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An air-water coupled model is developed to investigate wind-wave generation processes at low wind speed where the surface wind stress is about 0.089 dyn cm −2 and the associated surface friction velocities of the air and the water are u * a ∼ 8.6 cm s −1 and u * w ∼ 0.3 cm s −1 , respectively. The air-water coupled model satisfies continuity of velocity and stress at the interface simultaneously, and hence can capture the interaction between air and water motions. Our simulations show that the wavelength of the fastest growing waves agrees with laboratory measurements (λ ∼ 8-12 cm) and the wave growth consists of linear and exponential growth stages as suggested by theoretical and experimental studies. Constrained by the linearization of the interfacial boundary conditions, we perform simulations only for a short time period, about 70 s; the maximum wave slope of our simulated waves is ak ∼ 0.01 and the associated wave age is c/u * a ∼ 5, which is a slow-moving wave. The effects of waves on turbulence statistics above and below the interface are examined. Sensitivity tests are carried out to investigate the effects of turbulence in the water, surface tension, and the numerical depth of the air domain. The growth rates of the simulated waves are compared to a previous theory for linear growth and to experimental data and previous simulations that used a prescribed wavy surface for exponential growth. In the exponential growth stage, some of the simulated wave growth rates are comparable to previous studies, but some are about 2-3 times larger than previous studies. In the linear growth stage, the simulated wave growth rates for these four simulation runs are about 1-2 times larger than previously predicted. In qualitative agreement with previous theories for slow-moving waves, the mechanisms for the energy transfer from wind to waves in our simulations are mainly from turbulence-induced pressure fluctuations in the linear growth stage and due to the in-phase relationship between wave slope and wave-induced pressure fluctuations in the exponential growth stage.

The efficiency of transfer of gases and particles across the air-sea interface is controlled by several physical, biological and chemical processes in the atmosphere and water which are described here (including waves, large-and small-scale turbulence, bubbles, sea spray, rain and surface films). For a deeper understanding of relevant transport mechanisms, several models have been developed, ranging from conceptual models to numerical models. Most frequently the transfer is described by various functional dependencies of the wind speed, but more detailed descriptions need additional information. The study of gas transfer mechanisms uses a variety of experimental methods ranging from laboratory studies to carbon budgets, mass balance methods, micrometeorological techniques and thermographic techniques. Different methods resolve the transfer at different scales of time and space; this is important to take into account when comparing different results. Air-sea transfer is relevant in a wide range of applications, for example, local and regional fluxes, global models, remote sensing and computations of global inventories. The sensitivity of global models to the description of transfer velocity is limited; it is however likely that the formulations are more important when the resolution increases and other processes in models are improved. For global flux estimates using inventories or remote sensing products the accuracy of the transfer formulation as well as the accuracy of the wind field is crucial. IntroductionThe transfer of gases and particles across the air-sea interface depends not only on the concentration difference between the water and the air, but also on the efficiency of the transfer process. The efficiency of the transfer is controlled by complex interaction of a variety of processes in the air and in the water near the interface. Here we treat both gases and particles since the transfer, to some extent, is governed by similar mechanisms. Studies of transfer across the air-sea interface include a variety of methods and techniques ranging from laboratory studies, modeling and large-scale field studies. Various methods reach somewhat different conclusions, due to representation of different

[1] We assess the possible impact of the distribution of naturally occurring surfactants on the direct integration of the global atmosphere-ocean CO 2 flux across the ocean surface. The global atmosphere-ocean CO 2 flux is calculated using the monthly mean ÁpCO 2 climatology compiled by Takahashi et al. [1997] as well as satellite wind speed and seasurface temperature data. In the absence of any global map of surfactant coverage and as it is known that phytoplankton exudates and degradation products are the major sources of marine surfactants, ocean primary productivity, which can be derived from the satellitebased estimate of chlorophyll concentration, is used as an indicator of the presence of surfactants as proposed by Asher [1997]. From the calculated results it is found that suppression of the upward and downward CO 2 fluxes by marine surfactants exhibits an asymmetric effect: The average percent reduction of absorption flux by surfactants is about twice that of outgassing, which results in an overall decrease in the net global CO 2 uptake by the oceans. For almost half of the year (between January and May) the presence of surfactants does not affect CO 2 outgassing from global oceans. In contrast, throughout the entire year the presence of surfactants suppresses CO 2 absorption by the oceans. The major reduction in absorption fluxes occurs in the northern Pacific and Atlantic (10°N to 70°N) in all seasons and in the Southern Ocean (south of 40°S) in austral spring and summer. However, the most significant decrease in outgassing fluxes occurs in the equatorial and southern Pacific Ocean (40°S to 10°N), particularly in the eastern equatorial and subtropical waters off the southern American coast, in the period of austral spring and summer. Annual net CO 2 flux is reduced by approximately 20% under the surfactant coverage condition that the primary productivity is above a threshold value of 25 g-C m À2 mom À1 and by about 50% with a threshold of 15 g-C m À2 mom À1 .