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Journal of atmospheric and oceanic technology, 2015-11, Vol.32 (11), p.1977-1998
2015
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Details

Autor(en) / Beteiligte
Titel
Automated Retrieval of Cloud and Aerosol Properties from the ARM Raman Lidar. Part I: Feature Detection
Ist Teil von
  • Journal of atmospheric and oceanic technology, 2015-11, Vol.32 (11), p.1977-1998
Ort / Verlag
Boston: American Meteorological Society
Erscheinungsjahr
2015
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
  • A feature detection and extinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement Program's (ARM) Raman lidar (RL) has been developed. Presented here is Part I of the FEX algorithm: the detection of features including both clouds and aerosols. The approach of FEX is to use multiple quantities- scattering ratios derived using elastic and nitrogen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio-to identify features using range-dependent detection thresholds. FEX is designed to be context sensitive with thresholds determined for each profile by calculating the expected clear-sky signal and noise. The use of multiple quantities provides complementary depictions of cloud and aerosol locations and allows for consistency checks to improve the accuracy of the feature mask. The depolarization ratio is shown to be particularly effective at detecting optically thin features containing nonspherical particles, such as cirrus clouds. Improvements over the existing ARM RL cloud mask are shown. The performance of FEX is validated against a collocated micropulse lidar and observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite over the ARM Darwin, Australia, site. While the focus is on a specific lidar system, the FEX framework presented here is suitable for other Raman or high spectral resolution lidars.
Sprache
Englisch
Identifikatoren
ISSN: 0739-0572
eISSN: 1520-0426
DOI: 10.1175/JTECH-D-14-00150.1
Titel-ID: cdi_proquest_miscellaneous_1816018973

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