Articles | Volume 25, issue 20
https://doi.org/10.5194/acp-25-14071-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-14071-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Oct 2025
Research article |
| 29 Oct 2025
| 29 Oct 2025
Advances in CALIPSO (IIR) cirrus cloud property retrievals – Part 1: Methods and testing
Desert Research Institute, Reno, NV 89512-1095, USA
Anne Garnier
RSES, Analytical Mechanics Associates, Hampton, VA 23666, USA
Sarah Woods
SPEC, Inc., Boulder, CO 80301, USA,
now at: NSF NCAR, Boulder, CO 80301, USA
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David L. Mitchell and Anne Garnier
Atmos. Chem. Phys., 25, 14099–14129, https://doi.org/10.5194/acp-25-14099-2025, https://doi.org/10.5194/acp-25-14099-2025, 2025
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Arguably the greatest knowledge gap in cirrus cloud research is the relative roles of homogeneous and heterogeneous ice nucleation in cirrus cloud formation. Since this depends on temperature, latitude, season and topography, a satellite remote sensing method was developed to measure cirrus cloud properties. It was found that cirrus clouds strongly affected by homogeneous ice nucleation may account for over half of the overall cirrus cloud radiative effect during winter outside the tropics.
Ehsan Erfani and David L. Mitchell
EGUsphere, https://doi.org/10.5194/egusphere-2025-1165, https://doi.org/10.5194/egusphere-2025-1165, 2025
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Cirrus clouds play a key role in Earth’s climate by trapping heat. We use satellite data and radiative transfer modeling to explore how thinning these clouds could help cool the planet. It is shown that thinning cirrus clouds could significantly reduce warming, with the strongest effects in the polar regions during winter. These results improve our understanding of how clouds influence climate and could guide future efforts to combat global warming via climate intervention.
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3253–3276, https://doi.org/10.5194/amt-14-3253-2021, https://doi.org/10.5194/amt-14-3253-2021, 2021
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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).
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3277–3299, https://doi.org/10.5194/amt-14-3277-2021, https://doi.org/10.5194/amt-14-3277-2021, 2021
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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 II) shows retrievals over ocean and describes the improvements made with respect to version 3 as a result of the significant changes implemented in the version 4 algorithms, which are presented in a companion paper (Part I).
David L. Mitchell and Anne Garnier
Atmos. Chem. Phys., 25, 14099–14129, https://doi.org/10.5194/acp-25-14099-2025, https://doi.org/10.5194/acp-25-14099-2025, 2025
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Arguably the greatest knowledge gap in cirrus cloud research is the relative roles of homogeneous and heterogeneous ice nucleation in cirrus cloud formation. Since this depends on temperature, latitude, season and topography, a satellite remote sensing method was developed to measure cirrus cloud properties. It was found that cirrus clouds strongly affected by homogeneous ice nucleation may account for over half of the overall cirrus cloud radiative effect during winter outside the tropics.
Travis Toth, Gregory Schuster, Marian Clayton, Zhujun Li, David Painemal, Sharon Rodier, Jayanta Kar, Tyler Thorsen, Richard Ferrare, Mark Vaughan, Jason Tackett, Huisheng Bian, Mian Chin, Anne Garnier, Ellsworth Welton, Robert Ryan, Charles Trepte, and David Winker
EGUsphere, https://doi.org/10.5194/egusphere-2025-2832, https://doi.org/10.5194/egusphere-2025-2832, 2025
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NASA’s CALIPSO satellite mission observed aerosols (airborne particles) globally from 2006 to 2023. Its final data products update improves its aerosol optical parameters over oceans by adjusting for regional and seasonal differences in a new measurement-model synergistic approach. This results in a more realistic aerosol characterization, specifically near coastlines (where sea salt mixes with pollution), with potential impacts to future studies of science applications (e.g., climate effects).
