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High-frequency wind measurements from Saildrone autonomous surface vehicles are used to calculate wind stress in the tropical east Pacific. Comparison between direct covariance (DC) and bulk wind stress estimates demonstrates very good agreement. Building on previous work that showed the bulk input data were reliable, our results lend credibility to the DC estimates. Wind flow distortion by Saildrones is comparable to or smaller than other platforms. Motion correction results in realistic wind spectra, albeit with signatures of swell-coherent wind fluctuations that may be unrealistically strong. Fractional differences between DC and bulk wind stress magnitude are largest at wind speeds below 4 m s−1. The size of this effect, however, depends on choice of stress direction assumptions. Past work has shown the importance of using current-relative (instead of Earth-relative) winds to achieve accurate wind stress magnitude. We show that it is also important for wind stress direction. Significance Statement We use data from Saildrone uncrewed oceanographic research vehicles to investigate the horizontal forces applied to the surface of the ocean by the action of the wind. We compare two methods to calculate the forces: one uses several simplifying assumptions, and the other makes fewer assumptions but is error prone if the data are incorrectly processed. The two methods agree well, suggesting that Saildrone vehicles are suitable for both methods and that the data processing methods work. Our results show that it is important to consider ocean currents, as well as winds, in order to achieve accurate magnitude and direction of the surface forces.

Direct covariance flux (DCF) measurements taken from floating platforms are contaminated by wave-induced platform motions that need to be removed before computation of the turbulent fluxes. Several correction algorithms have been developed and successfully applied in earlier studies from research vessels and, most recently, by the use of moored buoys. The validation of those correction algorithms has so far been limited to short-duration comparisons against other floating platforms. Although these comparisons show in general a good agreement, there is still a lack of a rigorous validation of the method, required to understand the strengths and weaknesses of the existing motion-correction algorithms. This paper attempts to provide such a validation by a comparison of flux estimates from two DCF systems, one mounted on a moored buoy and one on the Air–Sea Interaction Tower (ASIT) at the Martha’s Vineyard Coastal Observatory, Massachusetts. The ASIT was specifically designed to minimize flow distortion over a wide range of wind directions from the open ocean for flux measurements. The flow measurements from the buoy system are corrected for wave-induced platform motions before computation of the turbulent heat and momentum fluxes. Flux estimates and cospectra of the corrected buoy data are found to be in very good agreement with those obtained from the ASIT. The comparison is also used to optimize the filter constants used in the motion-correction algorithm. The quantitative agreement between the buoy data and the ASIT demonstrates that the DCF method is applicable for turbulence measurements from small moving platforms, such as buoys.

Obtaining accurate measurements of wave statistics from research vessels remains a challenge due to the platform motion. One principal correction is the removal of ship heave and Doppler effects from point measurements. Here, open-ocean wave measurements were collected using a laser altimeter, a Doppler radar microwave sensor, a radar-based system, and inertial measurement units. Multiple instruments were deployed to capture the low- and high-frequency sea surface displacements. Doppler and motion correction algorithms were applied to obtain a full 1D (0.035–1.3 ± 0.2 Hz) wave spectrum. The radar-based system combined with the laser altimeter provided the optimal low- and high-frequency combination, producing a frequency spectrum in the range from 0.035 to 1.2 Hz for cruising speeds ≤3 m s−1 with a spectral rolloff of f−4 Hz and noise floor of −20/−30 dB. While on station, the significant wave height estimates were comparable within 10%–15% among instrumentation. Discrepancies in the total energy and in the spectral shape between instruments arise when the ship is in motion. These differences can be quantified using the spectral behavior of the measurements, accounting for aliasing and Doppler corrections. The inertial sensors provided information on the amplitude of the ship’s modulation transfer function, which was estimated to be ~1.3 ± 0.2 while on station and increased while underway [2.1 at ship-over-ground (SOG) speed; 4.3 m s−1]. The correction scheme presented here is adequate for measurements collected at cruising speeds of 3 m s−1 or less. At speeds greater than 5 m s−1, the motion and Doppler corrections are not sufficient to correct the observed spectral degradation.

A surface mooring was deployed in the Gulf Stream for 15 months to investigate the role of air–sea interaction in mode water formation and other processes. The accuracies of the near-surface meteorological and oceanographic measurements are investigated. In addition, the impacts of these measurement errors on the estimation and study of the air–sea fluxes in the Gulf Stream are discussed. Pre- and postdeployment calibrations together with in situ comparison between shipboard and moored sensors supported the identification of biases due to sensor drifts, sensor electronics, and calibration errors. A postdeployment field study was used to further investigate the performance of the wind sensors. The use of redundant sensor sets not only supported the filling of data gaps but also allowed an examination of the contribution of random errors. Air–sea fluxes were also analyzed and computed from both Coupled Ocean–Atmosphere Response Experiment (COARE) bulk parameterization and using direct covariance measurements. The basic conclusion is that the surface buoy deployed in the Gulf Stream to support air–sea interaction research was successful, providing an improved 15-month record of surface meteorology, upper-ocean variability, and air–sea fluxes with known accuracies. At the same time, the coincident deployment of mean meteorological and turbulent flux sensors proved to be a successful strategy to certify the validity of the bulk formula fluxes over the midrange of wind speeds and to support further work to address the present shortcomings of the bulk formula methods at the low and high wind speeds.

