Abstract
Abstract. A method to distinguish cloud thermodynamic phase from polarized Micro Pulse Lidar (MPL) measurements is described. The method employs a simple enumerative approach to classify cloud layers as either liquid water, ice water, or mixed-phase clouds based on the linear volume depolarization ratio and cloud top temperatures derived from Goddard Earth Observing System, version 5 (GEOS-5), assimilated data. Two years of cloud retrievals from the Micro Pulse Lidar Network (MPLNET) site in Greenbelt, MD, are used to evaluate the performance of the algorithm. The fraction of supercooled liquid water in the mixed-phase temperature regime (−37–0 ∘C) calculated using MPLNET data is compared to similar calculations made using the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite, with reasonable consistency.
Highlights
Due to their high temporal and vertical resolutions and unique spectral sensitivity, lidars are key instruments for atmospheric profiling of gaseous species, aerosols, and translucent clouds
It is noted that multiple scattering induces an increase in the apparent linear depolarization ratio (LDR) measured increasingly further into the clouds (Sassen and Petrilla, 1986; Sassen, 1991; Hu et al, 2006), which can lead to values for liquid water clouds approaching the threshold for ice water clouds with increasing depth
The goal here is to present a method by which ice water, liquid water, and mixed-phase clouds can be identified from polarized Micro Pulse Lidar (MPL) measurements to fully describe the cloud thermodynamic phase
Summary
Due to their high temporal and vertical resolutions and unique spectral sensitivity, lidars are key instruments for atmospheric profiling of gaseous species, aerosols, and translucent clouds. Liquid water clouds are broadly characterized by relatively warmer temperatures, smaller droplet sizes, and higher number concentrations. They are more efficient at reflecting shortwave radiation and are generally associated with an overall negative cloud radiative effect (CRE) or cooling (Yi et al, 2017). Ice water clouds (and cirrus clouds) are broadly characterized by colder temperatures, larger particle sizes, and lower number concentrations They can be more efficient at trapping longwave radiation and are generally associated with an overall positive CRE or warming, though its magnitude and sign exhibit latitudinal and daytime temporal diurnal variations (Campbell et al, 2016; Lolli et al, 2017; Campbell et al, 2020). The goal here is to present a method by which ice water, liquid water, and mixed-phase clouds can be identified from polarized MPL measurements to fully describe the cloud thermodynamic phase
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