1. Introduction
Over the past decade, there has been renewed interest in air–sea fluxes in the high wind regime. Here, we define as “high” those winds with speeds of over 20 m s−1, corresponding roughly to Beaufort force numbers 9 and over. This regime has long been distinguished by mariners by the presence of breaking waves and high concentrations of sea spray in the marine atmospheric boundary layer. Scientifically, this regime is of interest, in that high wind fluxes play a controlling role in the development and maintenance of tropical cyclones. High winds also dominate the high-latitude regions, where poor knowledge of surface fluxes is a key limiting factor in our understanding of global budgets of heat and carbon, inter alia (Bourassa et al. 2013).
In strong wind conditions, the interface is dominated by breaking waves, entrained air, ejected droplets, and spume lifted or sheared off the crests of steep waves. The significance of wave breaking in affecting both sides of the interface has been demonstrated by laboratory studies and numerical models (Banner and Melville 1976; Reul et al. 1999; Belcher and Hunt 1998; Makin 1998) on the air side and by field measurements (e.g., Terray et al. 1996; Gemmrich and Farmer 2004) on the water side.
Fairall et al. (2009) recently summarized the air–sea exchange estimates from three field-based air–sea interaction groups, representing tens of thousands of hours of data collected over the past 15 years. There is a remarkable consistency in the mean bulk relations of the three groups for wind speeds between 5 and 15 m s−1 (their Fig. 5): the mean drag coefficient increases roughly linearly with wind speed, while the bulk coefficients for latent and sensible heat (the Dalton and Stanton numbers, respectively) are constant. At higher wind speeds, the amount of data drops significantly with very few points, representing a few isolated events, at wind speeds above 20 m s−1.
Several papers published in the last decade support a fundamental change in behavior of the bulk coefficients at higher wind speeds. Powell et al. (2003), estimating the drag coefficient using an extensive set of GPS dropsonde observations from many years of hurricane flights, found the drag coefficient to level off at high winds (>32 m s−1), and then decrease for winds above 40 m s−1. Donelan et al. (2004) in a controlled laboratory study found a leveling off of the drag coefficient at high winds, in their case over 33 m s−1. Finally, the low-level aircraft data of French et al. (2007), collected in several hurricanes, indicated a flattening of the drag coefficient curve before 30 m s−1.
Likewise, the Dalton number has been predicted to increase at higher wind speeds due to the effect of sea spray (Andreas 1992). While this has not been observed in field data to date (see, e.g., Drennan et al. 2007; Sahlée et al. 2012), it cannot be ruled out at higher winds, as per the model predictions of Bao et al. (2011).
The present dearth of high wind speed measurements is related both to the relative rarity of winds over 20 m s−1 and to the lack of suitable platforms from which to make such measurements. Waves in the vicinity of coastal towers tend to be strongly modified by both shoaling and refraction in these conditions, while ship motion is greatly amplified in large breaking waves. The Air–Sea Interaction Spar (ASIS) buoy (Graber et al. 2000) has survived seas of over 7-m significant height, Hs (Knobles et al. 2008), but it is not designed for extended deployments in these conditions. Here, we define Hs as 4 times the standard deviation of surface elevation.
Recently, we designed and built a platform specifically for extended surface deployments in extreme wave environments. The platform would be capable of high-resolution measurements of direct (i.e., via eddy correlation) air–sea turbulent fluxes of momentum, sensible heat, latent heat and carbon dioxide, mean meteorology, surface waves, and mean upper-ocean characteristics. In designing the platform, three criteria were initially established. The first was the durability of the platform in high sea states. This includes the capability of unattended operation for one year, and survivability in a high wind, high sea-state environment. Following a survey of existing platforms, we decided to base the design of the new Extreme Air–Sea Interaction (EASI) buoy on that of the Navy Oceanographic Meteorological Automatic Device (NOMAD) buoy designed in the 1940s for navy use (Timpe and van de Voorde 1995). The 6-m NOMAD buoy is currently used by the U.S. National Data Buoy Center (NDBC) for most of its open-ocean deployments. The NOMAD is also used by the Canadian Marine Environmental Data Service (MEDS). The ship-hull-shaped NOMAD buoy (Fig. 1) has proven capabilities to survive the rough wintertime conditions of the North Pacific and North Atlantic.
(left) Photograph of EASI (foreground) and ASIS buoys taken shortly after deployment during ITOP. The 60-m surface tether connecting ASIS to EASI is clearly seen. (right) Close-up of EASI showing meteorological instruments. Bow is to the left.
