On the variability of whitecap fraction using satellite-based observations

Abstract

[1] Despite decades of effort to accurately quantify whitecap fraction W using in situ photography of the ocean surface, there remains significant scatter in estimates for any given 10 m wind speed (U 10 ). It is believed that the resulting, commonly used, W(U 10 ) parameterizations do not fully account for the true variability in W, by failing to incorporate the impact of the wavefield and other environmental conditions. This paper attests to the variability in whitecap fraction attributed to these additional factors, by analyzing satellitederived W estimates over the globe for a full year. A comparison is made between the wind speed dependence of satellite estimates and three W(U 10 ) relationships formulated from in situ photographic data. The influence of various secondary factors on W is investigated once the dominant wind speed dependence is accounted for. The W retrieval's sensitivity to secondary forcings is dependent upon microwave frequency; at 37 GHz it varies by up to 25% of the mean at a given wind speed, while at 10 GHz it is a maximum of 8%. This results from a frequency-dependent sensitivity to foam depth; at 10 GHz predominantly foam from active breaking waves is detected, while at 37 GHz thin foam in residual whitecaps is also seen. Principal component analysis is used to rank variables by their success in accounting for variability in W. After wind speed, the most important secondary factor that accounts for variability in W is the wavefield. A wind-wave Reynolds number accounts for almost as much variability in W as wind speed.

SURFEX v8.0 interface with OASIS3-MCT to couple atmosphere with hydrology, ocean, waves and sea-ice models, from coastal to global scales

“…Emissivity is a constant value, usually taken as 0.96 over the ocean. Ocean albedo can be taken as a constant or can evolve following the Taylor et al (1996) formulation to account for the solar zenith angle, the Séférian et al (2017) multi-spectral band albedo accounting for solar zenith angle and wind speed, or the Salisbury et al (2013) formulation. E is total evaporation (including sublimation), and P L and P S are liquid and solid precipitation on the surface, respectively (coming directly from the ATM component or from the atmospheric forcing in forced mode).…”

Effects of Salinity on Surface Lifetime of Large Individual Bubbles

“…Whitecap fraction is usually parameterized as a function of wind speed. However, other variables also influence W, including atmospheric stability, currents, seawater temperature, wave field, salinity, and surface-active materials (surfactants) [6,7]. A better understanding of the relationship of whitecap fraction to each of these variables can facilitate the development of new W parameterizations.…”

Status and future of numerical atmospheric aerosol prediction with a focus on data requirements

“…There remains, however, an order of magnitude uncertainty in the parameterization of the whitecap fraction, and there is increasing evidence that neither the production of aerosol per unit area whitecap nor the lifetime of a whitecap are independent of the scale of wave breaking or other water properties (Norris et al, 2013a;Callaghan, 2013;Spada et al, 2013;Salter et al, 2014b;Salter et al, 2015). Recent work on satellite retrievals of the whitecaps (Anguelova and Webster, 2006;Gaiser, 2011, 2013) shows significant promise as a means of providing this driving parameter for sea spray source functions and implicitly accounting for the wide range of important controlling factors in addition to wind speed (Salisbury et al, 2013(Salisbury et al, , 2014. It might also ultimately allow a source function to be specified directly in terms of the satellite measurements.…”