Derek Ngo, Minghui Diao, Ryan J. Patnaude, Sarah Woods, and Glenn Diskin
Atmos. Chem. Phys., 25, 7007–7036, https://doi.org/10.5194/acp-25-7007-2025, https://doi.org/10.5194/acp-25-7007-2025, 2025
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Key controlling factors of cirrus clouds were individually quantified using machine learning models based on global-scale in situ observations from 12 campaigns at 67° S–87° N. Relative humidity shows much larger effects on cirrus occurrences and ice water content (IWC) fluctuations than vertical velocity. Aerosol–cloud interactions are seen for both large and small aerosols, with higher IWC and ice crystal number concentration under higher aerosol concentrations. Large aerosols are more impactful than small aerosols.
Jason L. Tackett, Robert A. Ryan, Anne E. Garnier, Jayanta Kar, Brian J. Getzewich, Xia Cai, Mark A. Vaughan, Charles R. Trepte, Ron C. Verhappen, David M. Winker, and Kam-Pui A. Lee
EGUsphere, https://doi.org/10.5194/egusphere-2025-2376, https://doi.org/10.5194/egusphere-2025-2376, 2025
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The spaceborne atmospheric lidar CALIOP experienced an increasing number of intermittent low energy laser pulses in the final seven years of the 17-year long CALIPSO mission. Low energy pulses degraded the quality of retrievals in affected profiles. This paper describes low energy mitigation (LEM) algorithms that remove affected data and minimize data loss. LEM is demonstrated to correct calibration biases, reduce false feature detections, and restore the integrity of the CALIOP data record.
Ehsan Erfani and David L. Mitchell
EGUsphere, https://doi.org/10.5194/egusphere-2025-1165, https://doi.org/10.5194/egusphere-2025-1165, 2025
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Cirrus clouds play a key role in Earth’s climate by trapping heat. We use satellite data and radiative transfer modeling to explore how thinning these clouds could help cool the planet. It is shown that thinning cirrus clouds could significantly reduce warming, with the strongest effects in the polar regions during winter. These results improve our understanding of how clouds influence climate and could guide future efforts to combat global warming via climate intervention.
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
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Clouds play important roles in both weather and climate. In this paper we describe version 1.0 of a unique global ice cloud data product derived from over 12 years of global spaceborne lidar measurements. This monthly gridded product provides a unique vertically resolved characterization of the occurrence and properties, optical and physical, of thin ice clouds and the tops of deep convective clouds. It should provide significant value for cloud research and model evaluation.
Rose Marie Miller, Robert M. Rauber, Larry Di Girolamo, Matthew Rilloraza, Dongwei Fu, Greg M. McFarquhar, Stephen W. Nesbitt, Luke D. Ziemba, Sarah Woods, and Kenneth Lee Thornhill
Atmos. Chem. Phys., 23, 8959–8977, https://doi.org/10.5194/acp-23-8959-2023, https://doi.org/10.5194/acp-23-8959-2023, 2023
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The influence of human-produced aerosols on clouds remains one of the uncertainties in radiative forcing of Earth’s climate. Measurements of aerosol chemistry from sources around the Philippines illustrate the linkage between aerosol chemical composition and cloud droplet characteristics. Differences in aerosol chemical composition in the marine layer from biomass burning, industrial, ship-produced, and marine aerosols are shown to impact cloud microphysical structure just above cloud base.
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
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We developed a multi-year satellite-based retrieval of dust optical depth at 10 µm and the coarse-mode dust effective diameter over global oceans. It reveals climatological coarse-mode dust transport patterns and regional differences over the North Atlantic, the Indian Ocean and the North Pacific.
Ewan Crosbie, Luke D. Ziemba, Michael A. Shook, Claire E. Robinson, Edward L. Winstead, K. Lee Thornhill, Rachel A. Braun, Alexander B. MacDonald, Connor Stahl, Armin Sorooshian, Susan C. van den Heever, Joshua P. DiGangi, Glenn S. Diskin, Sarah Woods, Paola Bañaga, Matthew D. Brown, Francesca Gallo, Miguel Ricardo A. Hilario, Carolyn E. Jordan, Gabrielle R. Leung, Richard H. Moore, Kevin J. Sanchez, Taylor J. Shingler, and Elizabeth B. Wiggins
Atmos. Chem. Phys., 22, 13269–13302, https://doi.org/10.5194/acp-22-13269-2022, https://doi.org/10.5194/acp-22-13269-2022, 2022
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The linkage between cloud droplet and aerosol particle chemical composition was analyzed using samples collected in a polluted tropical marine environment. Variations in the droplet composition were related to physical and dynamical processes in clouds to assess their relative significance across three cases that spanned a range of rainfall amounts. In spite of the pollution, sea salt still remained a major contributor to the droplet composition and was preferentially enhanced in rainwater.
