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Title: Drop size distribution broadening mechanisms in a bin microphysics Eulerian model

Abstract

In this study, processes that broaden drop size distributions (DSDs) in Eulerian models with two-moment bin microphysics are analyzed. Numerous tests are performed to isolate the effects of different physical mechanisms that broaden DSDs in two- and three-dimensional Weather Research and Forecasting model simulations of an idealized ice-free cumulus cloud. Additionally, sensitivity of these effects to modifying horizontal and vertical model grid spacings is also examined. As expected, collision-coalescence is a key process broadening the modeled DSDs. In-cloud droplet activation also contributes substantially to DSD broadening, whereas evaporation has only a minor effect and sedimentation has little effect. Cloud dilution (mixing of cloud-free and cloudy air) also broadens the DSDs considerably, whether or not it is accompanied by evaporation. This mechanism involves the reduction of droplet concentration from dilution along the cloud’s lateral edges, leading to locally high supersaturation and enhanced drop growth when this air is subsequently lifted in the updraft. DSD broadening ensues when the DSDs are mixed with those from the cloud core. Decreasing the horizontal and vertical model grid spacings from 100 m to 30 m has limited impact on the DSDs. However, when these physical broadening mechanisms (in-cloud activation, collision-coalescence, dilution, etc.) are turned off,more » there is a reduction of DSD width by up to ~20-50% when the vertical grid spacing is decreased from 100 m to 30 m, consistent with effects of artificial broadening from vertical numerical diffusion. Nonetheless, this artificial numerical broadening appears to be relatively unimportant overall for DSD broadening when physically based broadening mechanisms in the model are included for this cumulus case.« less

Authors:
 [1];  [2];  [3];  [4];  [5]
  1. Inst. Nacional de Pesquisas Espaciais, São Paulo (Brazil)
  2. National Center for Atmospheric Research, Boulder, CO (United States); Univ. of New South Wales, Sydney, NSW (Australia)
  3. Inst. Nacional de Pesquisas Espaciais, São Paulo (Brazi); Max Planck Inst. for Chemistry, Mainz (Germany)
  4. Pennsylvania State Univ., University Park, PA (United States)
  5. Univ. of Wyoming, Laramie, WY (United States)
Publication Date:
Research Org.:
University Corporation for Atmospheric Research, Boulder, CO (United States); National Center for Atmospheric Research, Boulder, CO (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER); São Paulo Research Foundation (FAPESP); National Science Foundation (NSF); National Center of Meteorology
OSTI Identifier:
1657539
Alternate Identifier(s):
OSTI ID: 1786990
Grant/Contract Number:  
SC0020118; 2016/24562-6; 2019/06988-4; AGS-1824243; AGS-1822268
Resource Type:
Accepted Manuscript
Journal Name:
Journal of the Atmospheric Sciences
Additional Journal Information:
Journal Volume: 77; Journal Issue: 9; Journal ID: ISSN 0022-4928
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Hernández Pardo, Lianet, Morrison, Hugh, Machado, Luiz A. T., Harrington, Jerry Y., and Lebo, Zachary J. Drop size distribution broadening mechanisms in a bin microphysics Eulerian model. United States: N. p., 2020. Web. https://doi.org/10.1175/jas-d-20-0099.1.
Hernández Pardo, Lianet, Morrison, Hugh, Machado, Luiz A. T., Harrington, Jerry Y., & Lebo, Zachary J. Drop size distribution broadening mechanisms in a bin microphysics Eulerian model. United States. https://doi.org/10.1175/jas-d-20-0099.1
Hernández Pardo, Lianet, Morrison, Hugh, Machado, Luiz A. T., Harrington, Jerry Y., and Lebo, Zachary J. Thu . "Drop size distribution broadening mechanisms in a bin microphysics Eulerian model". United States. https://doi.org/10.1175/jas-d-20-0099.1.
@article{osti_1657539,
title = {Drop size distribution broadening mechanisms in a bin microphysics Eulerian model},
author = {Hernández Pardo, Lianet and Morrison, Hugh and Machado, Luiz A. T. and Harrington, Jerry Y. and Lebo, Zachary J.},
abstractNote = {In this study, processes that broaden drop size distributions (DSDs) in Eulerian models with two-moment bin microphysics are analyzed. Numerous tests are performed to isolate the effects of different physical mechanisms that broaden DSDs in two- and three-dimensional Weather Research and Forecasting model simulations of an idealized ice-free cumulus cloud. Additionally, sensitivity of these effects to modifying horizontal and vertical model grid spacings is also examined. As expected, collision-coalescence is a key process broadening the modeled DSDs. In-cloud droplet activation also contributes substantially to DSD broadening, whereas evaporation has only a minor effect and sedimentation has little effect. Cloud dilution (mixing of cloud-free and cloudy air) also broadens the DSDs considerably, whether or not it is accompanied by evaporation. This mechanism involves the reduction of droplet concentration from dilution along the cloud’s lateral edges, leading to locally high supersaturation and enhanced drop growth when this air is subsequently lifted in the updraft. DSD broadening ensues when the DSDs are mixed with those from the cloud core. Decreasing the horizontal and vertical model grid spacings from 100 m to 30 m has limited impact on the DSDs. However, when these physical broadening mechanisms (in-cloud activation, collision-coalescence, dilution, etc.) are turned off, there is a reduction of DSD width by up to ~20-50% when the vertical grid spacing is decreased from 100 m to 30 m, consistent with effects of artificial broadening from vertical numerical diffusion. Nonetheless, this artificial numerical broadening appears to be relatively unimportant overall for DSD broadening when physically based broadening mechanisms in the model are included for this cumulus case.},
doi = {10.1175/jas-d-20-0099.1},
journal = {Journal of the Atmospheric Sciences},
number = 9,
volume = 77,
place = {United States},
year = {2020},
month = {9}
}

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