Citation: Journal of Atmospheric and Oceanic Technology 31, 6; 10.1175/JTECH-D-13-00201.1
The second criterion was minimal flow distortion. There has been considerable attention paid to the effects of flow distortion on meteorological measurements (e.g., Oost et al. 1994; Dupuis et al. 2003). Flow distortion affects both the mean and turbulent components of the flow field, and can have a significant effect on direct (eddy correlation) turbulent fluxes, particularly that of momentum (Pedreros et al. 2003). This second criterion led to a redesign of the buoy superstructure from that used by NDBC and MEDS. Both these agencies include an array of solar panels mounted on a ~1-m mast on the forward deck. While this configuration allows for the use of rechargeable batteries, the flow distortion around the array was estimated to result in unacceptable errors in the turbulent flux measurements, which are not made on the NDBC or MEDS platforms. Hence, the solar panels were eliminated from the present design. This was also thought to reduce the risk of vandalism. We further discuss the power system of the EASI buoy below. The third criterion was the capability to safely deploy the buoy in rough seas. This last criterion was eventually dropped for practical reasons: no major “over the side” ship operations are possible in high sea states.
Two of the new EASI buoys were recently deployed off Taiwan as part of the Impact of Typhoons on the Ocean in the Pacific (ITOP) experiment. The seas east of Taiwan are known to be a particularly active region for tropical cyclone development (Pun et al. 2011). During ITOP three typhoons and one tropical storm passed over or near each of the buoys. Here, we describe the design of buoys, as well as their performance in sea states as high as 10-m significant wave height.
2. Research platform
As discussed above, the EASI buoy hull is that of the original NOMAD buoy, which has a ship-hull shape with dimensions 6 m long × 3 m wide × 3 m high. The EASI exterior hull and deck are made of a 13-mm-thick aluminum plate with an overall tare weight of 3900 kg. The interior contains four compartments separated by 10-mm-thick bulkheads. The bulkheads are fully watertight with the exception of two 100-mm-diameter openings near the top of each bulkhead. These channels, used to pass cables between compartments, are effectively sealed by potting the cables in Roxtec frames and sealing modules. A false floor in each compartment allows for the addition of lead ballast to ensure proper trim of the buoy. Six 225-kg lead ingots were also bolted onto the keel of EASI.
The compartments are used for the electronics, data, and power systems of the buoys. Given the extreme nature of the expected environmental conditions, two fully isolated and redundant power/data/sensor systems were used on each buoy. On each buoy, one data acquisition system was the custom personal computer (PC)-based system developed for use on the University of Miami ASIS buoy. The other was a Campbell Scientific CR3000 micrologger. Summary data, including position, were transmitted back to shore in near–real time over both ARGOS and Iridium satellites. With the decision to move away from rechargeable batteries, several alternative power arrangements were considered. Cegasa air alkaline batteries were tested, but they delivered only about one-third of the expected power, likely due to limited air exchange. Although each pair of compartments was vented to the exterior with a 0.7-m-high, 50-mm-diameter inverse-U-shaped vent fitted with a ball valve, air exchange with the exterior was passive, relying on pumping from the moving buoy. The final decision was made to use custom packs of D-cell alkaline batteries wired to produce a 15-V output. The packs were installed in custom tray units mounted in each compartment.
To dispense with (or minimize) guy wires and exposed cables, the EASI masts were made from flanged pipe segments. The upper two-thirds portion of each tall mast was hinged to the lower one-third portion, allowing the upper portion to be supported horizontally on the deck for setup. This arrangement allows instruments to be worked on from the deck fairly easily with the masts down. It also permits deployment of EASI through a large A-frame, again with masts down. The total height of the tall masts was 3.5 m above the deck. The highest instruments, sonic anemometers mounted at the top of the tall masts, were 5.4 m above mean sea level. Cables were strung inside the pipe masts, and passed directly into the interior through holes in the deck located within flanged pipe base segments welded onto the deck. Rubber gaskets were used between mating flanges, and Roxtecs located below the deck ensured a water-tight seal in the event of a mast failure.