Eva-Lou Edwards, Jeffrey S. Reid, Peng Xian, Sharon P. Burton, Anthony L. Cook, Ewan C. Crosbie, Marta A. Fenn, Richard A. Ferrare, Sean W. Freeman, John W. Hair, David B. Harper, Chris A. Hostetler, Claire E. Robinson, Amy Jo Scarino, Michael A. Shook, G. Alexander Sokolowsky, Susan C. van den Heever, Edward L. Winstead, Sarah Woods, Luke D. Ziemba, and Armin Sorooshian
Atmos. Chem. Phys., 22, 12961–12983, https://doi.org/10.5194/acp-22-12961-2022, https://doi.org/10.5194/acp-22-12961-2022, 2022
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This study compares NAAPS-RA model simulations of aerosol optical thickness (AOT) and extinction to those retrieved with a high spectral resolution lidar near the Philippines. Agreement for AOT was good, and extinction agreement was strongest below 1500 m. Substituting dropsonde relative humidities into NAAPS-RA did not drastically improve agreement, and we discuss potential reasons why. Accurately modeling future conditions in this region is crucial due to its susceptibility to climate change.
Dongwei Fu, Larry Di Girolamo, Robert M. Rauber, Greg M. McFarquhar, Stephen W. Nesbitt, Jesse Loveridge, Yulan Hong, Bastiaan van Diedenhoven, Brian Cairns, Mikhail D. Alexandrov, Paul Lawson, Sarah Woods, Simone Tanelli, Sebastian Schmidt, Chris Hostetler, and Amy Jo Scarino
Atmos. Chem. Phys., 22, 8259–8285, https://doi.org/10.5194/acp-22-8259-2022, https://doi.org/10.5194/acp-22-8259-2022, 2022
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Satellite-retrieved cloud microphysics are widely used in climate research because of their central role in water and energy cycles. Here, we provide the first detailed investigation of retrieved cloud drop sizes from in situ and various satellite and airborne remote sensing techniques applied to real cumulus cloud fields. We conclude that the most widely used passive remote sensing method employed in climate research produces high biases of 6–8 µm (60 %–80 %) caused by 3-D radiative effects.
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
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A new IIR-based cloud and aerosol discrimination (CAD) algorithm is developed using the IIR brightness temperature differences for cloud and aerosol features confidently identified by the CALIOP version 4 CAD algorithm. IIR classifications agree with the majority of V4 cloud identifications, reduce the ambiguity in a notable fraction of
not confidentV4 cloud classifications, and correct a few V4 misclassifications of cloud layers identified as dense dust or elevated smoke layers by CALIOP.
Youssef Wehbe, Sarah A. Tessendorf, Courtney Weeks, Roelof Bruintjes, Lulin Xue, Roy Rasmussen, Paul Lawson, Sarah Woods, and Marouane Temimi
Atmos. Chem. Phys., 21, 12543–12560, https://doi.org/10.5194/acp-21-12543-2021, https://doi.org/10.5194/acp-21-12543-2021, 2021
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The role of dust aerosols as ice-nucleating particles is well established in the literature, whereas their role as cloud condensation nuclei is less understood, particularly in polluted desert environments. We analyze coincident aerosol size distributions and cloud particle imagery collected over the UAE with a research aircraft. Despite the presence of ultra-giant aerosol sizes associated with dust, an active collision–coalescence process is not observed within the limited depths of warm cloud.
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3253–3276, https://doi.org/10.5194/amt-14-3253-2021, https://doi.org/10.5194/amt-14-3253-2021, 2021
Short summary
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).
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3277–3299, https://doi.org/10.5194/amt-14-3277-2021, https://doi.org/10.5194/amt-14-3277-2021, 2021
Short summary
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 II) shows retrievals over ocean and describes the improvements made with respect to version 3 as a result of the significant changes implemented in the version 4 algorithms, which are presented in a companion paper (Part I).
