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). It is believed that the resulting, commonly used, W(U) 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 satellite-derived 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) 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. Key Points Variability in whitecap fraction is not completely explained by wind speed The impact of second order forcing factors is assessed Relative importance of secondary factors depends on the retrieval wavelength.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)