affecting air–sea gas transfer due to air entrainment. In this paper observations are presented of the occurrence of breaking waves under conditions of strong winds (10–25 m s−1) and fetch-limited seas (0–500 km) in the Gulf of Tehuantepec Experiment (GOTEX) in 2004. An airborne nadir-looking video camera, along with a global positioning system (GPS) and inertial motion unit (IMU), provided digital videos of the breaking sea surface and position in an earth frame. In particular, the authors present observations of Λ(c), which is the distribution of breaking wave crest lengths per unit sea surface area, per unit increment in velocity c or scalar speed c, first introduced by O. M. Phillips. In another paper, the authors discuss the effect of processing methodology on the resulting shape of the Λ(c) distribution. In this paper, the elemental method of measuring breaking crests is used to investigate the Λ(c) distributions under a variety of wind and wave conditions. The integral and the first two moments of the Λ(c) distributions are highly correlated with the active breaking rate and the active whitecap coverage. The computation of whitecap coverage yields a larger observational dataset from which the variability of whitecap coverage with wind speed, friction velocity, wave age, and wave slope is presented and compared to previous observations. The dependence of the active breaking rate on the spectral peak steepness is in agreement with previous studies. Dimensional analysis of Λ(c) indicates that scaling with friction velocity and gravity, as in the classical fetch relations, collapses the breaking distributions more effectively than scaling with dominant wave parameters. Significant wave breaking is observed at speeds near the spectral peak in young seas only, consistent with previous studies. The fourth and fifth moments of Λ(c) are related to the flux of momentum transferred by breaking waves to the underlying water and the rate of wave energy dissipation, respectively. The maximum in the fourth moment occurs at breaking speeds of 5–5.5 m s−1, and the maximum in the fifth moment occurs at 5.8–6.8 m s−1, apparently independent of wave age. However, when nondimensionalized by the phase speed at the peak of the local wave spectrum cp, the maxima in the nondimensionalized fourth and fifth moments show a decreasing trend with wave age, obtaining the maxima at dimensionless speeds c/cp near unity at smaller wave ages and moving to lower dimensionless speeds c/cp ≪ 1 at larger wave ages. The angular dependence of Λ(c) is predominantly unimodal and better aligned with the wind direction than the dominant wave direction. However, the directional distribution of Λ(c) is broadest for small c and often exhibits a bimodal structure for slow breaking speeds under developing seas. An asymmetry in the directional distribution is also observed for moderately developed seas. Observations are compared to the Phillips model for Λ(c) in the equilibrium range of the wave spectrum. Although the ensemble of Λ(c) distributions appears consistent with a c−6 function, the distributions are not described by a constant power-law exponent. However, the Λ(c) observations are described well by the Rayleigh distribution for slow and intermediate speeds, yet fall above the Rayleigh distribution for the fastest breaking speeds. From the Rayleigh description, it is found that the dimensionless width of the Λ(c) distribution increases weakly with dimensionless fetch, s/u*e = 1.69χ0.06, where s is the Rayleigh parameter, u*e is the effective friction velocity, and the dimensionless fetch is a function of the fetch X and gravitational acceleration g. The nondimensionalized total length of breaking per unit sea surface area is found to decrease with dimensionless fetch for intermediate to fully developed seas, , where A is the total length of breaking crests per unit sea surface area.

Visible sea surface images are analyzed to determine the distribution of the average length of breaking crests per unit sea surface area per unit speed increment Λ(c). The Λ(c) distribution offers a scale-dependent description of wave breaking that is valuable for understanding wave energy dissipation, momentum flux from the wave field to the surface currents, and air–sea fluxes of gas and sea salt aerosols. Two independent processing techniques for determining Λ(c) from video images are implemented. In particular, the importance of the definition of the velocity of a breaking event is considered, as a single value, as a function of time, or as a function of space and time. The velocity can furthermore be defined as the full translational velocity or as the velocity normal to the breaking front. The Λ(c) distributions resulting from various definitions of velocity, sensitivity to thresholds, observational resolution, and the effect of surface currents and long wave orbital velocity are presented. The appropriateness and limitations of the comparison of the first moment of Λ(c) with the breaking rate are discussed. Two previous field observations of Λ(c) give qualitatively different results: Melville and Matusov found an exponential form for Λ(c), whereas Gemmrich et al. obtained a function that peaks at intermediate speeds and is up to an order of magnitude higher than that of Melville and Matusov. Both results can qualitatively be reproduced using the current dataset by employing the definitions of breaking velocity used in the previous studies. The authors argue that the current optimal interpretation of breaking speed resolves the breaking velocity as a function of both space and time and considers the velocity orthogonal to the breaking crest.

Ceilometer observations of cloud cover are an important component of the automated weather observation network. However, the accuracy of its measurements of cloud amount is impacted by the limited vertical range and areal extent of its observations. A multiyear collocated dataset of observations from a laser ceilometer, a total sky imager (TSI), and a micropulse lidar (MPL) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility is used to simulate the observations of operational ceilometers and to analyze the magnitude of the errors associated with ceilometer-based observations of cloud amount. The limited areal coverage of ceilometers results in error when skies are heterogeneous, but these errors are small compared to those caused by the limited vertical range: observations of clear sky or few clouds are often in error as the instrument cannot detect the presence of upper-level clouds. The varying quantities of upper-level clouds mean that errors are diurnally and seasonally dependent, with the greatest error at the SGP site happening in the morning and summer, respectively. Overall, the spatial homogeneity and low base of stratus clouds means that ceilometer-based observations of overcast skies are the most accurate, with a root-mean-square error of cloud fraction in overcast conditions an order of magnitude lower than for the dataset as a whole.

A long-term climatology of classified cloud types has been generated for 13 years (1997–2009) over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for seven cloud categories: low clouds, congestus, deep convection, altocumulus, altostratus, cirrostratus/anvil, and cirrus. The classification was based on the cloud macrophysical quantities of cloud top, cloud base, and physical thickness of cloud layers, as measured by active sensors such as the millimeter-wavelength cloud radar (MMCR) and micropulse lidar (MPL). Climate variability of cloud characteristics has been examined using the 13-yr cloud-type retrieval. Low clouds and cirrus showed distinct diurnal and seasonal cycles. Total cloud occurrence followed the variation of low clouds, with a diurnal peak in early afternoon and a seasonal maximum in late winter. Additionally, further work has been done to identify fair-weather shallow cumulus (FWSC) events for 9 years (2000–08). Periods containing FWSC, a subcategory of clouds classified as low clouds, were produced using cloud fraction information from a total-sky imager and ceilometer. The identified FWSC periods in our study show good agreement with manually identified FWSC, missing only 6 cases out of 70 possible events during the spring to summer seasons (May–August).