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Title: Investigation of liquid cloud microphysical properties of deep convective systems: 1. Parameterization raindrop size distribution and its application for stratiform rain estimation: STRATIFORM RAINDROP SIZE DISTRIBUTION

Authors:
 [1];  [1];  [1];  [2]
  1. Department of Atmospheric Sciences, University of North Dakota, Grand Forks North Dakota USA
  2. National Center for Atmospheric Research, Boulder Colorado USA
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1402138
Grant/Contract Number:
SC0008468
Resource Type:
Journal Article: Publisher's Accepted Manuscript
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
Journal Volume: 121; Journal Issue: 18; Related Information: CHORUS Timestamp: 2017-10-23 16:37:11; Journal ID: ISSN 2169-897X
Publisher:
Wiley Blackwell (John Wiley & Sons)
Country of Publication:
United States
Language:
English

Citation Formats

Wang, Jingyu, Dong, Xiquan, Xi, Baike, and Heymsfield, Andrew J. Investigation of liquid cloud microphysical properties of deep convective systems: 1. Parameterization raindrop size distribution and its application for stratiform rain estimation: STRATIFORM RAINDROP SIZE DISTRIBUTION. United States: N. p., 2016. Web. doi:10.1002/2016JD024941.
Wang, Jingyu, Dong, Xiquan, Xi, Baike, & Heymsfield, Andrew J. Investigation of liquid cloud microphysical properties of deep convective systems: 1. Parameterization raindrop size distribution and its application for stratiform rain estimation: STRATIFORM RAINDROP SIZE DISTRIBUTION. United States. doi:10.1002/2016JD024941.
Wang, Jingyu, Dong, Xiquan, Xi, Baike, and Heymsfield, Andrew J. 2016. "Investigation of liquid cloud microphysical properties of deep convective systems: 1. Parameterization raindrop size distribution and its application for stratiform rain estimation: STRATIFORM RAINDROP SIZE DISTRIBUTION". United States. doi:10.1002/2016JD024941.
@article{osti_1402138,
title = {Investigation of liquid cloud microphysical properties of deep convective systems: 1. Parameterization raindrop size distribution and its application for stratiform rain estimation: STRATIFORM RAINDROP SIZE DISTRIBUTION},
author = {Wang, Jingyu and Dong, Xiquan and Xi, Baike and Heymsfield, Andrew J.},
abstractNote = {},
doi = {10.1002/2016JD024941},
journal = {Journal of Geophysical Research: Atmospheres},
number = 18,
volume = 121,
place = {United States},
year = 2016,
month = 9
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1002/2016JD024941

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  • This study presents new algorithms for retrieving ice cloud microphysical properties (ice water content (IWC) and median mass diameter (Dm)) for the stratiform and thick anvil regions of Deep Convective Systems (DCSs) using Next-Generation Radar (NEXRAD) reflectivity and recently developed empirical relationships from aircraft in situ measurements during the Midlatitude Continental Convective Clouds Experiment (MC3E). A classic DCS case on 20 May 2011 is used to compare the retrieved IWC profiles with other retrieval and cloud-resolving model simulations. The mean values of each retrieved and simulated IWC fall within one standard derivation of the other two. The statistical results frommore » six selected cases during MC3E show that the aircraft in situ derived IWC and Dm are 0.47 ± 0.29 g m-3 and 2.02 ± 1.3 mm, while the mean values of retrievals have a positive bias of 0.16 g m-3 (34%) and a negative bias of 0.39 mm (19%). To validate the newly developed retrieval algorithms from this study, IWC and Dm are performed with other DCS cases during Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX) field campaign using composite gridded NEXRAD reflectivity and compared with in situ IWC and Dm from aircraft. A total of 64 1-min collocated aircraft and radar samples are available for comparisons, and the averages of radar retrieved and aircraft in situ measured IWCs are 1.22 g m-3 and 1.26 g m-3 with a correlation of 0.5, and their averaged Dm values are 2.15 and 1.80 mm. These comparisons have shown that the retrieval algorithms 45 developed during MC3E can retrieve similar ice cloud microphysical properties of DCS to aircraft in situ measurements during BAMEX with median errors of ~40% and ~25% for IWC and Dm retrievals, respectively. This is indicating our retrieval algorithms are suitable for other midlatitude continental DCS ice clouds, especially at stratiform rain and thick anvil regions. In addition, based on the averaged IWC and Dm values during MC3E and BAMEX, the DCS IWC values over midlatitude are significantly different, while their Dm values are close to each other. On the other hand, these DCS IWC and Dm values are 1-2 orders of magnitude larger than those of single-layered cirrus clouds over midlatitudes.« less
  • In model studies of aerosol-dependent immersion freezing in clouds, a common assumption is that each ice nucleating aerosol particle corresponds to exactly one cloud droplet. Conversely, the immersion freezing of larger drops—“rain”—is usually represented by a liquid volume-dependent approach, making the parameterizations of rain freezing independent of specific aerosol types and concentrations. This may lead to inconsistencies when aerosol effects on clouds and precipitation shall be investigated, since raindrops consist of the cloud droplets—and corresponding aerosol particles—that have been involved in drop-drop-collisions. We introduce an extension to a two-moment microphysical scheme in order to account explicitly for particle accumulation inmore » raindrops by tracking the rates of selfcollection, autoconversion, and accretion. This also provides a direct link between ice nuclei and the primary formation of large precipitating ice particles. A new parameterization scheme of drop freezing is presented to consider multiple ice nuclei within one drop and effective drop cooling rates. In our test cases of deep convective clouds, we find that at altitudes which are most relevant for immersion freezing, the majority of potential ice nuclei have been converted from cloud droplets into raindrops. Compared to the standard treatment of freezing in our model, the less efficient mineral dust-based freezing results in higher rainwater contents in the convective core, affecting both rain and hail precipitation. The aerosol-dependent treatment of rain freezing can reverse the signs of simulated precipitation sensitivities to ice nuclei perturbations.« less
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