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Lonneke Goddijn-Murphy, David K. Woolf, and Adrian H. Callaghan

relationships between wind speed and W are described by a power law or by a function of cubed wind speed. Summaries of “wind speed only” empirical parameterizations are given by Zhao and Toba (2001) and Anguelova and Webster (2006) . The large differences in the listed parameterizations and the scatter within the various datasets imply that additional factors play a role in the whitecap formation. In this study, we compare a selection of published W algorithms, which are based on wind speed and sea

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W. Brechner Owens and Robert C. Millard Jr.

MAY 1985 NOTES AND CORRESPONDENCE 621NOTES AND CORRESPONDENCEA New Algorithm for CTD Oxygen Calibration:~w. BRECHNER OWENS AND ROBERT C. MILLARD, JR.Woods Hole Oceanographic Institution, Woods Hole, MA 0254310 May 1984 and 5 February 1985 ABSTRACT An algorithm for converting the Beckman dissolved-oxygen probe variables with other data from a WHOI/Brown CTD/O2 system to oxygen

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Edgar L. Andreas, P. Ola G. Persson, and Jeffrey E. Hare

. The fluxes via these two routes scale differently ( Andreas 1994 ; Andreas and DeCosmo 2002 ). For example, although the Tropical Ocean-Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (COARE) version 3.0 bulk flux algorithm ( Fairall et al. 2003 ) has been tuned with flux data collected in wind speeds up to 20 m s −1 and is therefore operationally useful in this wind speed range, it is based strictly on interfacial scaling and thus may not be reliable if it is extrapolated to wind

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James B. Edson, Venkata Jampana, Robert A. Weller, Sebastien P. Bigorre, Albert J. Plueddemann, Christopher W. Fairall, Scott D. Miller, Larry Mahrt, Dean Vickers, and Hans Hersbach

field programs against the relative wind speed adjusted to 10-m. Fig . 3. Direct estimates of the momentum flux (surface stress) vs relative wind speed adjusted to 10 m and neutral stability from four field programs and five platforms. No ship data are included in the analysis to reduce the effect of flow distortion. (top) The individual flux estimates from each experiment and (bottom) the data averaged over wind speed bins. The dashed line represents the original COARE 3.0 bulk algorithm and the

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Lisa M. Beal, Shane Elipot, Adam Houk, and Greta M. Leber

simulations, where its definition remains exactly equivalent regardless of grid resolution and hence boundary layer thickness, which would affect T box . The time-varying jet can have a complex structure ( ACT movie , supplemental information), and it took a few iterations to find a simple and objective algorithm that could identify the jet satisfactorily at each time step. We calculate T x at each time step, low-pass filter using the decorrelation length scale of 56 km, and then look for the position

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Fabien Leckler, Fabrice Ardhuin, Charles Peureux, Alvise Benetazzo, Filippo Bergamasco, and Vladimir Dulov

parameters) of each camera were calibrated using the camera calibration toolbox by Jean-Yves Bouguet. The relative position between the two cameras (i.e., the extrinsic parameters) was computed by first recovering the essential matrix with the autocalibration algorithm of Hartley and Zisserman (2003) and then setting the scale using a known calibration target. Full details of camera calibration procedure can be found in Leckler (2013) . The data described here were acquired on 4 October 2011, with a

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Tianze Peng and David Richter

categorized into three major groups: bulk algorithms, Eulerian multiphase approaches (or one-dimensional models), and Lagrangian approaches. Bulk models attempt to estimate the net air–sea fluxes without resolving the corresponding vertical profiles in the atmosphere or the details of spray’s dynamics and thermodynamics ( Andreas et al. 2015 ; Bao et al. 2011 ; Fairall et al. 1994 ; Mestayer and Lefauconnier 1988 ). Hence, bulk models are associated with two common hypotheses: 1) contributions from

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R. D. Ray and E. D. Zaron

2010 ), it is possible for the mesoscale correction technique to degrade tidal estimates. If tide modeling errors, or internal tide signals, have leaked into the AVISO gridded SSH data, then the correction would remove our signal. Several features of the AVISO gridding algorithms (e.g., Le Traon et al. 2003 ; Pascual et al. 2006 ; Chelton et al. 2011 ) act to diminish such leakage; for example, the use of as many as four different altimeters with different tidal alias periods, the relatively

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Peter Sutherland and W. Kendall Melville

location. Directional frequency spectra were calculated from these data using the iterative maximum likelihood method algorithm in the Wave Analysis for Fatigue and Oceanography (WAFO) MATLAB toolbox ( Brodtkorb et al. 2000 ). Wavenumber spectra could not be computed directly from stereo reconstructions for scales larger than approximately 2 m, and so the directional frequency spectra were converted to wavenumber spectra using the linear deep-water dispersion relation , where ω is the angular

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Michael L. Banner, Christopher J. Zappa, and Johannes R. Gemmrich

properties of microscale breaking waves from infrared imagery using a PIV algorithm . Meas. Sci. Technol. , 16 , 1961 – 1969 , doi: 10.1088/0957-0233/16/10/011 . Keeling , R. F. , 1993 : On the role of large bubbles in air–sea gas exchange and supersaturation in the ocean . J. Mar. Res. , 51 , 237 – 271 , doi: 10.1357/0022240933223800 . Kleiss , J. M. , and W. K. Melville , 2010 : Observations of wave breaking kinematics in fetch-limited seas . J. Phys. Oceanogr. , 40 , 2575 – 2604

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