EASI uses two fully duplicate mast pairs, one fore and one aft, with each pair connected to independent power and data systems. The instrument suite is summarized in Table 1. The tall mast of each pair was mainly dedicated to turbulence measurements, the other to mean parameters. The turbulence sensor suite consisted of a Gill 1012-R2A sonic anemometer (or in one case, a Gill WindMaster), a LI-COR infrared gas analyzer (IRGA), and a Compact Lightweight Aerosol Spectrometer Probe (CLASP; Norris et al. 2008), with a Rotronic MP101A-T7 temperature and relative humidity (RH) sensor mounted nearby. One turbulence suite on each buoy included a standard open-path LI-COR LI-7500. Given previous experience of poor sensor performance in saturated environments (cf. Sahlée et al. 2012), the other suite on each buoy included a closed-path IRGA. On one buoy this was a LI-7200; on the other a LI-7500 was modified for closed-path operation as described in Sahlée and Drennan (2009).
Meteorological and oceanographic instruments installed on EASI-N (N) and EASI-S (S) during the ITOP campaign. Two CLASP units were also deployed on each EASI.
The Rotronic MP101A-T7 temperature and relative humidity sensors were mounted on R. M. Young radiation shields. Several of the shields were modified by sealing adjacent plates with room-temperature vulcanizing silicone (RTV) so as to prevent spray from wetting the sensor in high winds. All plates on the windward side of the shield were sealed. While this significantly reduced airflow to the sensor, leaving measurements useless at low winds, it was thought the large vertical motions of the platform at high winds (waves) would provide sufficient ventilation while eliminating the sea spray. Sensors in standard (unmodified) shields would be used in lower wind conditions.
On each buoy one turbulence suite was supplemented with a K-Gill anemometer. The K-Gill is a vintage 1980s sensor that measures two components of the wind in a vertical plane using two Gill propellers with carbon-fiber blades mounted at ±45° from the horizontal (Katsaros et al. 1993). The K-Gill was deployed here out of concerns for the reliability of sonic anemometers in a rain- or spray-dominated environment (see Fig. 9 of Eckman et al. 2007). The turbulence suite was designed to measure the eddy correlation fluxes of momentum, sensible heat (via the sonic temperature signal; see Drennan and Shay 2006), latent heat, carbon dioxide, and aerosols.
The sensor suite on the “mean” mast of each pair consisted of an R. M. Young Marine Wind Monitor (rear mast only), a Setra model 278 barometer, an Eppley Precision Spectral Pyranometer (PSP), and an Eppley Precision Infrared Radiometer (PIR). On each buoy, one of the Setra barometers directly sensed the exterior pressure with an aft-facing port. To alleviate concerns of possible high wind Bernoulli effects on this sensor, the second barometer measured the EASI interior pressure, relying on the EASI vents to achieve equilibrium with the exterior. The measurements from the two systems generally differed by less than 0.4 hPa—well within the limits of calibration. Finally, an arm on the rear mean mast on each buoy held a Carmanah M704 marine lantern.
For water-side measurements, EASI is fitted with a 24-cm-diameter flanged well protruding through the hull and deck, which is designed to hold a downward-looking acoustic Doppler current profiler (ADCP). While an ADCP was not deployed from EASI during ITOP, several thermistors were attached to the well to measure water temperature near the surface (1 m below the mean surface). A hull-mounted sensor was also deployed. In addition, a dozen thermistors of various designs (Hugrun Seamon mini; Wadar TL; Brancker TR-1000; RBR TR-1050, TDO-2050, and TDR-2050) were deployed in the top 200 m along the mooring line, the design of which is discussed below. Some of the thermistors included pressure sensors, which allowed for the depth to be calculated; others included dissolved oxygen. All thermistors were cross calibrated in controlled thermal baths at the Rosenstiel School of Marine and Atmospheric Science (RSMAS) prior to the experiment.
The mooring design is critical to the durability of any surface mooring, especially in high sea states. Here, we used an inverse-catenary-style mooring designed for full ocean depth. The mooring consisted of (from the top): 27 m of 1 1/2-in. (4 cm) galvanized stud link chain attached to (and isolated from) the stainless steel EASI yoke and serving primarily as ballast (764 kg); 2000 m of jacketed wire rope (1.3-cm outer diameter); 1850 m of 2.5-cm-diameter braided nylon rope; 3125 m of 2.8-cm-diameter Sampson Ultra Blue eight-braid polypropylene rope (positively buoyant); 52 Benthos 2040-17V glass flotation spheres mounted on 9.5-cm galvanized chain; dual ORE model 8242XS acoustic releases; 5 m of 9.5-cm galvanized chain; a 30-m section of 2.5-cm nylon (acting as a shock absorber for the anchor launch); 5 m of 9.5-cm galvanized chain; and terminating in a 3100-kg anchor. The total mooring length of 7050 m, designed for a depth of 5600 m, allowed for a scope of 1.26.
