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Understanding Ice Cloud‐Precipitation Properties of Three Modes of Mesoscale Convective Systems During PECAN
Author(s) -
Cui Wenjun,
Dong Xiquan,
Xi Baike,
Fan Jiwen,
Tian Jingjing,
Wang Jingyu,
McHardy Theodore M.
Publication year - 2019
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1029/2019jd030330
Subject(s) - mesoscale meteorology , convection , precipitation , squall line , mesoscale convective system , atmospheric sciences , climatology , geology , precipitation types , meteorology , environmental science , physics
This study analyzes the precipitation and ice cloud microphysical features of three common modes of linear mesoscale convective systems during the Plains Elevated Convection at Night (PECAN) campaign. Three cases, one for each linear mesoscale convective system archetype (trailing stratiform, leading stratiform, and parallel stratiform precipitation), are selected. We focus primarily on analyzing ice cloud microphysical properties and precipitation rates (PRs) over the classified convective core (CC) and stratiform rain (SR) regions, as well as the two stratiform regions that developed behind (SR1) and ahead (SR2) of the convective line relative to the storm motion. In the three selected cases, the ice water path (IWP) and PR have strong correlations in the CC, but not in the SR. In terms of the temporal evolution of the mean IWPs and PRs, both CC and SR IWPs, as well as CC PRs, reach peaks quickly but take a longer time to dissipate than the increase period. For all the three cases, both SR1 and SR2 IWPs are 20–70% of their corresponding CC values in both the leading stratiform and parallel stratiform cases and up to 95% for the trailing stratiform case, while all of their PRs are only 7–25% of their CC values. These values suggest not only that the SR PRs may depend on IWPs but also that the microphysical properties of ice particles such as habit and size distribution may play an important role. Utilizing cloud‐resolving simulations of these systems may provide better understanding of the physical meanings behind the results in the future.