J1.4
The Discrete Whitecap Method for Estimating Sea Salt Aerosol Generation: A Reassessment

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Tuesday, 6 January 2015: 2:15 PM
124A (Phoenix Convention Center - West and North Buildings)
Edward C. Monahan, University of Connecticut, Groton, CT; and A. H. Callaghan
Manuscript (398.0 kB)

The Discrete Whitecap Method (DWM) for combining measurements made during, and immediately after, the decay of a laboratory whitecap with field measurements of oceanic whitecap coverage to estimate the rate of sea salt aerosol generation as a function of wind speed introduced by Monahan et al (1982,1986) has recently been described as “the most widely used source function” by Grythe et al (2014) in an extensive review of such sea-spray aerosol source functions. In the more than 30 years since this marine aerosol generation function was first described, numerous authors have made constructive suggestions as to how it could be improved, and many other authors, accessing this function via secondary sources, have inadvertently misconstrued the significance of the three terms that make up this model (Eq.1).

dFo/dr = Wb•τ-1 •dE/dr Eq.1

Here dFo/dr is the rate of marine aerosol generation, per unit area of sea surface, per unit increment of spray droplet radius (at 80% R.H.), and Wb represents the simple fraction of the sea surface covered by Stage B whitecaps, i.e. decaying foam patches in the usage of Bondur and Sharkov (1982). The symbol tau represents the e-folding time for the exponential decay of such a whitecap, and dE/dr is the laboratory-determined number of marine aerosol particles produced, per increment droplet radius, as a consequence of the demise of all the bubbles initially associated with a whitecap of know initial area.

It should be stressed at the outset that dE/dr encompasses the total production of sea spray droplets resulting from the decay of a laboratory whitecap, and that this production was observed to continue for many seconds beyond the time when the whitecap was no longer visible (Woolf et al, 1987). Thus the suggestion by some that dE/dr might represent in some fashion the average production during the lifetime of the optically resolvable whitecap in not accurate.

The quotient Wb/τ is understood to represent the rate at which optically resolvable whitecap area disappears, and, if a near dynamic equilibrium pertains, also the rate at which new whitecap area appears, on the sea surface.

It should be noted here that the W-values discussed in Monahan (1971), Monahan and O'Muircheartaigh (1980,1986), actually represent the sum of both Stage A whitecap coverage (Wa) and Stage B whitecap coverage. This approximation was deemed appropriate, since for the same wind conditions, etc., Wa was found to be typically only slightly more than 10% of Wb (see, e.g., Monahan and Lu, 1990). The conceptual image animating this model is one where the spilling wave crest, i.e. Stage A whitecap, with its bubble-rich sub-surface alpha-plume, settles down and transforms into a larger Stage B whitecap, with its dependent beta-plume, in a brief enough time that only a sub-set of the largest bubbles have had time to break on the ocean surface, producing a limited number of film-droplets, in this pre-transformation interval. In this construct most of the bubble-mediated aerosol production (essentially all of the jet-droplet-production, and the overwhelming bulk of the film-drop production) occurs during the decay of the optically-resolvable Stage B whitecap, and for tens of seconds, perhaps minutes, afterward.

Recent field measurements have shown that in some circumstances the whitecap growth phase persists for considerably longer than the ~ 10% of the e-folding time for the decaying whitecap (see, e.g., Callaghan et al, 2012; Callaghan, 2013). Indeed, whitecap growth timescales have been shown to be from 20% up to, in some instances, 100% of whitecap decay timescales for individual breaking waves, and therefore make a significant contribution of the overall whitecap timescale. Furthermore, It has been shown that the effective whitecap timescale for the DWM can be more accurately described as the area-weighted mean whitecap lifetime (τDWM) for an ensemble of breaking waves in any given time period (Callaghan, 2013). Field observations suggest ôDWM cannot be expected to remain constant between different observational periods at a given location. Environmental factors expected to influence the value of τDWM include the severity of wave breaking and the injection depth of the bubble plume, the concentration of surfactants in the water column and the surface microlayer, and the scale of the breaking wave. Furthermore, since whitecap coverage is in part a function of the lifetime of whitecap foam along with the breaking rate and mean whitecap scale, not choosing the correct value of τDWM will introduce systematic biases in the estimated sea spray aerosol production flux.

By Developing approaches to parameterize whitecap timescales as a function of appropriate forcing variables, (e.g., wind speed, wave age, surfactant concentration) has the potential to lead to improvements in the accuracy of the DWM. Additional field data on the distributions of maximum whitecap area for individual breaking waves, and a scale-resolved breaking rate, will provide valuable information that can be used to constrain observational measurements of total whitecap coverage. Such field data would lead to improved insights on the natural variability of whitecap coverage, ultimately leading to improved parameterizations with commensurate improvements in the prediction of sea spray aerosol production flux. Finally, as stated in Monahan et al., 1982, it is likely that the quantity dE/dr in the DWM varies for spilling to plunging breaking waves, yet no further work has been done to characterize this with laboratory breaking waves. Having available an improved parameterization for the rate of sea salt aerosol generation on the surface of the world's oceans will also lead to more accurate estimates of the sea surface heat, moisture, and gas fluxes, and thus to improved global climate modeling.

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