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| Titel |
Detection of dust aerosol by combining CALIPSO active lidar and passive IIR measurements |
| VerfasserIn |
B. Chen, J. Huang, P. Minnis, Y. Hu, Y. Yi, Z. Liu, D. Zhang, X. Wang |
| 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 ; 10, no. 9 ; Nr. 10, no. 9 (2010-05-06), S.4241-4251 |
| Datensatznummer |
250008425
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| Publikation (Nr.) |
 copernicus.org/acp-10-4241-2010.pdf |
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| Zusammenfassung |
| The version 2 Cloud-Aerosol Lidar and Infrared Pathfinder Satellite
Observations (CALIPSO) dust layer detection method, which is based only on
lidar measurements, misclassified about 43% dust layers (mainly dense
dust layers) as cloud layers over the Taklamakan Desert. To address this
problem, a new method was developed by combining the CALIPSO Cloud-Aerosol
Lidar with Orthogonal Polarization (CALIOP) and passive Infrared Imaging
Radiometer (IIR) measurements. This combined lidar and IR measurement
(hereafter, CLIM) method uses the IIR tri-spectral IR brightness
temperatures to discriminate between ice cloud and dense dust layers, and
lidar measurements alone to detect thin dust and water cloud layers. The
brightness temperature difference between 10.60 and 12.05 μm
(BTD11−12) is typically negative for dense dust and generally positive
for ice cloud, but it varies from negative to positive for thin dust layers,
which the CALIPSO lidar correctly identifies. Results show that the CLIM
method could significantly reduce misclassification rates to as low as ~7%
for the active dust season of spring 2008 over the Taklamakan Desert.
The CLIM method also revealed 18% more dust layers having greatly
intensified backscatter between 1.8 and 4 km altitude over the source region
compared to the CALIPSO version 2 data. These results allow a more accurate
assessment of the effect of dust on climate. |
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