3. ITOP experiment
The ITOP experiment took place during August–November 2010 in the Philippine Sea, east of Taiwan. The purpose of the experiment, as per the name, is to investigate the impact of tropical cyclones on the ocean, including the feedbacks between the ocean, atmosphere, and surface waves. The overall experiment included two aircraft [a U.S. Air Force C-130 out of Guam, and the Taiwanese Dropwinde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) Astra], several ships [the Research Vessel (R/V) Roger Revelle and the R/V Ocean Researchers 1–3], a variety of floats and buoys, as well as significant satellite and modeling components. Here, we focus on the two EASI buoys deployed in early August from the R/V Roger Revelle. The role of the EASI buoy deployment within ITOP was to measure mean lower-atmospheric and upper-oceanic parameters, along with surface waves and air–sea fluxes of momentum and energy.
The two EASI buoys, designated North and South (EASI-N and EASI-S, respectively), were deployed at 21.2°N, 126.8°E (5450-m depth) and 19.6°N, 127.3°E (5500 m), respectively (see Fig. 2). The buoys were deployed on 6 and 4 August [year days (YD) 218 and 216], respectively, with sufficient power and disk capacity for an expected 100-day duration. All data on the custom data acquisition system were sampled at 20 Hz. Because of storage limitations, turbulence and wave and motion data on the Campbell system were recorded at 5 Hz; other Campbell sensors were recorded every 60 s. Data were subsequently analyzed in 30-min blocks. Because of heavy weather encountered during the scheduled recovery cruise (which coincided with Typhoon Chaba, see below), the buoys were not recovered until March 2011. Data collection on the buoys ended on 13 December and 22 November, respectively. Below we use the term deployment period to refer to the time of data collection.
Positions of EASI-N and EASI-S moorings during 2010 ITOP experiment. The tracks of Tropical Storm Dianmu (005W, 5–12 Aug), Typhoon Fanapi (012W, 13–20 Sep), Super Typhoon Megi (015W, 11–24 Oct), and Typhoon Chaba (016W, 20–30 October) are also shown. The storm-track color indicates wind speed as estimated from the Joint Typhoon Warning Center, while the dots indicate 0000 UTC positions.
Citation: Journal of Atmospheric and Oceanic Technology 31, 6; 10.1175/JTECH-D-13-00201.1
Attached to each EASI buoy with a 60-m surface tether was an ASIS buoy. The primary function of the ASIS buoys was to measure surface waves, using an array of capacitance wave wires. See Pettersson et al. (2003) for a description of the array and subsequent processing. The outer perimeter wires were extended 76 cm over previous ASIS deployments to reduce the overtopping of wave staffs during high wave conditions. While this reduced the problem, some wave overtopping did occur. Such cases were corrected on a wave-by-wave basis using the cubic spline routine described in Sahlée et al. (2012). ASIS data were sampled at 20 Hz and analyzed in blocks of 30 min.
Time series data from EASI-N (black, blue) and EASI-S (green) during ITOP experiment. Shown are (a) barometric pressure, (b) 10-m neutral wind speed, (c) downwelling SW, (d) atmospheric and near-surface water (blue) temperatures, and (e) significant wave height. The near passages of Tropical Storm Dianmu (YD 218–221), Typhoons Fanapi (YD 258–262) and Chaba (YD 299–301), and Super Typhoon Megi (YD 289–290) are indicated in (e).
Citation: Journal of Atmospheric and Oceanic Technology 31, 6; 10.1175/JTECH-D-13-00201.1
4. Performance of EASI during ITOP
The performance of EASI as a platform will be evaluated on several aspects. At the most basic level, the mechanical system components survived the high winds and sea states associated with several typhoons: all masts remained upright and there was no evidence of any water leakage in the interior compartments. The only significant mechanical failures occurred at the tethers linking the EASI and ASIS buoys. Both failed during the high wave conditions of either Typhoons Fanapi (North mooring, YD 260.7) or Megi (South mooring, YD 289.7). Just before the break on EASI North, surge accelerations on ASIS reached 0.5 g due to the snap loading of the tether as EASI crested a wave and accelerated down the rear face. The ASIS buoys are not an integral part of the EASI design, but it is clear that if ASIS and EASI are to be deployed together in the future, a shock-absorbing tether must be used. The two ASIS buoys, each equipped with multiple satellite beacons, were recovered by the R/V Revelle on YD 287 (ASIS-N) and YD 295 (ASIS-S).
