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Johannes R. Gemmrich, Michael L. Banner, and Chris Garrett

1. Introduction Surface waves have been described as the “gearbox” between the atmosphere and ocean ( Ardhuin et al. 2005 ). In particular, wave breaking plays an important role in many air–sea exchange and upper-ocean processes. At moderate to high wind speeds the momentum transfer from wind to ocean currents passes through the wave field via wave breaking. The breaking of surface waves is responsible for the dissipation of wave energy, and thus wave breaking is a source of enhanced turbulence

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P. B. Smit and T. T. Janssen

1. Introduction The dynamics and statistics of ocean waves are important, for example, for upper-ocean dynamics (e.g., Craik and Leibovich 1976 ; Smith 2006 ; Aiki and Greatbatch 2011 ), air–sea interaction (e.g., Janssen 2009 ), ocean circulation (e.g., McWilliams and Restrepo 1999 ), and wave-driven circulation and transport processes (e.g., Hoefel and Elgar 2003 ; Svendsen 2006 ). Modern stochastic wave models are routinely applied to a wide range of oceanic scales, both in open-ocean

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Alexander V. Babanin, Jason McConochie, and Dmitry Chalikov

1. Introduction Modeling and measurements of the winds over the ocean surface are important in engineering, geophysics, remote sensing, and other metocean applications. The wind-wave/current interactions, or more generally air–sea energy and momentum exchanges, happen directly at the ocean interface, but measuring wind speeds and momentum right at the surface is difficult in field conditions, particularly at heavy seas which are usually of the main interest. Therefore, the 10-m elevation is

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Jerome A. Smith

1. Introduction Although first described over 100 years ago (e.g., Pidduck 1912 ), there has been a recent rekindling of interest in oceanic acoustic–gravity surface waves, in particular in the context of tsunamis (e.g., Stiassnie 2010 ; Kadri and Stiassnie 2012 ; Hendin and Stiassnie 2013 ; Abdolali et al. 2015 ; Cecioni et al. 2015 ). It has also been suggested that they can contribute to deep water transport ( Kadri 2014 ). The original derivation is a bit hard to follow, so in the

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Min Zhang, Zhaohua Wu, and Fangli Qiao

the warming hiatus. One suggests that the La Niña–like decadal cooling in the eastern Pacific Ocean and intensified trade winds over the equatorial Pacific, corresponding to the negative phase of the interdecadal Pacific oscillation (IPO), had taken up the “missing heat” ( Zhang et al. 1997 ; Kosaka and Xie 2013 ; England et al. 2014 ; Watanabe et al. 2014 ; Nieves et al. 2015 ). The intensified trade winds produce the equatorial ocean Kelvin waves and deepen the equatorial thermocline

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S. Y. Annenkov and V. I. Shrira

1. Introduction For practical applications, it is important to know the probability of wave height in seas and oceans at a given place and time. It is essential to predict the probability density function (PDF) of surface elevations, along with the meteorological forecasting (e.g., Goda 2000 ). If a wave field is linear, it obeys the Gaussian statistics, and the wave heights follow the Rayleigh distribution, under the additional assumption of the narrowbandedness of the energy spectrum ( Rice

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Fanglou Liao and Xiao Hua Wang

important in coastal oceanic variabilities on time scales between the local inertial period and atmospheric weather changes over the continental margins ( Brink 1991 ; Ding et al. 2012 ), as they are generally excited by the alongshore wind stress ( Adams and Buchwald 1969 ). Assuming no stratification and a variable shelf bottom, the low-frequency wind-forced coastal responses generally exist as continental shelf waves (CSWs), whereas in a stratified ocean with a flat shelf bottom and a lateral

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Rodolfo Bolaños, Laurent O. Amoudry, and Ken Doyle

1. Introduction Instrumented bottom frames have been used since the 1960s to investigate bottom boundary layer processes and sediment dynamics. Data from these frames have led to a better understanding of near-bottom wave and current flows in the coastal ocean, and have been very important for the development of numerical models. These data have been used for calculations of bottom stress, bottom roughness, sediment flux, sediment resuspension, and near-bed and water column processes (e

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Dejun Dai, Fangli Qiao, Wojciech Sulisz, Lei Han, and Alexander Babanin

1. Introduction Energy input from wind to the surface waves, integrated over the World Ocean, is about 60 TW ( Wang and Huang 2004 ). Such a large amount of energy will dissipate and cause mixing in the ocean mixed layer. Qiao et al. (2004) proposed a parameterization scheme for the nonbreaking surface-wave-induced vertical mixing (NBWAIM), and numerical experiments show that this parameterization can significantly improve the performance of the ocean circulation models ( Qiao et al. 2004

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Nirnimesh Kumar, Douglas L. Cahl, Sean C. Crosby, and George Voulgaris

1. Introduction Surface gravity waves are important drivers for coastal circulation and upper open-ocean mixing. Wave-induced mass flux (i.e., Stokes drift u St ; Stokes 1847 ) affects multiple processes in the marine environment. In an alongshore uniform bathymetry, Stokes drift–induced mass flux leads to offshore-directed undertow in the surfzone and the inner shelf (e.g., Lentz et al. 2008 ). Stokes drift and mean velocity shear interaction (i.e., vortex force; Craik and Leibovich 1976

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