Martina Krämer, Christian Rolf, Nicole Spelten, Armin Afchine, David Fahey, Eric Jensen, Sergey Khaykin, Thomas Kuhn, Paul Lawson, Alexey Lykov, Laura L. Pan, Martin Riese, Andrew Rollins, Fred Stroh, Troy Thornberry, Veronika Wolf, Sarah Woods, Peter Spichtinger, Johannes Quaas, and Odran Sourdeval
Atmos. Chem. Phys., 20, 12569–12608, https://doi.org/10.5194/acp-20-12569-2020, https://doi.org/10.5194/acp-20-12569-2020, 2020
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To improve the representations of cirrus clouds in climate predictions, extended knowledge of their properties and geographical distribution is required. This study presents extensive airborne in situ and satellite remote sensing climatologies of cirrus and humidity, which serve as a guide to cirrus clouds. Further, exemplary radiative characteristics of cirrus types and also in situ observations of tropical tropopause layer cirrus and humidity in the Asian monsoon anticyclone are shown.
Cited articles
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.
Baker, B. and Lawson, R. P.: Improvement in Determination of Ice Water Content from Two-Dimensional Particle Imagery. Part I: Image-to-Mass Relationships, J. Appl. Meteorol. Clim., 45, 1282–1290, https://doi.org/10.1175/JAM2398.1, 2006.
Baker, B., Mo, Q., Lawson, R. P., Korolev, A., and O'Connor, D.: Drop size distributions and the lack of small drops in RICO rain shafts, J. Atmos. Sci., 48, 616–623, https://doi.org/10.1175/2008JAMC1934.1, 2009.
Barahona, D. and Nenes, A.: Parameterizing the competition between homogeneous and heterogeneous freezing in ice cloud formation – polydisperse ice nuclei, Atmos. Chem. Phys., 9, 5933–5948, https://doi.org/10.5194/acp-9-5933-2009, 2009.
Cziczo, D. J., Froyd, K. D., Hoose, C., Jensen, E. J., Diao, M., Zondlo, M.A., Smith, J. B., Twohy, C. H., and Murphy, D. M.: Clarifying the dominant sources and mechanisms of cirrus cloud formation, Science, 340, 1320–1324, https://doi.org/10.1126/science.1234145, 2013.
Delanoë, J. and Hogan, R. J.: Combined CloudSat-CALIPSO-MODIS retrievals of the properties of ice clouds, J. Geophys. Res.-Atmos., 115, D00H29, https://doi.org/10.1029/2009JD012346, 2010.
Delanoë, J., Heymsfield, A. J., Protat, A., Bansemer, A., and Hogan, R. J.: Normalized particle size distribution for remote sensing application, J. Geophys. Res., 119, 4204–4227, https://doi.org/10.1002/2013JD020700, 2014.
Eidhammer, T., Morrison, H., Mitchell, D., Gettelman, A., and Erfani, E.: Improvements in Global Climate Model Microphysics Using a Consistent Representation of Ice Particle Properties, J. Climate, 30, 609–629, https://doi.org/10.1175/JCLI-D-16-0050.1, 2017.
Erfani, E. and Mitchell, D. L.: Developing and bounding ice particle mass- and area-dimension expressions for use in atmospheric models and remote sensing, Atmos. Chem. Phys., 16, 4379–4400, https://doi.org/10.5194/acp-16-4379-2016, 2016.
Field, P. R. and Heymsfield, A. J.: Aggregation and Scaling of Ice Crystal Size Distributions, J. Atmos. Sci., 60, 544–560, https://doi.org/10.1175/1520-0469(2003)060<0544:AASOIC>2.0.CO;2, 2003.
Garnier, A., Pelon, J., Vaughan, M. A., Winker, D. M., Trepte, C. R., and Dubuisson, P.: Lidar multiple scattering factors inferred from CALIPSO lidar and IIR retrievals of semi-transparent cirrus cloud optical depths over oceans, Atmos. Meas. Tech., 8, 2759–2774, https://doi.org/10.5194/amt-8-2759-2015, 2015.
