Literature DB >> 21935239

CALIPSO lidar ratio retrieval over the ocean.

Damien Josset1, Raymond Rogers, Jacques Pelon, Yongxiang Hu, Zhaoyan Liu, Ali Omar, Peng-Wang Zhai.   

Abstract

We are demonstrating on a few cases the capability of CALIPSO to retrieve the 532 nm lidar ratio over the ocean when CloudSat surface scattering cross section is used as a constraint. We are presenting the algorithm used and comparisons with the column lidar ratio retrieved by the NASA airborne high spectral resolution lidar. For the three cases presented here, the agreement is fairly good. The average CALIPSO 532 nm column lidar ratio bias is 13.7% relative to HSRL, and the relative standard deviation is 13.6%. Considering the natural variability of aerosol microphysical properties, this level of accuracy is significant since the lidar ratio is a good indicator of aerosol types. We are discussing dependencies of the accuracy of retrieved aerosol lidar ratio on atmospheric aerosol homogeneity, lidar signal to noise ratio, and errors in the optical depth retrievals. We are obtaining the best result (bias 7% and standard deviation around 6%) for a nighttime case with a relatively constant lidar ratio (in the vertical) indicative of homogeneous aerosol type.

Year:  2011        PMID: 21935239     DOI: 10.1364/OE.19.018696

Source DB:  PubMed          Journal:  Opt Express        ISSN: 1094-4087            Impact factor:   3.894


  1 in total

1.  The CALIPSO Version 4 Automated Aerosol Classification and Lidar Ratio Selection Algorithm.

Authors:  Man-Hae Kim; Ali H Omar; Jason L Tackett; Mark A Vaughan; David M Winker; Charles R Trepte; Yongxiang Hu; Zhaoyan Liu; Lamont R Poole; Michael C Pitts; Jayanta Kar; Brian E Magill
Journal:  Atmos Meas Tech       Date:  2018       Impact factor: 4.176

  1 in total

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