Articles | Volume 13, issue 8
https://doi.org/10.5194/amt-13-4539-2020
© Author(s) 2020. 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-13-4539-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Aug 2020
Research article |
| 25 Aug 2020
CALIOP V4 cloud thermodynamic phase assignment and the impact of near-nadir viewing angles
NASA Langley Research Center, Atmospheric Composition Branch, Hampton,
VA 23681, USA
Robert A. Ryan
Science Systems Applications Inc., 1 Enterprise Pkwy, Hampton, VA 23666, USA
Brian J. Getzewich
Science Systems Applications Inc., 1 Enterprise Pkwy, Hampton, VA 23666, USA
Mark A. Vaughan
NASA Langley Research Center, Atmospheric Composition Branch, Hampton,
VA 23681, USA
David M. Winker
NASA Langley Research Center, Atmospheric Composition Branch, Hampton,
VA 23681, USA
Yongxiang Hu
NASA Langley Research Center, Atmospheric Composition Branch, Hampton,
VA 23681, USA
Anne Garnier
Science Systems Applications Inc., 1 Enterprise Pkwy, Hampton, VA 23666, USA
Jacques Pelon
Laboratoire Atmosphères, Milieux, Observations Spatiales,
UPMC-UVSQ-CNRS, Paris, France
Carolus A. Verhappen
Science Systems Applications Inc., 1 Enterprise Pkwy, Hampton, VA 23666, USA
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- Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part II: Results over oceans A. Garnier et al. 10.5194/amt-14-3277-2021
- Sensitivity of Mixed-Phase Cloud Optical Properties to Cloud Particle Model and Microphysical Factors at Wavelengths from 0.2 to 100 µm Q. Luo et al. 10.3390/rs13122330
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- Horizontally oriented ice crystals observed by the synergy of zenith- and slant-pointed polarization lidar over Wuhan (30.5°N, 114.4°E), China Y. He et al. 10.1016/j.jqsrt.2021.107626
- Fengyun-3D/MERSI-II Cloud Thermodynamic Phase Determination Using a Machine-Learning Approach D. Zhao et al. 10.3390/rs13122251
- Identifying Aerosol Subtypes from CALIPSO Lidar Profiles Using Deep Machine Learning S. Zeng et al. 10.3390/atmos12010010
- An extended lidar-based cirrus cloud retrieval scheme: first application over an Arctic site K. Nakoudi et al. 10.1364/OE.414770
- Global aerosol vertical structure analysis by clustering gridded CALIOP aerosol profiles with fuzzy k-means L. Wang et al. 10.1016/j.scitotenv.2020.144076
- Improvement in cloud retrievals from VIIRS through the use of infrared absorption channels constructed from VIIRS+CrIS data fusion Y. Li et al. 10.5194/amt-13-4035-2020
11 citations as recorded by crossref.
- Wildfire smoke, Arctic haze, and aerosol effects on mixed-phase and cirrus clouds over the North Pole region during MOSAiC: an introduction R. Engelmann et al. 10.5194/acp-21-13397-2021
- Determining AHI Cloud-Top Phase and Intercomparisons With MODIS Products Over North Pacific X. Zhuge et al. 10.1109/TGRS.2020.2990955
- Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part II: Results over oceans A. Garnier et al. 10.5194/amt-14-3277-2021
- Sensitivity of Mixed-Phase Cloud Optical Properties to Cloud Particle Model and Microphysical Factors at Wavelengths from 0.2 to 100 µm Q. Luo et al. 10.3390/rs13122330
- Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part I: The retrieval algorithms A. Garnier et al. 10.5194/amt-14-3253-2021
- Hemispheric and Seasonal Contrast in Cloud Thermodynamic Phase From A‐Train Spaceborne Instruments D. Villanueva et al. 10.1029/2020JD034322
- Horizontally oriented ice crystals observed by the synergy of zenith- and slant-pointed polarization lidar over Wuhan (30.5°N, 114.4°E), China Y. He et al. 10.1016/j.jqsrt.2021.107626
- Fengyun-3D/MERSI-II Cloud Thermodynamic Phase Determination Using a Machine-Learning Approach D. Zhao et al. 10.3390/rs13122251
- Identifying Aerosol Subtypes from CALIPSO Lidar Profiles Using Deep Machine Learning S. Zeng et al. 10.3390/atmos12010010
- An extended lidar-based cirrus cloud retrieval scheme: first application over an Arctic site K. Nakoudi et al. 10.1364/OE.414770
- Global aerosol vertical structure analysis by clustering gridded CALIOP aerosol profiles with fuzzy k-means L. Wang et al. 10.1016/j.scitotenv.2020.144076
Latest update: 01 Jun 2023
Short summary
CALIOP data users will find more cloud layers detected in V4, with edges that extend further than in V3, for an increase in total atmospheric cloud volume of 6 %–9 % for high-confidence cloud phases and 1 %–2 % for all cloudy bins, including cloud fringes and unknown cloud phases. In V4 there are many fewer cloud layers identified as horizontally oriented ice, particularly in the 3° off-nadir view. Depolarization at 532 nm is the predominant parameter determining cloud thermodynamic phase.
CALIOP data users will find more cloud layers detected in V4, with edges that extend further...
Special issue