Garnier, A., Trémas, T., Pelon, J., Lee, K.-P., Nobileau, D., Gross-Colzy, L., Pascal, N., Ferrage, P., and Scott, N. A.: CALIPSO IIR Version 2 Level 1b calibrated radiances: analysis and reduction of residual biases in the Northern Hemisphere, Atmos. Meas. Tech., 11, 2485–2500, https://doi.org/10.5194/amt-11-2485-2018, 2018.
Garnier, A., Pelon, J., Pascal, N., Vaughan, M. A., Dubuisson, P., Yang, P., and Mitchell, D. L.: Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part I: The retrieval algorithms, Atmos. Meas. Tech., 14, 3253–3276, https://doi.org/10.5194/amt-14-3253-2021, 2021a.
Garnier, A., Pelon, J., Pascal, N., Vaughan, M. A., Dubuisson, P., Yang, P., and Mitchell, D. L.: Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part II: Results over oceans, Atmos. Meas. Tech., 14, 3277–3299, https://doi.org/10.5194/amt-14-3277-2021, 2021b.
Gasparini, B., Meyer, A., Neubauer, D., Münch, S., and Lohmann, U.: Cirrus Cloud Properties as Seen by the CALIPSO Satellite and ECHAM-HAM Global Climate Model, J. Climate, 31, 1983-2003, https://doi.org/10.1175/JCLI-D-16-0608.1, 2018.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Glienke, S. and Mei, F.: Fast Cloud Droplet Probe (FCDP) Instrument Handbook, U.S. Department of Energy, Office of Science, DOE/SC-ARM-TR-238, https://doi.org/10.2172/1597469, 2020.
Haag, W., Kärcher, B., Ström, J., Minikin, A., Lohmann, U., Ovarlez, J., and Stohl, A.: Freezing thresholds and cirrus cloud formation mechanisms inferred from in situ measurements of relative humidity, Atmos. Chem. Phys., 3, 1791–1806, https://doi.org/10.5194/acp-3-1791-2003, 2003.
Heymsfield, A., Winker, D., Avery, M., Vaughan, M., Diskin, G., Deng, M., Mitev, V., and Matthey, R.: Relationships between Ice Water Content and Volume Extinction Coefficient from In Situ Observations for Temperatures from 0° to −86 °C: Implications for Spaceborne Lidar Retrievals, J. Appl. Meteor. Climatol., 53, 479–505, https://doi.org/10.1175/JAMC-D-13-087.1, 2014.
Hong, Y. and Liu, G.: The Characteristics of ice cloud properties derived from CloudSat and CALIPSO measurements, J. Climate, 28, 3880–3901, https://doi.org/10.1175/JCLI-D-14-00666.1, 2015.
Jensen, E. J., Pfister, L., and Bui, T. P.: Physical processes controlling ice concentrations in cold cirrus near the tropical tropopause, J. Geophys. Res., 117, D11205, https://doi.org/10.1029/2011JD017319, 2012.
Jensen, E. J., Lawson, R. P., Bergman, J. W., Pfister, L., Bui, T. P., and Schmitt, C. G.: Physical processes controlling ice concentrations in synoptically forced, midlatitude cirrus, J. Geophys. Res.-Atmos., 118, 5348–5360, https://doi.org/10.1002/jgrd.50421, 2013a.
Jensen, E. J., Diskin, G., Lawson, R. P., Lance, S., Bui, T. P., Hlavkad, D., McGille, M., Pfister, L., Toon, O. B., and Gao, R.: Ice nucleation and dehydration in the Tropical Tropopause Layer, P. Natl. Acad. Sci. USA, 110, 2041–2046, https://doi.org/10.1073/pnas.1217104110, 2013b.
Jensen, E. J., Pfister, L., Jordan, D. E., Bui, T. V., Ueyama, R., Singh, H. B., Thornberry, T. D., Rollins, A. W., Gao, R-S, Fahey, D. W., Rosenlof, K. H., Elkins, J. W., Diskin, G. S., DiGangi, J. P., Lawson, R. P., Woods, S., Atlas, E. L., Navarro Rodriguez, M. A., Wofsy, S. C., Pittman, J., Bardeen, C. G., Toon, O. B., Kindel, B. C., Newman, P. A., McGill, M. J., Hlavka, D. L., Lait, L. R., Schoeberl, M. R., Bergman, J. W., Selkirk, H. B., Alexander, M. J., Kim, J-E, Lim, B. H., Stutz, J., and Pfeilsticker, K.: The NASA Airborne Tropical Tropopause Experiment: High-Altitude Aircraft Measurements in the Tropical Western Pacific, B. Am. Meteor. Soc., 98, 129–143, https://doi.org/10.1175/BAMS-D-14-00263.1, 2017.
