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| Titel |
Discrimination of biomass burning smoke and clouds in MAIAC algorithm |
| VerfasserIn |
A. Lyapustin, S. Korkin, Y. Wang, B. Quayle, I. Laszlo |
| 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 ; 12, no. 20 ; Nr. 12, no. 20 (2012-10-24), S.9679-9686 |
| Datensatznummer |
250011528
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| Publikation (Nr.) |
 copernicus.org/acp-12-9679-2012.pdf |
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| Zusammenfassung |
| The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm
makes aerosol retrievals from MODIS data at 1 km resolution providing
information about the fine scale aerosol variability. This information is
required in different applications such as urban air quality analysis,
aerosol source identification etc. The quality of high resolution aerosol
data is directly linked to the quality of cloud mask, in particular detection
of small (sub-pixel) and low clouds. This work continues research in this
direction, describing a technique to detect small clouds and introducing the
"smoke test" to discriminate the biomass burning smoke from the clouds. The
smoke test relies on a relative increase of aerosol absorption at MODIS
wavelength 0.412 μm as compared to 0.47–0.67 μm due to
multiple scattering and enhanced absorption by organic carbon released during
combustion. This general principle has been successfully used in the OMI
detection of absorbing aerosols based on UV measurements. This paper provides
the algorithm detail and illustrates its performance on two examples of
wildfires in US Pacific North-West and in Georgia/Florida of 2007. |
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