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| Titel |
A review of sea-spray aerosol source functions using a large global set of sea salt aerosol concentration measurements |
| VerfasserIn |
H. Grythe, J. Ström, R. Krejci, P. Quinn, A. Stohl |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 14, no. 3 ; Nr. 14, no. 3 (2014-02-03), S.1277-1297 |
| Datensatznummer |
250118352
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| Publikation (Nr.) |
 copernicus.org/acp-14-1277-2014.pdf |
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| Zusammenfassung |
| 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 Dp < 10 μm,
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 U103.5, where
U10 is the source region averaged
10 m 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
Dp < 10 μm of 9 Pg yr−1, and is the best fit to the observed
concentrations. |
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