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Title: Modeling Condensation in Deep Convection

Abstract

Cloud-scale models apply two drastically different methods to represent condensation of water vapor to form and grow cloud droplets. Maintenance of water saturation inside liquid clouds is assumed in the computationally efficient saturation adjustment approach used in most bulk microphysics schemes. When super- or subsaturations are allowed, condensation/evaporation can be calculated using the predicted saturation ratio and (either predicted or prescribed) mean droplet radius and concentration. Here, we investigate differences between simulations of deep unorganized convection applying a saturation adjustment condensation scheme (SADJ) and a scheme with supersaturation prediction (SPRE). A double-moment microphysics scheme with CCN activation parameterized as a function of the local vertical velocity is applied to compare cloud fields simulated applying SPRE and SADJ. Clean CCN conditions are assumed to demonstrate upper limits of the SPRE and SADJ difference. Microphysical piggybacking is used to extract the impacts with confidence. Results show a significant impact on deep convection dynamics, with SADJ featuring more cloud buoyancy and thus stronger updrafts. This leads to around a 3% increase of the surface rain accumulation in SADJ. Upper-tropospheric anvil cloud fractions are much larger in SPRE than in SADJ because of the higher ice concentrations and thus longer residence times of anvilmore » particles in SPRE, as demonstrated by sensitivity tests. Higher ice concentrations in SPRE come from significantly larger ice supersaturations in strong convective updrafts that feature water supersaturations of several percent.« less

Authors:
 [1];  [2]
  1. National Center for Atmospheric Research, Boulder, CO (United States). Mesoscale and Microscale Meteorology Lab.; Univ. of Warsaw, Warsaw (Poland). Inst. of Geophysics, Faculty of Phyiscs
  2. National Center for Atmospheric Research, Boulder, CO (United States). Mesoscale and Microscale Meteorology Lab.
Publication Date:
Research Org.:
University Corporation for Atmospheric Research, Boulder, CO (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1536991
Grant/Contract Number:  
SC0016476
Resource Type:
Accepted Manuscript
Journal Name:
Journal of the Atmospheric Sciences
Additional Journal Information:
Journal Volume: 74; Journal Issue: 7; Journal ID: ISSN 0022-4928
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; meteorology & atmospheric sciences; clouds; convection; convective-scale processes; glaciation

Citation Formats

Grabowski, Wojciech W., and Morrison, Hugh. Modeling Condensation in Deep Convection. United States: N. p., 2017. Web. https://doi.org/10.1175/jas-d-16-0255.1.
Grabowski, Wojciech W., & Morrison, Hugh. Modeling Condensation in Deep Convection. United States. https://doi.org/10.1175/jas-d-16-0255.1
Grabowski, Wojciech W., and Morrison, Hugh. Sat . "Modeling Condensation in Deep Convection". United States. https://doi.org/10.1175/jas-d-16-0255.1. https://www.osti.gov/servlets/purl/1536991.
@article{osti_1536991,
title = {Modeling Condensation in Deep Convection},
author = {Grabowski, Wojciech W. and Morrison, Hugh},
abstractNote = {Cloud-scale models apply two drastically different methods to represent condensation of water vapor to form and grow cloud droplets. Maintenance of water saturation inside liquid clouds is assumed in the computationally efficient saturation adjustment approach used in most bulk microphysics schemes. When super- or subsaturations are allowed, condensation/evaporation can be calculated using the predicted saturation ratio and (either predicted or prescribed) mean droplet radius and concentration. Here, we investigate differences between simulations of deep unorganized convection applying a saturation adjustment condensation scheme (SADJ) and a scheme with supersaturation prediction (SPRE). A double-moment microphysics scheme with CCN activation parameterized as a function of the local vertical velocity is applied to compare cloud fields simulated applying SPRE and SADJ. Clean CCN conditions are assumed to demonstrate upper limits of the SPRE and SADJ difference. Microphysical piggybacking is used to extract the impacts with confidence. Results show a significant impact on deep convection dynamics, with SADJ featuring more cloud buoyancy and thus stronger updrafts. This leads to around a 3% increase of the surface rain accumulation in SADJ. Upper-tropospheric anvil cloud fractions are much larger in SPRE than in SADJ because of the higher ice concentrations and thus longer residence times of anvil particles in SPRE, as demonstrated by sensitivity tests. Higher ice concentrations in SPRE come from significantly larger ice supersaturations in strong convective updrafts that feature water supersaturations of several percent.},
doi = {10.1175/jas-d-16-0255.1},
journal = {Journal of the Atmospheric Sciences},
number = 7,
volume = 74,
place = {United States},
year = {2017},
month = {7}
}

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