Koop, T., Luo, B., Tsias, A., and Peter, T.: Water activity as the determinant for homogeneous ice nucleation in aqueous solutions, Nature, 406, 611-614, https://doi.org/10.1038/35020537, 2000.
Krämer, M., Schiller, C., Afchine, A., Bauer, R., Gensch, I., Mangold, A., Schlicht, S., Spelten, N., Sitnikov, N., Borrmann, S., de Reus, M., and Spichtinger, P.: Ice supersaturations and cirrus cloud crystal numbers, Atmos. Chem. Phys., 9, 3505–3522, https://doi.org/10.5194/acp-9-3505-2009, 2009.
Krämer, M., Rolf, C., Luebke, A., Afchine, A., Spelten, N., Costa, A., Meyer, J., Zöger, M., Smith, J., Herman, R. L., Buchholz, B., Ebert, V., Baumgardner, D., Borrmann, S., Klingebiel, M., and Avallone, L.: A microphysics guide to cirrus clouds – Part 1: Cirrus types, Atmos. Chem. Phys., 16, 3463–3483, https://doi.org/10.5194/acp-16-3463-2016, 2016.
Krämer, M., Rolf, C., Spelten, N., Afchine, A., Fahey, D., Jensen, E., Khaykin, S., Kuhn, T., Lawson, P., Lykov, A., Pan, L. L., Riese, M., Rollins, A., Stroh, F., Thornberry, T., Wolf, V., Woods, S., Spichtinger, P., Quaas, J., and Sourdeval, O.: A microphysics guide to cirrus – Part 2: Climatologies of clouds and humidity from observations, Atmos. Chem. Phys., 20, 12569–12608, https://doi.org/10.5194/acp-20-12569-2020, 2020.
Lawson, R. P.: Effects of ice particles shattering on the 2D-S probe, Atmos. Meas. Tech., 4, 1361–1381, https://doi.org/10.5194/amt-4-1361-2011, 2011.
Lawson, R. P., Baker, B. A., Schmitt, C. G., and Jensen, T. L.: An overview of microphysical properties of Arctic clouds observed in May and July 1998 during FIRE ACE, J. Geophys. Res., 106, 14989–15014, https://doi.org/10.1029/2000JD900789, 2001.
Lawson, R. P., O'Connor, D., Zmarzly, P., Weaver, K., Baker, B. A., Mo, Q., and Jonsson, H.: The 2D-S (Stereo) Probe: Design and preliminary tests of a new airborne, high speed, high-resolution particle imaging probe, J. Atmos. Ocean. Tech., 23, 1462–1477, https://doi.org/10.1175/JTECH1927.1, 2006.
Lawson, P., Gurganus, C., Woods, S., and Bruintjes, R.: Aircraft Observations of Cumulus Microphysics Ranging from the Tropics to Midlatitudes: Implications for a “New” Secondary Ice Process, J. Atmos. Sci., 74, 2899–2920, https://doi.org/10.1175/JAS-D-17-0033.1, 2017.
Lawson, R. P., Woods, S., Jensen, E. Erfani, E., Gurganus, C., Gallagher, M., Connolly, P., Whiteway, J., Baran, A. J., May, P., Heymsfield, A., Schmitt, C. G., McFarquhar, G., Um, J., Protat, A., Bailey, M., Lance, S., Muehlbauer, A., Stith, J., Korolev, A., Toon, O. B., and Krämer, M.: A review of ice particle shapes in cirrus formed in situ and in anvils, J. Geophys. Res.-Atmos., 124, 10049–10090, https://doi.org/10.1029/2018JD030122, 2019.
Lu, X., Hu, Y., Liu, Z., Rodier, S., Vaughan, M., Lucker, P., Trepte, C., and Pelon, J.: Observations of Arctic snow and sea ice cover from CALIOP lidar measurements, Remote Sens. Environ., 194, 248–263, https://doi.org/10.1016/j.rse.2017.03.046, 2017.
