Evidence for complete and partial surface renewal at an air‐water interface

Jessup, Andrew T.; Asher, William E.; Atmane, Mohamed A.; Phadnis, Kapil; Zappa, Christopher J.; Loewen, Mark

doi:10.1029/2009gl038986

Cited by 24 publications

(28 citation statements)

References 24 publications

(28 reference statements)

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“…Following Asher et al (2004), the surface penetration theory provides a more accurate conceptual model for air-sea gas exchange. This is supported by the work of Jessup et al (2009) who found evidence for complete and partial surface renewal at an air-water interface.…”

Section: Thermographic Techniquessupporting

confidence: 72%

Transfer Across the Air-Sea Interface

Garbe

Rutgersson

Boutin

et al. 2013

Springer Earth System Sciences

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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

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Section: Thermographic Techniquessupporting

confidence: 72%

Transfer Across the Air-Sea Interface

Garbe

Rutgersson

Boutin

et al. 2013

Springer Earth System Sciences

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“…The signal is evident in parts of the river in all of the image sequences, even in the daylight, high‐noise (see below) image sequences. On the basis of the dynamic nature of the thermal signals seen in image sequences, the ubiquity of the texture across the river, and the small, consistent temperature difference, we conclude that the thermal signals are caused by a thin layer of water near the river surface being replaced by bulk underlying water because of turbulent mixing, a process often referred to as “surface renewal” [ Jessup et al , 2009; Katsaros , 1980]. The thin layer at the surface of natural waters is on the order of 1 mm thick and is alternatively referred to in the literature as the thermal boundary layer, thermal skin, conductive sublayer, or aquatic surface microlayer [ Katsaros , 1980].…”

Section: Discussionmentioning

confidence: 99%

Quantifying riverine surface currents from time sequences of thermal infrared imagery

Puleo

McKenna

Holland

et al. 2012

Water Resources Research

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[1] River surface currents are quantified from thermal and visible band imagery using two methods. One method utilizes time stacks of pixel intensity to estimate the streamwise velocity at multiple locations. The other method uses particle image velocimetry to solve for optimal two-dimensional pixel displacements between successive frames. Field validation was carried out on the Wolf River, a small coastal plain river near Landon, Mississippi, United States, on 26-27 May 2010 by collecting imagery in association with in situ velocities sampled using electromagnetic current meters deployed 0.1 m below the river surface. Comparisons are made between mean in situ velocities and image-derived velocities from 23 thermal and 6 visible-band image sequences (5 min length) during daylight and darkness conditions. The thermal signal was a small apparent temperature contrast induced by turbulent mixing of a thin layer of cooler water near the river surface with underlying warmer water. The visible-band signal was foam on the water surface. For thermal imagery, streamwise velocities derived from the pixel time stack and particle image velocimetry technique were generally highly correlated to mean streamwise current meter velocities during darkness (r 2 typically greater than 0.9) and early morning daylight (r 2 typically greater than 0.83). Streamwise velocities from the pixel time stack technique had high correlation for visible-band imagery during early morning daylight hours with respect to mean current meter velocities (r 2 > 0.86). Streamwise velocities for the particle image velocimetry technique for visible-band imagery had weaker correlations with only three out of six correlations performed having an r 2 exceeding 0.6.

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“…In other words, there exist divergence/convergence events that have a measurable effect on surface temperature but do not affect the near‐surface gas concentration profile. This observation is consistent with the evidence for partial surface renewal events reported by Jessup et al [2009].…”

Section: Discussionmentioning

confidence: 99%

Statistics of surface divergence and their relation to air‐water gas transfer velocity

Asher¹,

Liang²,

Zappa³

et al. 2012

J. Geophys. Res.

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[1] Air-sea gas fluxes are generally defined in terms of the air/water concentration difference of the gas and the gas transfer velocity, k L . Because it is difficult to measure k L in the ocean, it is often parameterized using more easily measured physical properties. Surface divergence theory suggests that infrared (IR) images of the water surface, which contain information concerning the movement of water very near the air-water interface, might be used to estimate k L . Therefore, a series of experiments testing whether IR imagery could provide a convenient means for estimating the surface divergence applicable to air-sea exchange were conducted in a synthetic jet array tank embedded in a wind tunnel. Gas transfer velocities were measured as a function of wind stress and mechanically generated turbulence; laser-induced fluorescence was used to measure the concentration of carbon dioxide in the top 300 mm of the water surface; IR imagery was used to measure the spatial and temporal distribution of the aqueous skin temperature; and particle image velocimetry was used to measure turbulence at a depth of 1 cm below the air-water interface. It is shown that an estimate of the surface divergence for both wind-shear driven turbulence and mechanically generated turbulence can be derived from the surface skin temperature. The estimates derived from the IR images are compared to velocity field divergences measured by the PIV and to independent estimates of the divergence made using the laser-induced fluorescence data. Divergence is shown to scale with k L values measured using gaseous tracers as predicted by conceptual models for both wind-driven and mechanically generated turbulence.

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Evidence for complete and partial surface renewal at an air‐water interface

Cited by 24 publications

References 24 publications

Transfer Across the Air-Sea Interface

Transfer Across the Air-Sea Interface

Quantifying riverine surface currents from time sequences of thermal infrared imagery

Statistics of surface divergence and their relation to air‐water gas transfer velocity

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