Exploring the use of satellite-derived data in sea spray source functions

Abstract

When ocean waves break, air is trapped in the water mass and is brought below the ocean surface. The air breaks up into bubbles which rise in the water column. When these bubbles reach the surface and break, many small droplets are formed. These droplets consist of seawater containing mostly sea salt and organic compounds. They mix with the air above the ocean surface and as a whole form “sea spray aerosol” (SSA). The droplets affect climate both directly, by scattering incoming solar radiation, and indirectly, by acting as cloud condensation nuclei. This cooling effect is important because it partly balances the warming by greenhouse gases. SSA constitutes a substantial part of the natural background aerosol. It is important to know the magnitude of effects of natural aerosols on climate to evaluate effects of anthropogenic aerosols. Models describing these effects include sea spray source functions (SSSFs) that describe the amount of SSA produced per unit oceanic surface area as function of meteorological factors such as wind speed. The organic contribution to SSA significantly affects both its radiative properties and its activity as cloud condensation nuclei. Therefore it is important to explicitly include this contribution in SSSFs. The amount of SSA produced and the fraction of organic aerosol emitted from the ocean are highly uncertain. Aiming at reducing the uncertainties regarding effects of SSA on air quality and climate, in this study the use of satellite-derived data in SSA emission calculations is explored. The overall accomplishments in this study are: •The development of a modelling tool to calculate the global primary emission of SSA particles combined with a methodology to estimate the fraction of organic matter in the sub-micron SSA particles. •A better understanding of the impact of key factors that are used to determine the submicron organic matter fraction in sea spray aerosol emission estimates. Using the developed modelling tool we first calculated a baseline estimate of the global annual emission of sub-micron organic matter with SSA. Subsequently, we determined the sensitivity of this estimate to different choices for the applied SSSF and OM-chlorophyll-a relationship, and to the source, resolution, and handling of the implemented satellite-retrieved chlorophyll-a data set. The largest uncertainties in the global organic matter emission estimate originate from the definition of the OM relationship, the assumed chlorophyll-a background concentration, and the choice of the applied SSSF. •An evaluation of how natural variability of whitecaps affects SSA mass flux predictions. For this we used estimates of whitecap fraction W from satellite-based observations. These long-term global data sets encompass a wide range of meteorological and environmental conditions, and as such implicitly carry information on the influence of environmental factors. A new parameterization for W was derived and applied in an SSSF based on the discrete whitecap method to estimate the global emission rate of super-micron SSA. The obtained SSA production is within the range of previously reported estimates, but shows a distinctly different spatial distribution.