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Abstract. In this study, the utility of satellite-based whitecap fraction (W ) data for the prediction of sea spray aerosol (SSA) emission rates is explored. More specifically, the study aims at evaluating how an account for natural variability of whitecaps in the W parameterization would affect SSA mass flux predictions when using a sea spray source function (SSSF) based on the discrete whitecap method. The starting point is a data set containing W data for 2006 together with matching wind speed U 10 and sea surface temperature (SST) T . Whitecap fraction W was estimated from observations of the ocean surface brightness temperature T B by satellite-borne radiometers at two frequencies (10 and 37 GHz). A global-scale assessment of the data set yielded approximately quadratic correlation between W and U 10 . A new global W (U 10 ) parameterization was developed and used to evaluate an intrinsic correlation between W and U 10 that could have been introduced while estimating W from T B . A regional-scale analysis over different seasons indicated significant differences of the coefficients of regional W (U 10 ) relationships. The effect of SST on W is explicitly accounted for in a new W (U 10 , T ) parameterization. The analysis of W values obtained with the new W (U 10 ) and W (U 10 , T ) parameterizations indicates that the influence of secondary factors on W is for the largest part embedded in the exponent of the wind speed dependence. In addition, the W (U 10 , T ) parameterization is able to partially model the spread (or variability) of the satellite-based W data. The satellite-based parameterization W (U 10 , T ) was applied in an SSSF to estimate the global SSA emission rate. The thus obtained SSA production rate for 2006 of 4.4 × 10 12 kg year −1 is within previously reported estimates, however with distinctly different spatial distribution.

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Abstract. In this study the utility of satellite-based whitecap fraction (W) values for the prediction of sea spray aerosol (SSA) emission rates is explored. More specifically, the study is aimed at improving the accuracy of the sea spray source function (SSSF) derived by using the whitecap method through the reduction of the uncertainties in the parameterization of W by better accounting for its natural variability. The starting point is a dataset containing W data, together with matching environmental and statistical data, for 2006. Whitecap fraction W was estimated from observations of the ocean surface brightness temperature TB by satellite-borne radiometers at two frequencies (10 and 37 GHz). A global scale assessment of the data set to evaluate the wind speed dependence of W revealed a quadratic correlation between W and U10, as well as a relatively larger spread in the 37 GHz data set. The latter could be attributed to secondary factors affecting W in addition to U10. To better visualize these secondary factors, a regional scale assessment over different seasons was performed. This assessment indicates that the influence of secondary factors on W is for the largest part imbedded in the exponent of the wind speed dependence. Hence no further improvement can be expected by looking at effects of other factors on the variation in W explicitly. From the regional analysis, a new globally applicable quadratic W(U10) parameterization was derived. An intrinsic correlation between W and U10 that could have been introduced while estimating W from TB was determined, evaluated and presumed to lie within the error margins of the newly derived W(U10) parameterization. The satellite-based parameterization was compared to parameterizations from other studies and was applied in a SSSF to estimate the global SSA emission rate. The thus obtained SSA production for 2006 of 4.1 × 1012 kg is within previously reported estimates. While recent studies that account for parameters other than U10 explicitly could be suitable to improve predictions of SSA emissions, we promote our new W(U10) parameterization as an alternative approach that implicitly accounts for these different parameters and helps to improve SSA emission estimates equally well.

Abstract. In this study, the utility of satellite-based whitecap fraction (W ) data for the prediction of sea spray aerosol (SSA) emission rates is explored. More specifically, the study aims at evaluating how an account for natural variability of whitecaps in the W parameterization would affect SSA mass flux predictions when using a sea spray source function (SSSF) based on the discrete whitecap method. The starting point is a data set containing W data for 2006 together with matching wind speed U 10 and sea surface temperature (SST) T . Whitecap fraction W was estimated from observations of the ocean surface brightness temperature T B by satellite-borne radiometers at two frequencies (10 and 37 GHz). A global-scale assessment of the data set yielded approximately quadratic correlation between W and U 10 . A new global W (U 10 ) parameterization was developed and used to evaluate an intrinsic correlation between W and U 10 that could have been introduced while estimating W from T B . A regional-scale analysis over different seasons indicated significant differences of the coefficients of regional W (U 10 ) relationships. The effect of SST on W is explicitly accounted for in a new W (U 10 , T ) parameterization. The analysis of W values obtained with the new W (U 10 ) and W (U 10 , T ) parameterizations indicates that the influence of secondary factors on W is for the largest part embedded in the exponent of the wind speed dependence. In addition, the W (U 10 , T ) parameterization is able to partially model the spread (or variability) of the satellite-based W data. The satellite-based parameterization W (U 10 , T ) was applied in an SSSF to estimate the global SSA emission rate. The thus obtained SSA production rate for 2006 of 4.4 × 10 12 kg year −1 is within previously reported estimates, however with distinctly different spatial distribution.