Articles | Volume 11, issue 11
https://doi.org/10.5194/amt-11-6107-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-11-6107-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The CALIPSO version 4 automated aerosol classification and lidar ratio selection algorithm
Man-Hae Kim
CORRESPONDING AUTHOR
NASA Postdoctoral Program (USRA), Hampton, VA, USA
Ali H. Omar
NASA Langley Research Center, Hampton, VA, USA
Jason L. Tackett
Science Systems and Applications, Inc., Hampton, VA, USA
Mark A. Vaughan
NASA Langley Research Center, Hampton, VA, USA
David M. Winker
NASA Langley Research Center, Hampton, VA, USA
Charles R. Trepte
NASA Langley Research Center, Hampton, VA, USA
Yongxiang Hu
NASA Langley Research Center, Hampton, VA, USA
Zhaoyan Liu
NASA Langley Research Center, Hampton, VA, USA
Lamont R. Poole
Science Systems and Applications, Inc., Hampton, VA, USA
Michael C. Pitts
NASA Langley Research Center, Hampton, VA, USA
Jayanta Kar
Science Systems and Applications, Inc., Hampton, VA, USA
Brian E. Magill
Science Systems and Applications, Inc., Hampton, VA, USA
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Saved (final revised paper)
Latest update: 14 May 2026
Short summary
This paper discusses recent advances made in distinguishing among different aerosols species detected in the CALIPSO lidar measurements. A new classification algorithm now classifies four different aerosol types in the stratosphere, and the number of aerosol types recognized in the troposphere has increased from six to seven. The lidar ratios characterizing each type have been updated and the effects of these changes on CALIPSO retrievals of aerosol optical depth are examined in detail.
This paper discusses recent advances made in distinguishing among different aerosols species...
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