Liquid Phase Cloud Microphysical Property Estimates From CALIPSO Measurements

Thumbnail Image

Files

frsen-02-724615.pdf (5.96 MB)

Links to Files

https://www.frontiersin.org/articles/10.3389/frsen.2021.724615/full

Permanent Link

https://doi.org/10.3389/frsen.2021.724615
 http://hdl.handle.net/11603/24317

Collections

UMBC Joint Center for Earth Systems Technology (JCET)
UMBC Faculty Collection
UMBC Physics Department

Author/Creator

Author/Creator ORCID

https://orcid.org/0000-0003-4695-5200

Date

2021-09-08

Type of Work

journal articles
Text

Department

Program

Citation of Original Publication

Hu Y, Lu X, Zhai P-W, Hostetler CA, Hair JW, Cairns B, Sun W, Stamnes S, Omar A, Baize R, Videen G, Mace J, McCoy DT, McCoy IL and Wood R (2021) Liquid Phase Cloud Microphysical Property Estimates From CALIPSO Measurements. Front. Remote Sens. 2:724615. doi: 10.3389/frsen.2021.724615

Rights

This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
Public Domain Mark 1.0

Subjects

Abstract

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.