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Titel |
Effect of water vapor on the determination of aerosol direct radiative effect based on the AERONET fluxes |
VerfasserIn |
J. Huttunen, A. Arola, G. Myhre, A. V. Lindfors, T. Mielonen, S. Mikkonen, J. S. Schafer, S. N. Tripathi, M. Wild, M. Komppula, K. E. J. Lehtinen |
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. 12 ; Nr. 14, no. 12 (2014-06-20), S.6103-6110 |
Datensatznummer |
250118823
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Publikation (Nr.) |
copernicus.org/acp-14-6103-2014.pdf |
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Zusammenfassung |
The aerosol direct radiative effect (ADRE) is defined as the change in the
solar radiation flux, F, due to aerosol scattering and absorption. The
difficulty in determining ADRE stems mainly from the need to estimate F
without aerosols, F0, with either radiative transfer modeling and
knowledge of the atmospheric state, or regression analysis of radiation data
down to zero aerosol optical depth (AOD), if only F and AOD are observed.
This paper examines the regression analysis method by using modeled surface
data products provided by the Aerosol Robotic Network (AERONET). We
extrapolated F0 by two functions: a straight linear line and an
exponential nonlinear decay. The exponential decay regression is expected to
give a better estimation of ADRE with a few percent larger extrapolated
F0 than the linear regression. We found that, contrary to the
expectation, in most cases the linear regression gives better results than
the nonlinear. In such cases the extrapolated F0 represents an
unrealistically low water vapor column (WVC), resulting in underestimation
of attenuation caused by the water vapor, and hence too large F0 and
overestimation of the magnitude of ADRE. The nonlinear ADRE is generally
40–50% larger in magnitude than the linear ADRE due to the extrapolated
F0 difference. Since for a majority of locations, AOD and WVC have a
positive correlation, the extrapolated F0 with the nonlinear regression
fit represents an unrealistically low WVC, and hence too large F0. The
systematic underestimation of F0 with the linear regression is
compensated by the positive correlation between AOD and water vapor,
providing the better result. |
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