The standard deviation of pitch and roll of EASI as a function of wind speed are plotted in Figs. 4a and 4b, respectively. Quadratic fits to the data explain 78% and 76% of the variance, respectively. It is clear that while EASI has considerable motion in both pitch and roll at low winds (very evident when on board), the standard deviation of pitch rarely exceeded 5° (only during 12 runs, with a maximum of 5.2°), while that of roll exceeded 4° during only 3 runs (maximum 4.1°). Significant wave height does not explain significantly more variance in std(pitch) or std(roll) (Figs. 4c and 4d), and the quadratic fits are questionable at high wave heights. Equivalent data from ASIS-N are also plotted for the period when ASIS was attached to EASI. The motion of ASIS in pitch and roll is roughly one-third that of EASI, consistent with the numbers reported by Graber et al. (2000). ASIS was designed specifically for stability in pitch and roll, while EASI is expected to more closely follow the surface.
Standard deviations of 30 min of (a) pitch and (b) roll vs 10-m neutral wind speed measured on EASI-N during ITOP. Motion data are from EASI (blue) and ASIS (red), the latter shown only for the period when ASIS and EASI were attached. The curves represent the best quadratic fit to the EASI data. (c),(d) As in (a) and (b), but plotted against significant wave height.
Citation: Journal of Atmospheric and Oceanic Technology 31, 6; 10.1175/JTECH-D-13-00201.1
In Fig. 5, we plot time series of the main motion components (heave, surge, sway, pitch, and roll), as well as the surface elevation. The 100-s time series, from Typhoon Chaba (YD 300, after 0610 UTC), are some of the roughest conditions experienced during ITOP. During the 30-min period of the run, U5.4 = 20.4 m s−1 and Hs = 8 m. Using (2), the 10-m neutral wind speed is U10N = 21.7 m s−1. Here, the standard deviations of pitch and roll are 5.17° and 3.86°, respectively. Maximum instantaneous pitch and roll angles of 27.9° and 24.8° were recorded, both during the passage of a single 15-m wave. The trough-to-trough wavelength was λ = 202 m, giving ak = a(2π/λ) = 0.23, consistent with the recorded instantaneous tilt angles. Here a is half the peak-to-trough height. These pitch and roll values were close to the maximum recorded during the experiment. Maximum horizontal acceleration during the wave passage reached 8.27 m s−2, or 0.86 g, well in excess of the limits proposed by Longuet-Higgins (1985). It is therefore likely that the wave was breaking.
Time series of (a) surface elevation, (b) heave with g removed, (c) surge, (d) sway, (e) pitch, and (f) roll measured from the motion package on EASI-N for the 100 s starting at 0610 UTC 27 Oct 2010 (YD 300.26) during Typhoon Chaba. The mean wind speed for the 30-min run was 20.4 m s−1, and the mean significant wave height was 8 m.
Citation: Journal of Atmospheric and Oceanic Technology 31, 6; 10.1175/JTECH-D-13-00201.1
As described in Edson et al. (1998), motion correction algorithms including that used here (which is based on Anctil et al. 1994) employ a small angle assumption in deriving the rotation matrix used to correct the instantaneous angle of the platform. In practice this involves the assumption of separation of variables, so that the rotation matrix 
An additional consequence of platform tilt is to reduce the effective instrument heights from the nominal values. For this extreme run, 63% of all points had height corrections of less than 1%, while only 1.6% had corrections greater than 5%. The net effect is a mean reduction of measurement height by 1.0%. Mahrt et al. (2005) investigated the effect of nonconstant measurement heights on mean wind speed using the logarithmic mean wind profile [Eq. (2)]. Here, we follow their analysis using the instantaneous heights 5.4cos(θ)cos(ϕ), (where 5.4 m is the height of the anemometer in still conditions) and the measured friction velocity u* = 0.86 m s−1 for the run. The net effect of tilt in this extreme case is a reduction of measured wind speed by order 0.1%.