Mitchell, D. L.: Evolution of snow-size spectra in cyclonic storms. Part I: Snow growth by vapor deposition and aggregation, J. Atmos. Sci., 45, 3431–3451, https://doi.org/10.1175/1520-0469(1988)045<3431:EOSSSI>2.0.CO;2, 1988.
Mitchell, D. L.: A model predicting the evolution of ice particle size spectra and radiative properties of cirrus clouds. Part 1: Microphysics, J. Atmos. Sci., 51, 797–816, https://doi.org/10.1175/1520-0469(1994)051<0797:AMPTEO>2.0.CO;2, 1994.
Mitchell, D. L.: Parameterization of the Mie extinction and absorption coefficients for water clouds, J. Atmos. Sci., 57, 1311–1326, https://doi.org/10.1175/1520-0469(2000)057<1311:POTMEA>2.0.CO;2, 2000.
Mitchell, D. L.: Effective diameter in radiation transfer: general definition, applications, and limitations, J. Atmos. Sci., 59, 2330–2346, https://doi.org/10.1175/1520-0469(2002)059<2330:edirtg>2.0.co;2, 2002.
Mitchell, D. L. and Garnier, A.: Advances in CALIPSO (IIR) cirrus cloud property retrievals – Part 2: Global estimates of the fraction of cirrus clouds affected by homogeneous ice nucleation, Atmos. Chem. Phys., 25, 14099–14129, https://doi.org/10.5194/acp-25-14099-2025, 2025.
Mitchell, D. L., Ivanova, D., Edwards, J. M., and McFarquhar, G. C.: A GCM parameterization of bimodal size spectra for ice clouds, Ninth ARM Science Team Meeting Proceedings, 22–26 March, San Antonio, Texas, 1999.
Mitchell, D. L., Baran, A. J., Arnott, W. P., and Schmitt, C.: Testing and comparing the modified anomalous diffraction approximation, J. Atmos. Sci., 63, 2948–2962, https://doi.org/10.1175/JAS3775.1, 2006.
Mitchell, D. L., Rasch, P., Ivanova, D., McFarquhar, G., and Nousiainen, T.: Impact of small ice crystal assumptions on ice sedimentation rates in cirrus clouds and GCM simulations, Geophys. Res. Lett., 35, L09806, https://doi.org/10.1029/2008GL033552, 2008.
Mitchell, D. L., D'Entremont, R. P., and Lawson, R. P.: Inferring Cirrus Size Distributions through Satellite Remote Sensing and Microphysical Databases, J. Atmos. Sci., 67, 1106–1125, https://doi.org/10.1175/2009JAS3150.1, 2010.
Mitchell, D. L., Lawson, R. P., and Baker, B.: Understanding effective diameter and its application to terrestrial radiation in ice clouds, Atmos. Chem. Phys., 11, 3417–3429, https://doi.org/10.5194/acp-11-3417-2011, 2011.
Mitchell, D. L., Garnier, A., Pelon, J., and Erfani, E.: CALIPSO (IIR–CALIOP) retrievals of cirrus cloud ice-particle concentrations, Atmos. Chem. Phys., 18, 17325–17354, https://doi.org/10.5194/acp-18-17325-2018, 2018.
Mitchell, D. L., Mejia, J., Garnier, A., Tomii, Y., Krämer, M., and Hosseinpour, F.: An Estimate of Global, Regional and Seasonal Cirrus Cloud Radiative Effects Contributed by Homogeneous Ice Nucleation, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2020-846, 2020.
Muhlbauer, A., Ackerman, T. P., Comstock, J. M., Diskin, G. S., Evans, S. M., Lawson, R. P., and Marchand, R. T.: Impact of large-scale dynamics on the microphysical properties of midlatitude cirrus, J. Geophys. Res.-Atmos., 119, 3976–3996, https://doi.org/10.1002/2013JD020035, 2014.
NASA/LARC/SD/ASDC: CALIPSO Infrared Imaging Radiometer (IIR) Level 2 Track, V4-51, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/IIR/CALIPSO/CAL_IIR_L2_Track-Standard-V4-51, 2023a.
