Articles | Volume 14, issue 5
https://doi.org/10.5194/amt-14-3253-2021
https://doi.org/10.5194/amt-14-3253-2021
Research article
 | 
04 May 2021
Research article |  | 04 May 2021

Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part I: The retrieval algorithms

Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell

Related authors

Advances in CALIPSO (IIR) cirrus cloud property retrievals – Part 1: Methods and testing
David L. Mitchell, Anne Emilie Garnier, and Sarah Woods
EGUsphere, https://doi.org/10.5194/egusphere-2024-3790,https://doi.org/10.5194/egusphere-2024-3790, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Advances in CALIPSO (IIR) cirrus cloud property retrievals – Part 2: Global estimates of the fraction of cirrus clouds affected by homogeneous ice nucleation
David L. Mitchell and Anne Garnier
EGUsphere, https://doi.org/10.5194/egusphere-2024-3814,https://doi.org/10.5194/egusphere-2024-3814, 2024
Short summary
A Level 3 monthly gridded ice cloud dataset derived from 12 years of CALIOP measurements
David Winker, Xia Cai, Mark Vaughan, Anne Garnier, Brian Magill, Melody Avery, and Brian Getzewich
Earth Syst. Sci. Data, 16, 2831–2855, https://doi.org/10.5194/essd-16-2831-2024,https://doi.org/10.5194/essd-16-2831-2024, 2024
Short summary
Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations
Jianyu Zheng, Zhibo Zhang, Hongbin Yu, Anne Garnier, Qianqian Song, Chenxi Wang, Claudia Di Biagio, Jasper F. Kok, Yevgeny Derimian, and Claire Ryder
Atmos. Chem. Phys., 23, 8271–8304, https://doi.org/10.5194/acp-23-8271-2023,https://doi.org/10.5194/acp-23-8271-2023, 2023
Short summary
Assessing the benefits of Imaging Infrared Radiometer observations for the CALIOP version 4 cloud and aerosol discrimination algorithm
Thibault Vaillant de Guélis, Gérard Ancellet, Anne Garnier, Laurent C.-Labonnote, Jacques Pelon, Mark A. Vaughan, Zhaoyan Liu, and David M. Winker
Atmos. Meas. Tech., 15, 1931–1956, https://doi.org/10.5194/amt-15-1931-2022,https://doi.org/10.5194/amt-15-1931-2022, 2022
Short summary

Related subject area

Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Retrieving cloud-base height and geometric thickness using the oxygen A-band channel of GCOM-C/SGLI
Takashi M. Nagao, Kentaroh Suzuki, and Makoto Kuji
Atmos. Meas. Tech., 18, 773–792, https://doi.org/10.5194/amt-18-773-2025,https://doi.org/10.5194/amt-18-773-2025, 2025
Short summary
Discriminating between “drizzle or rain” and sea salt aerosols in Cloudnet for measurements over the Barbados Cloud Observatory
Johanna Roschke, Jonas Witthuhn, Marcus Klingebiel, Moritz Haarig, Andreas Foth, Anton Kötsche, and Heike Kalesse-Los
Atmos. Meas. Tech., 18, 487–508, https://doi.org/10.5194/amt-18-487-2025,https://doi.org/10.5194/amt-18-487-2025, 2025
Short summary
Cancellation of cloud shadow effects in the absorbing aerosol index retrieval algorithm of TROPOMI
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech., 18, 73–91, https://doi.org/10.5194/amt-18-73-2025,https://doi.org/10.5194/amt-18-73-2025, 2025
Short summary
Optimal estimation of cloud properties from thermal infrared observations with a combination of deep learning and radiative transfer simulation
He Huang, Quan Wang, Chao Liu, and Chen Zhou
Atmos. Meas. Tech., 17, 7129–7141, https://doi.org/10.5194/amt-17-7129-2024,https://doi.org/10.5194/amt-17-7129-2024, 2024
Short summary
3D cloud masking across a broad swath using multi-angle polarimetry and deep learning
Sean R. Foley, Kirk D. Knobelspiesse, Andrew M. Sayer, Meng Gao, James Hays, and Judy Hoffman
Atmos. Meas. Tech., 17, 7027–7047, https://doi.org/10.5194/amt-17-7027-2024,https://doi.org/10.5194/amt-17-7027-2024, 2024
Short summary

Cited articles

AERIS/ICARE: Homepage, available at: http://www.icare.univ-lille.fr, last access: 22 April 2021. 
Avery, M. A., Ryan, R. A., Getzewich, B. J., Vaughan, M. A., Winker, D. M., Hu, Y., Garnier, A., Pelon, J., and Verhappen, C. A.: CALIOP V4 cloud thermodynamic phase assignment and the impact of near-nadir viewing angles, Atmos. Meas. Tech., 13, 4539–4563, https://doi.org/10.5194/amt-13-4539-2020, 2020. 
Baum, B. A., Yang, P., Heymsfield, A. J., Schmitt, C. G., Xie, Y., Bansemer, A., Hu, Y.-X., and Zhang, Z.: Improvements in shortwave bulk scattering and absorption models for the remote sensing of ice clouds, J. Appl. Meteorol. Climatol., 50, 1037–1056, https://doi.org/10.1175/2010JAMC2608.1, 2011. 
Bi, L. and Yang, P.: Improved ice particle optical property simulations in the ultraviolet to far-infrared regime, J. Quant. Spectrosc. Radiat. Transfer, 189, 228–237, https://doi.org/10.1016/j.jqsrt.2016.12.007, 2017. 
Bodas-Salcedo, A., Hill, P. G., Furtado, K., Williams, K. D., Field, P. R., Manners, J. C., Hyder, P., and Kato, S.: Large contribution of supercooled liquid clouds to the solar radiation budget of the Southern Ocean, J. Climate, 29, 4213–4228, https://doi.org/10.1175/JCLI-D-15-0564.1, 2016. 
Short summary
The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results are presented in a companion paper (Part II).
Share