In assessing the performance of the buoy, it is instructive to compare the response of the buoy to the forcing of the surface. Here, we take the ASIS measurement of surface elevation, which has been validated by Pettersson et al. (2003), as the true η and compare it with the EASI estimate derived from the integrated vertical displacement [Eq. (1)]. The 60-m offset between ASIS and EASI makes it difficult to interpret the phase lag between forcing and response. We therefore consider here only the magnitude of the transfer function defined as T = Szz/Sηη, where S represents the frequency spectrum, z is the vertical displacement of EASI (response), and η is the actual surface elevation (forcing). The transfer function plotted in Fig. 6a, based on 4.5 h of data starting on YD 253.75, is typical of light to moderate sea states. The term T is seen to be near unity in the vicinity of the wave energy peak (0.11 Hz), increasing to roughly 2 by 0.4 Hz, before decreasing rapidly as the smaller scales are cut off due to the 6-m length of the EASI hull. Note that the frequency of 0.4 Hz corresponds to λ = 10 m. Surface elevation and EASI response spectra, and the heave transfer function, during the passage of Typhoon Fanapi, are shown in Fig. 6b. The transfer function T during these strongly forced conditions (U10N = 15.5 m s−1; Hs = 2.81 m) is largely similar to that during more moderate sea states, except at low frequencies when T reaches 8 around f = 0.06 Hz (as opposed to near unity in moderate sea states). It is not clear whether this can be attributed to mooring dynamics, but since the associated heave energies are an order of magnitude below those of the peak, the effects are small. The surface tether linking ASIS and EASI broke just prior to the collection of these data, making this the last transfer function to be calculated. The 0.4-Hz natural frequency of the heave transfer function is consistent with that reported by Timpe and van de Voorde (1995) for previous NOMAD configurations. Their response amplitude operator (RAO, not defined but presumably the square root of our T) reached a peak of 1.3 at the natural frequency, about 10% lower than our calculations. Their RAO reached a minimum of 0.7 around 0.33 Hz, a behavior not seen in the present data.
Spectra of surface elevation from ASIS (Sηη, blue) and EASI (Szz, green) along with transfer function T = Szz/Sηη (red). Data are from EASI-N during two 4.5-h periods, starting at (a) 1759 UTC 10 Sep 2010 (YD 253.75; Hs = 1.12 m, U10N = 4.0 m s−1) and (b) 0145 UTC 16 Sep 2010 (YD 259.07; Hs = 2.81 m, U10N = 15.5 m s−1).
Citation: Journal of Atmospheric and Oceanic Technology 31, 6; 10.1175/JTECH-D-13-00201.1
Timpe and van de Voorde (1995) also report an RAO for pitch that we are not able to estimate from the present data. Their pitch RAO has an amplitude near 1.15 in the range of wave frequencies 0.1–0.2 Hz, and it increases to 2.5 at the natural frequency of 0.38 Hz before dropping off.
5. Discussion and conclusions
The survival of EASI through a series of typhoons, with significant wave heights in excess of 10 m, gives confidence regarding the basic design of both the buoy and mooring. Ultimately, the success of the platform depends of the quality of the data recorded. Here, we assess the overall quality of several key meteorological and wave parameters, leaving to other papers a full description and discussion of these datasets.
The use of EASI accelerations to estimate wave height is predicated on the ability of EASI to follow the surface. The transfer function between buoy heave and surface elevation being near unity in the energy containing part of the spectrum (Fig. 6) confirms EASI does indeed follow the surface, at least in the vicinity of the peak. A comparison of significant wave heights measured from ASIS and EASI is given in Fig. 7. The maximum likelihood linear regression gives Hs-EASI = 0.96 Hs-ASIS + 0.08 (r2 = 0.974; 5162 points), which is very close to the 1:1 line. Here, and in Fig. 7, all data from both North and South moorings when EASI and ASIS were tethered together are included. A more thorough discussion of the EASI wave measurements is given in Collins et al. (2013, manuscript submitted to J. Atmos. Oceanic Technol.).
Significant wave height by ASIS vs that measured by EASI while the two buoys were tethered together. The black line indicates a 1:1 curve. The red line is the best linear fit (Hs-EASI = 0.96 Hs-ASIS + 0.08).
