![]() On one hand, this is due to the limited understanding of the formation mechanism of whitecaps as well as the increasing complexity of modeling with multiple factors. Some studies investigate the influence of other factors (e.g., wave height, sea surface temperature) on W besides wind speed, while most of them consider only one of those factors as a univariate variable. The W parameterization adopted in the most commonly used SSSF was proposed by Monahan and O’Muircheartaigh (hereafter M80, see Table 1, Table 1 shows three W physical parameterizations and their abbreviations used in this paper). These wind speed-dependent W parameterizations are used in the sea spray source function (SSSF). Most of the parameterizations are nonlinear functions obtained by fitting in situ observations of wind speed and W. Through a permutation test, we ranked the importance of different input variables and revealed the indispensable role of variables such as significant wave height, sea surface temperature, etc., in the whitecap fraction parameterization.Ī number of W observations have been made by previous studies and various parameterizations have been proposed (Wang et al.: Table 1 ). Compared with a recent developed parameterization by Albert and coworkers, the new parameterization can reduce the computational error of the whitecap fraction by about 15%, and it can better characterize the variability of the whitecap fraction, which provides a reference for the uncertainty study of sea-salt aerosol estimation. In this work, we constructed a novel multivariate whitecap fraction parameterization using a deep neural network, which is diagnosed and interpreted. Past whitecap fraction parameterizations were mostly power functions of wind speed, lacking consideration of other factors, while the single wind speed dependence makes it difficult to explain the variability of the whitecap fraction. Accurate calculation of the whitecap fraction is of great importance for the estimation of air-sea momentum flux, heat flux and sea-salt aerosol flux in Earth system models. ![]()
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