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| Titel |
Aerosol classification from airborne HSRL and comparisons with the CALIPSO vertical feature mask |
| VerfasserIn |
S. P. Burton, R. A. Ferrare, M. A. Vaughan, A. H. Omar, R. R. Rogers, C. A. Hostetler, J. W. Hair |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 6, no. 5 ; Nr. 6, no. 5 (2013-05-23), S.1397-1412 |
| Datensatznummer |
250017901
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| Publikation (Nr.) |
 copernicus.org/amt-6-1397-2013.pdf |
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| Zusammenfassung |
| Aerosol classification products from the NASA Langley Research
Center (LaRC) airborne High Spectral Resolution Lidar (HSRL-1) on
the NASA B200 aircraft are compared with coincident V3.01 aerosol
classification products from the Cloud-Aerosol Lidar with Orthogonal
Polarization (CALIOP) instrument on the CALIPSO
satellite. For CALIOP, aerosol classification is a key input to the
aerosol retrieval, and must be inferred using aerosol
loading-dependent observations and location information. In
contrast, HSRL-1 makes direct measurements of aerosol intensive
properties, including the lidar ratio, that provide information on
aerosol type. In this study, comparisons are made for 109
underflights of the CALIOP orbit track. We find that 62% of the
CALIOP marine layers and 54% of the polluted continental layers
agree with HSRL-1 classification results. In addition, 80% of
the CALIOP desert dust layers are classified as either dust or dusty
mix byHSRL-1. However, agreement is less for CALIOP smoke
(13%) and polluted dust (35%) layers. Specific case
studies are examined, giving insight into the performance of the
CALIOP aerosol type algorithm. In particular, we find that the
CALIOP polluted dust type is overused due to an attenuation-related
depolarization bias. Furthermore, the polluted dust type frequently
includes mixtures of dust plus marine aerosol. Finally, we find that
CALIOP's identification of internal boundaries between different
aerosol types in contact with each other frequently do not reflect
the actual transitions between aerosol types accurately. Based on
these findings, we give recommendations which may help to improve
the CALIOP aerosol type algorithms. |
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