Triple collocation is an established technique for retrieving linear calibration coefficients and observation error variances of a physical quantity observed simultaneously by three different observation systems. The formalism is extended to an arbitrary number of systems, and representativeness errors and associated cross‐covariances are included in a natural way. It is applied to quadruple collocations of ocean surface vector winds from two scatterometers (ASCAT‐A, ASCAT‐B, or ScatSat), buoy measurements, and NWP model forecasts. There are 15 possible sets of quadruple collocation equations, 12 of which are solvable for the essential variables (calibration coefficients, observation error variances, and common variance) as well as two additional error covariances, each set leading to a different solution. The quadruple collocation equations by themselves give little information on the representativeness errors involved; these have to be estimated using other methods. The spreading in the solutions is a measure of the accuracy of the underlying error model. Variation of the scale at which the spatial variances are evaluated yields an optimal scale of 100–200 km. From triple collocation subsets the error in the scatterometer error standard deviations is found to be 0.03–0.05 m s⁻¹, more than expected on statistical grounds. A more precise determination requires an error model that better describes the data error properties.

The accuracy and consistency of a quintuple collocation analysis of ocean surface vector winds from buoys, scatterometers, and NWP forecasts is established. A new solution method is introduced for the general multiple collocation problem formulated in terms of covariance equations. By a logarithmic transformation, the covariance equations reduce to ordinary linear equations that can be handled using standard methods. The method can be applied to each determined or overdetermined subset of the covariance equations. Representativeness errors are estimated from differences in spatial variances. The results are in good agreement with those from quadruple collocation analyses reported elsewhere. The geometric mean of all solutions from determined subsets of the covariance equations equals the least-squares solution of all equations. The accuracy of the solutions is estimated from synthetic data sets with random Gaussian errors that are constructed from the buoy data using the values of the calibration coefficients and error variances from the quintuple collocation analysis. For the calibration coefficients, the spread in the models is smaller than the accuracy, but for the observation error variances, the spread and the accuracy are about equal only for representativeness errors evaluated at a scale of 200 km for $u$ and 100 km for $v$. Some average error covariances differ significantly from zero, indicating weak inconsistencies in the underlying error model. Possible causes for this are discussed. With a data set of 2454 collocations, the accuracy in the observation error standard deviation is 0.02 to 0.03 m/s at the one-sigma level for all observing systems.

Kinetic energy variance as a function of spatial scale for wind fields is commonly estimated either using second-order structure functions (in the spatial domain) or by spectral analysis (in the frequency domain). Both techniques give an order-of-magnitude estimate. More accurate estimates are given by a statistic called spatial variance. Spatial variances have a clear interpretation and are tolerant for missing data. They can be related to second-order structure functions, both for discrete and continuous data. Spatial variances can also be Fourier transformed to yield a relation with spectra. The flexibility of spatial variances is used to study various sampling strategies, and to compare them with second-order structure functions and spectral variances. It is shown that the spectral sampling strategy is not seriously biased to calm conditions for scatterometer ocean surface vector winds. When the second-order structure function behaves like , its ratio with the spatial variance equals . Ocean surface winds in the tropics have between 2/3 and 1, so one-sixth to one-fifth of the second-order structure function value is a good proxy for the cumulative variance.

The direction of the energy cascade in the mesoscales of atmospheric turbulence is investigated using near‐surface winds over the tropical Pacific measured by satellite scatterometers SeaWinds (QuikSCAT) and ASCAT (MetOp‐A). The tropical Pacific was subdivided into nine regions, classified as rainy or dry. Longitudinal third‐order along‐track structure functions and skewness were calculated as a function of separation for each region and month during the period November 2008 to October 2009. We find that the results support both downscale and upscale interpretations, depending on region and month. The results indicate that normally energy cascades downscale, but cascades upscale over the cold tongue in the cold season and over the west Pacific in summer months. An explanation is offered based on the heating or cooling of the air by the underlying sea surface temperature. It is also found that the signature of intermittent small‐scale (<100 km) events could be identified in graphs of , implying that this diagnostic may be useful in the studies of tropical disturbances.

Vortex streets formed in the stratocumulus‐capped wake of mountainous islands are the atmospheric analogues of the classic Kármán vortex street observed in laboratory flows past bluff bodies. The quantitative analysis of these mesoscale unsteady atmospheric flows has been hampered by the lack of satellite wind retrievals of sufficiently high spatial and temporal resolution. Taking advantage of the cutting‐edge Advanced Baseline Imager, we derived kilometer‐scale cloud‐motion winds at 5‐min frequency for a vortex street in the lee of Guadalupe Island imaged by Geostationary Operational Environmental Satellite‐16. Combined with Moderate Resolution Imaging Spectroradiometer data, the geostationary imagery also provided accurate stereo cloud‐top heights. The time series of geostationary winds, supplemented with snapshots of ocean surface winds from the Advanced Scatterometer, allowed us to capture the wake oscillations and measure vortex shedding dynamics. The retrievals revealed a markedly asymmetric vortex decay, with cyclonic eddies having larger peak vorticities than anticyclonic eddies at the same downstream location. Drawing on the vast knowledge accumulated about laboratory bluff body flows, we argue that the asymmetric island wake arises from the combined effects of Earth's rotation and Guadalupe's nonaxisymmetric shape resembling an inclined flat plate at low angle of attack. However, numerical simulations will need to establish whether or not the selective destabilization of the shallow atmospheric anticyclonic eddies is caused by the same mechanisms that destabilize the deep columnar anticyclones of laboratory flows, such as three‐dimensional vertical perturbations due to centrifugal or elliptical instabilities.