The design of a surface mooring for deployment in the Gulf Stream in the Mid-Atlantic Bight is described. The authors' goals were to observe the surface meteorology; upper-ocean variability; and air–sea exchanges of heat, freshwater, and momentum in and near the Gulf Stream during two successive 1-yr deployments. Of particular interest was quantifying these air–sea fluxes during wintertime events that carry cold, dry air from the land over the Gulf Stream. Historical current data and information about the surface waves were used to guide the design of the surface mooring. The surface buoy provided the platform for both bulk meteorological sensors and a direct covariance flux system. Redundancy in the meteorological sensors proved to be a largely successful strategy to obtain complete time series. Oceanographic instrumentation was limited in size by considerations of drag; and two current meters, three temperature–salinity recorders, and 15 temperature recorders were deployed. Deployment from a single-screw vessel in the Gulf Stream required a controlled-drift stern first over the anchor sites. The first deployment lasted the planned full year. The second deployment ended after 3 months when the mooring was cut by unknown means at a depth of about 3000 m. The mooring was at times in the core of the Gulf Stream, and a peak surface current of over 2.7 m s−1 was observed. The 15-month records of surface meteorology and air–sea fluxes captured the seasonal variability as well as several cold-air outbreaks; the peak observed heat loss was in excess of 1400 W m−2.

Platform motion contaminates turbulence statistics measured in the surface layer over the ocean and therefore adds uncertainty to the understanding and parameterization of air–sea exchange. A modification to the platform motion–correction procedure of Edson et al. is presented that explicitly accounts for misalignment between anemometers and motion sensors. The method is applied to a high-resolution dataset, including four levels of turbulence within 20 m of the ocean surface, measured over deep ocean waves using the stable research platform R/P FLIP. The average error magnitude of the air–sea momentum flux (wind stress) from the four sensors during a 6-day period (10-m wind speed 2–14 m s−1) was 15% ± 1%, and varied systematically with measurement height. Motion and sensor-mounting offsets caused wind stress to be underestimated by 15% at 18.1 m, 13% at 13.8 m, and 11% at 8.7 m, and to be overestimated by 3% at 3.5 m. Sensor misalignment contributed to one-third of the correction to the wind stress. The motion correction reduced some measured artifacts in the wind that could otherwise be interpreted in terms of air–sea interaction, such as the angle between wind and wind stress vectors, while other features remained in the corrected wind, such as apparent upward momentum transfer from ocean to the atmosphere during low wind. These results demonstrate the complex interaction between motion and wind turbulence, and reinforce the necessity to measure and correct for platform motion. Finally, it is shown that the effects of motion on wind stress measured using R/P FLIP are much smaller than in situ measurements made using a conventional research ship.

This paper describes two methods for computing direct covariance fluxes from anemometers mounted on moving platforms at sea. These methods involve the use of either a strapped-down or gyro-stabilized system that are used to compute terms that correct for the 1) instantaneous tilt of the anemometer due to the pitch, roll, and heading variations of the platform; 2) angular velocities at the anemometer due to rotation of the platform about its local coordinate system axes; and 3) translational velocities of the platform with respect to a fixed frame of reference. The paper provides a comparison of fluxes computed with three strapped-down systems from two recent field experiments. These comparisons shows that the direct covariance fluxes are in good agreement with fluxes derived using the bulk aerodynamic method. Additional comparisons between the ship system and the research platform FLIP indicate that flow distortion systematically increases the momentum flux by 15%. Evidence suggests that this correction is appropriate for a commonly used class of research vessels. The application of corrections for both motion contamination and flow distortion results in direct covariance flux estimates with an uncertainty of approximately 10%‐20%.

Comparisons are made between surface wind stress measurements obtained by the inertial-dissipation and direct covariance methods on a stable offshore tower and by the inertial-dissipation and bulk methods on a ship. The shipboard inertial-dissipation friction velocity measurements agreed very well with both the tower inertialdissipation and direct covariance values, to within 62% in the mean and with a 10% or lower rms scatter. The inertial-dissipation determinations also exhibited less scatter than the tower direct covariance measurements. A detailed error analysis indicates that shipboard inertial-dissipation wind stress values can have an accuracy of better than 15% in near-neutral conditions, as compared to an accuracy of roughly 30% for the bulk method. The accuracy of shipboard inertial-dissipation values was shown to be equal to that of direct covariance measurements from a tower. Errors in inertial-dissipation wind stress values are most likely due primarily to deviations from the assumed balance between turbulent kinetic energy production and dissipation and to errors in determining the wind speed variance spectra. Errors in direct covariance measurements are most likely due primarily to finite time averaging and to flow distortion effects, unless great care is taken to minimize or correct for flow distortion. The high accuracy of inertial-dissipation wind stress values found in this study, combined with the well-known difficulties in shipboard direct covariance measurements due to platform motion and flow distortion, demonstrate that the inertial-dissipation method is the best option at present for determining the wind stress from a ship.

The NOAA Environmental Technology Laboratory air–sea interaction group and collaborators at the Woods Hole Oceanographic Institution have developed a seagoing measurement system suitable for mounting aboard ships. During its development, it was deployed on three different ships and recently completed three cruises in the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment as well as two cruises off the west coast of the United States. The system includes tower-mounted micrometeorological sensors for direct covariance flux measurements and a variety of remote sensors for profiling winds, temperature, moisture, and turbulence. A sonic anemometer/thermometer and a fast-response infrared hygrometer are used for turbulent fluxes. Winds are obtained from a stabilized Doppler radar (wind profiler) and a Doppler sodar. Returned power and Doppler width from these systems are used to deduce profiles of small-scale turbulence. A lidar ceilometer and a microwave radiometer are used ...

The response of a Kaijo Denki DAT 300 ultrasonic anemometer-thermometer is analyzed with respect to temperature and vertical velocity. The effects of the emitting-receiving cycle of the transducer array on w, T, and CowT spectra are considered. The resulting relations are used to interpret temperature spectra obtained during the HEXMAX (Humidity Exchange over the Sea, Main Experiment) measuring campaign.