NASA/LARC/SD/ASDC: CALIPSO Lidar Level 2 Cloud Profile, V4-51, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L2_05kmCPro-Standard-V4-51, 2023b.
Ngo, D., Diao, M., Patnaude, R. J., Woods, S., and Diskin, G.: Aerosol Indirect Effects on Cirrus Clouds Based on Global-Scale Airborne Observations and Machine Learning Models, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-2122, 2024.
Sanderson, B. M., Piani, C., Ingram, W. J., Stone, D. A., and Allen, M. R.: Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations, Clim. Dyn., 30, 175–190, https://doi.org/10.1007/s00382-007-0280-7, 2008.
Schoeberl, M. R., Jensen, E. J., Pfister, L., Ueyama, R., Wang, T., Selkirk, H., Avery, M., Thornberry, T., and Dessler, A. E.: Water vapor, clouds, and saturation in the tropical tropopause layer, J. Geophys. Res.-Atmos., 124, 3984–4003, https://doi.org/10.1029/2018JD029849, 2019.
Sourdeval, O., Gryspeerdt, E., Krämer, M., Goren, T., Delanoë, J., Afchine, A., Hemmer, F., and Quaas, J.: Ice crystal number concentration estimates from lidar–radar satellite remote sensing – Part 1: Method and evaluation, Atmos. Chem. Phys., 18, 14327–14350, https://doi.org/10.5194/acp-18-14327-2018, 2018.
Toon, O. B., Starr, D. O., Jensen, E. J., Newman, P. A., Platnick, S., Schoeberl, M. R., Wennberg, P. O., Wofsy, S. C., Kurylo, M. J., Maring, H., Jucks, K. W., Craig, M. S., Vasques, M. F., Pfister, L., Rosenlof, K. H., Selkirk, H. B., Colarco, P. R., Kawa, S. R., Mace, G. G., Minnis, P., and Pickering, K. E.: Planning, implementation, and first results of the Tropical Composition, Cloud and Climate Coupling Experiment (TC4), J. Geophys. Res., 115, D00J04, https://doi.org/10.1029/2009JD013073, 2010.
Vaughan, M., Pitts, M., Trepte, C., Winker, D., Getzewitch, B., Tackett, J., Cai, X., Garnier, A., Kar, J., Lee, K.-P., Lucker, P., Detweiler, P., Lambeth, J., Murray, T., Rodier, S., Ryan, R., Trémas, T., Pelon, J., and Flamant, C.: CALIPSO data management system data products catalog, document No. PC-SCI-503, Release 4.98, available at: http://www-calipso.larc.nasa.gov/products/CALIPSO_DPC_Rev4x98.pdf (last access: 17 October 2024), 2024.
Weitzel, M., Mitra, S. K., Szakáll, M., Fugal, J. P., and Borrmann, S.: Application of holography and automated image processing for laboratory experiments on mass and fall speed of small cloud ice crystals, Atmos. Chem. Phys., 20, 14889–14901, https://doi.org/10.5194/acp-20-14889-2020, 2020.
Woods, S., Lawson, P., Jensen, E., Thornberry, T., Rollins, A., Bui, P., Pfister, L., and Avery, M.: Microphysical Properties of Tropical Tropopause Layer Cirrus, J. Geophys. Res.-Atmos., https://doi.org/10.1029/2017JD028068, 2018.
Young, S. A., Vaughan, M. A., Garnier, A., Tackett, J. L., Lambeth, J. D., and Powell, K. A.: Extinction and optical depth retrievals for CALIPSO's Version 4 data release, Atmos. Meas. Tech., 11, 5701–5727, https://doi.org/10.5194/amt-11-5701-2018, 2018.
Short summary
Motivated by the need to better understand the physics of cirrus clouds, a satellite retrieval for cirrus cloud ice water content, ice particle number concentration and effective size was developed by exploiting relationships between cirrus cloud measurements made during field campaigns and cloud radiative properties measured by satellite. These retrievals tested favorably when compared against corresponding aircraft measurements and were found to depend on the visual opacity of the cloud.
Motivated by the need to better understand the physics of cirrus clouds, a satellite retrieval...
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