Citation: Journal of Atmospheric and Oceanic Technology 31, 6; 10.1175/JTECH-D-13-00201.1
Many individual meteorological sensors failed during the deployment, supporting the decision to use multiple redundant sensors on EASI. In particular, two sonic anemometers (an R2A and the WindMaster) failed during or following typhoon events, likely due to moisture (spray or rain) ingress into the electronics. Bearings failed on one of the Marine Wind Monitors, and one of the K-Gill anemometers lost a propeller blade. While Eckman et al. (2007) observed significant degradation of the sonic anemometer measurements during heavy rain events (droplet volumes in the acoustic path were large enough to affect the speed of sound), spray/rain effects during ITOP were limited to isolated spikes. These were readily identified from the sonic speed of sound channel, relatively rare (around 20 isolated events per 36 000 samples in a 30-min record at the highest winds observed), and easily corrected with interpolation. Wind data from multiple sensors compared favorably (not shown here), giving confidence in the individual measurements.
Turbulent components of the wind vector, after correction for platform motion (see Anctil et al. 1994), were used to calculate the stress, 
Time series of (a) surface elevation, (b) horizontal wind (along-wind component), and (c) vertical wind. The blue lines show the signal as measured and the red lines after motion correction. (d) The 30-min cospectra of uw in dimensionless coordinates. Colors at left, with black representing the Miyake et al. (1970) universal curve, f is frequency, U is mean wind speed, z is the measurement height, and u* is the friction velocity. Time series are from the same time as Fig. 5, during Typhoon Chaba. The cospectra include the same period.
Citation: Journal of Atmospheric and Oceanic Technology 31, 6; 10.1175/JTECH-D-13-00201.1
Downwelling shortwave (SW) radiation from both buoys is shown in Fig. 3c. To reduce flow distortion effects on the wind measurements, the radiometers are placed on shorter masts, below the level of the anemometers. This has the clear trade-off that the radiometers will at times be shaded by the taller masts. This was accounted for by placing the two pairs of radiometers (PSP + PIR) on the opposite corners of EASI, and using the higher PSP values of the two. Katsaros and Devault (1986) and MacWhorter and Weller (1991) present thorough discussions of the errors associated with making SW radiation measurements from buoys. Errors arise due to both the mean tilt and the wave-induced rocking of the pyranometer. Although all sensors (including the radiometers) were leveled on the deck prior to deployment, the accelerometers on board EASI-North indicate a mean of 30-min mean pitch angles, each calculated as asin
The independence of the mean pitch and mean roll values from wind and wave conditions (not shown) support the conclusion that the EASI yoke successfully decoupled EASI from the mooring forces, with the mean pitch angles resulting from the ballasting of EASI. We note that in contrast the ASIS platform mean tilt increases quadratically with wind speed and reached 23° during the almost 20 m s−1 wind speeds in the Southern Ocean (Sahlée et al. 2012). The error associated with nonzero pitch angle on SW radiation measurements is a function primarily of both pitch angle and sun azimuth angle (MacWhorter and Weller 1991). For solar azimuth angles under 30° (0° being overhead), the 5° mean tilt results in an error in SW radiation of O(5%) or less. This increases to 10% for solar azimuth angles over 45°. The platform rocking will increase this error in both cases. In future deployments, the trim of EASI in the water will be better accounted for in leveling the radiometers. This should significantly reduce the mean pitch angle of the radiometer and thence the error.
The air temperature plot (Fig. 3d) shows considerable noise at low winds. These data, from the Rotronic housed in the modified (partially sealed) R. M. Young shield, are clear evidence that the modified shield does not have sufficient ventilation at low winds. In these cases, temperature from other nearby, and well ventilated, sensors was used. However, at high winds, the Rotronics in the modified shields do not show signs of wetting, whereas those in the standard shields were compromised. It is clear that multiple sensors provide the highest chance of a continuous usable temperature dataset.
In summary, the Extreme Air–Sea Interaction buoy has proven to be a platform well suited for making quality wave and near-surface turbulence measurements (including air–sea fluxes) in high wind and wave conditions. Several manuscripts describing the data collected during ITOP have been submitted.
Acknowledgments
The development of EASI was funded by NSF-OCE-0526442, through the OTIC program. Our participation in ITOP was funded by ONR under Grant N0014-09-1-0392. We thank both agencies for their continued support. In addition we acknowledge the contributions of Mike Rebozo (RSMAS); Joe Gabriele and Cary Smith of Environment Canada; John Kemp and the WHOI mooring group; David Tang, Ruey-Chang Wei, Yiing Jang Yang, Yih Yang, and our TORI colleagues. We are grateful for the excellent support and assistance provided by the captains and crew of the R/V Roger Revelle. We thank an anonymous reviewer for prompting the discussion on rotation angle errors.
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