Liquid Phase Cloud Microphysical Property Estimates From CALIPSO Measurements

Yongxiang Hu; Xiaomei Lu; Peng-Wang Zhai; Chris A. Hostetler; Johnathan W. Hair; Brian Cairns; Wenbo Sun; Snorre Stamnes; Ali Omar; Rosemary Baize; Gorden Videen; Gorden Videen; Jay Mace; Daniel T. McCoy; Isabel L. McCoy; Isabel L. McCoy; Isabel L. McCoy; Robert Wood

doi:10.3389/frsen.2021.724615

Frontiers in Remote Sensing (Sep 2021)

Liquid Phase Cloud Microphysical Property Estimates From CALIPSO Measurements

Yongxiang Hu,
Xiaomei Lu,
Peng-Wang Zhai,
Chris A. Hostetler,
Johnathan W. Hair,
Brian Cairns,
Wenbo Sun,
Snorre Stamnes,
Ali Omar,
Rosemary Baize,
Gorden Videen,
Gorden Videen,
Jay Mace,
Daniel T. McCoy,
Isabel L. McCoy,
Isabel L. McCoy,
Isabel L. McCoy,
Robert Wood

Affiliations

Yongxiang Hu: Science Directorate, NASA Langley Research Center, Hampton, VA, United States
Xiaomei Lu: Science Directorate, NASA Langley Research Center, Hampton, VA, United States
Peng-Wang Zhai: Physics Department, University of Maryland, Baltimore County, Baltimore, MD, United States
Chris A. Hostetler: Science Directorate, NASA Langley Research Center, Hampton, VA, United States
Johnathan W. Hair: Science Directorate, NASA Langley Research Center, Hampton, VA, United States
Brian Cairns: NASA Goddard Institute for Space Studies, New York, NY, United States
Wenbo Sun: Science Directorate, NASA Langley Research Center, Hampton, VA, United States
Snorre Stamnes: Science Directorate, NASA Langley Research Center, Hampton, VA, United States
Ali Omar: Science Directorate, NASA Langley Research Center, Hampton, VA, United States
Rosemary Baize: Science Directorate, NASA Langley Research Center, Hampton, VA, United States
Gorden Videen: Space Science Institute, Boulder Suite, CO, United States
Gorden Videen: US Army Research Laboratory, Adelphi, MD, United States
Jay Mace: Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT, United States
Daniel T. McCoy: Department of Atmospheric Science, University of Wyoming, Laramie, WY, United States
Isabel L. McCoy: Department of Atmospheric Sciences, University of Washington, Seattle, WA, United States
Isabel L. McCoy: Rosenstiel School of Marine and Atmospheric Sciences, University of Miami, Miami, FL, United States
Isabel L. McCoy: 0University Corporation for Atmospheric Research, Boulder, CO, United States
Robert Wood: Department of Atmospheric Sciences, University of Washington, Seattle, WA, United States

DOI: https://doi.org/10.3389/frsen.2021.724615
Journal volume & issue: Vol. 2

Abstract

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A neural-network algorithm that uses CALIPSO lidar measurements to infer droplet effective radius, extinction coefficient, liquid-water content, and droplet number concentration for water clouds is described and assessed. These results are verified against values inferred from High-Spectral-Resolution Lidar (HSRL) and Research Scanning Polarimeter (RSP) measurements made on an aircraft that flew under CALIPSO. The global cloud microphysical properties are derived from 14+ years of CALIPSO lidar measurements, and the droplet sizes are compared to corresponding values inferred from MODIS passive imagery. This new product will provide constraints to improve modeling of Earth’s water cycle and cloud-climate interactions.

Published in Frontiers in Remote Sensing

ISSN: 2673-6187 (Online)
Publisher: Frontiers Media S.A.
Country of publisher: Switzerland
LCC subjects: Science: Physics: Geophysics. Cosmic physics; Science: Physics: Meteorology. Climatology
Website: https://www.frontiersin.org/journals/remote-sensing

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