Abstract

AbstractSix deep convective systems (DCSs) with a total of 5589 five‐second samples and a range of temperatures from −41°C to 0°C during the Midlatitude Continental Convective Clouds Experiment (MC3E) were selected to investigate the ice cloud microphysical properties of DCSs over the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. The ice cloud measurements of the DCS cases were made by the University of North Dakota Citation II research aircraft, and the ice cloud properties were derived through the following processes. First, the instances of supercooled liquid water in the ice‐dominated cloud layers of DCSs have been eliminated using multisensor detection, including the Rosemount Icing Detector, King and Cloud Droplet Probes, as well as 2DC and Cloud Imaging Probe images. Then the Nevzorov‐measured ice water contents (IWCs) at maximum diameter Dmax < 4000 µm are used as the best estimation to determine a new mass‐dimensional relationship. Finally, the newly derived mass‐dimensional relationship (a = 0.00365, b = 2.1) has been applied to a full spectrum of particle size distributions (PSDs, 120–30,000 µm) constructed from both 2DC and High‐Volume Precipitation Spectrometer measurements to calculate the best‐estimated IWCs of DCSs during MC3E. The averages of the total number concentrations (Nt), median mass diameter (Dm), maximum diameter (Dmax), and IWC from six selected cases are 0.035 cm−3, 1666 µm, 8841 µm, and 0.45 g m−3, respectively. The gamma‐type‐size distributions are then generated matching the observed PSDs (120–30,000 µm), and the fitted gamma parameters are compared with the observed PSDs through multimoment assessments including first moment (Dm), third moment (IWC), and sixth moment (equivalent radar reflectivity, Ze). For application of observed PSDs to the remote sensing community, a series of empirical relationships between fitted parameters and Ze values has been derived, and the bullet rosette ice crystal backscattering relationship has been suggested for ground‐based remote sensing.

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