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

TITLE=Liquid Phase Cloud Microphysical Property Estimates From CALIPSO Measurements

JOURNAL=Frontiers in Remote Sensing

VOLUME=2

YEAR=2021

URL=https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2021.724615

DOI=10.3389/frsen.2021.724615

ISSN=2673-6187

ABSTRACT=<p>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.</p>