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A review of sea-spray aerosol source functions using a large global set of sea salt aerosol concentration measurements
Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
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2014 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 14, no 3, 1277-1297 p.Article in journal (Refereed) Published
Abstract [en]

Sea-spray aerosols (SSA) are an important part of the climate system because of their effects on the global radiative budget - both directly as scatterers and absorbers of solar and terrestrial radiation, and indirectly as cloud condensation nuclei (CCN) influencing cloud formation, lifetime, and precipitation. In terms of their global mass, SSA have the largest uncertainty of all aerosols. In this study we review 21 SSA source functions from the literature, several of which are used in current climate models. In addition, we propose a new function. Even excluding outliers, the global annual SSA mass produced spans roughly 3-70 Pg yr(-1) for the different source functions, for particles with dry diameter D-p < 10 mu m, with relatively little interannual variability for a given function. The FLEXPART Lagrangian particle dispersion model was run in backward mode for a large global set of observed SSA concentrations, comprised of several station networks and ship cruise measurement campaigns. FLEXPART backward calculations produce gridded emission sensitivity fields, which can subsequently be multiplied with gridded SSA production fluxes in order to obtain modeled SSA concentrations. This allowed us to efficiently and simultaneously evaluate all 21 source functions against the measurements. Another advantage of this method is that source-region information on wind speed and sea surface temperatures (SSTs) could be stored and used for improving the SSA source function parameterizations. The best source functions reproduced as much as 70% of the observed SSA concentration variability at several stations, which is comparable with state of the art aerosol models. The main driver of SSA production is wind, and we found that the best fit to the observation data could be obtained when the SSA production is proportional to U-10(3.5), where U-10 is the source region averaged 10m wind speed. A strong influence of SST on SSA production, with higher temperatures leading to higher production, could be detected as well, although the underlying physical mechanisms of the SST influence remains unclear. Our new source function with wind speed and temperature dependence gives a global SSA production for particles smaller than D-p < 10 mu m of 9 Pg yr(-1), and is the best fit to the observed concentrations.

Place, publisher, year, edition, pages
2014. Vol. 14, no 3, 1277-1297 p.
National Category
Meteorology and Atmospheric Sciences
URN: urn:nbn:se:su:diva-102492DOI: 10.5194/acp-14-1277-2014ISI: 000332384900009OAI: diva2:710474


Available from: 2014-04-07 Created: 2014-04-07 Last updated: 2014-04-09Bibliographically approved

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Grythe, HenrikStröm, JohanKrejci, Radovan
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