An Investigation of Hydrometeor Latent Cooling upon Convective Cold Pool Formation, Sustainment, and Properties

Holly M. Mallinson University of Illinois at Urbana–Champaign, Urbana, Illinois

Search for other papers by Holly M. Mallinson in
Current site
Google Scholar
PubMed
Close
and
Sonia G. Lasher-Trapp University of Illinois at Urbana–Champaign, Urbana, Illinois

Search for other papers by Sonia G. Lasher-Trapp in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Downdrafts extending from convective clouds can produce cold pools that propagate outward, sometimes initiating new convection along their leading edges. Models operating at scales requiring convective parameterizations usually lack representation of this detail, and thus fail to predict this convective regeneration and longer episodes of convective activity. Developing such parameterizations requires an improved understanding of the physical drivers of cold pools, and detailed studies of the roles of all the contributing microphysical processes have been lacking. This study utilizes a set of 12 simulations conducted within a single convective environment, but with variability in the microphysical fields produced by varying parameters influencing warm-rain or ice processes. Time-integrated microphysical budgets quantify the contribution of each hydrometeor type to the total latent cooling occurring in the downdrafts that form and sustain the cold pool. The timing of the onset of the cold pool is earlier in cases with a stronger warm rain process, but both graupel and rain were equally as likely to be the dominant hydrometeor in the downdraft first forming the cold pool. Graupel sublimation is the dominant term in sustaining the cold pool in all simulations, but the evaporation of rain has the strongest correlation to the cold pool expansion rate, depth, and intensity. Reconciling the current results with past studies elucidates the importance of considering: graupel sublimation, the latent cooling only in downdrafts contributing to the cold pool, and latent cooling in those downdrafts at altitudes that may be significantly higher than the melting level.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Holly M. Mallinson, hmm2@illinois.edu

Abstract

Downdrafts extending from convective clouds can produce cold pools that propagate outward, sometimes initiating new convection along their leading edges. Models operating at scales requiring convective parameterizations usually lack representation of this detail, and thus fail to predict this convective regeneration and longer episodes of convective activity. Developing such parameterizations requires an improved understanding of the physical drivers of cold pools, and detailed studies of the roles of all the contributing microphysical processes have been lacking. This study utilizes a set of 12 simulations conducted within a single convective environment, but with variability in the microphysical fields produced by varying parameters influencing warm-rain or ice processes. Time-integrated microphysical budgets quantify the contribution of each hydrometeor type to the total latent cooling occurring in the downdrafts that form and sustain the cold pool. The timing of the onset of the cold pool is earlier in cases with a stronger warm rain process, but both graupel and rain were equally as likely to be the dominant hydrometeor in the downdraft first forming the cold pool. Graupel sublimation is the dominant term in sustaining the cold pool in all simulations, but the evaporation of rain has the strongest correlation to the cold pool expansion rate, depth, and intensity. Reconciling the current results with past studies elucidates the importance of considering: graupel sublimation, the latent cooling only in downdrafts contributing to the cold pool, and latent cooling in those downdrafts at altitudes that may be significantly higher than the melting level.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Holly M. Mallinson, hmm2@illinois.edu
Save
  • Beard, K. V., and H. T. Ochs III, 1993: Warm-rain initiation: An overview of microphysical mechanisms. J. Appl. Meteor., 32, 608625, https://doi.org/10.1175/1520-0450(1993)032<0608:WRIAOO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., 2017: The governing equations for CM1. National Center for Atmospheric Research, 24 pp., http://www2.mmm.ucar.edu/people/bryan/cm1/cm1_equations.pdf.

  • Bryan, G. H., and J. M. Fritsch, 2002: A benchmark simulation for moist nonhydrostatic numerical models. Mon. Wea. Rev., 130, 29172928, https://doi.org/10.1175/1520-0493(2002)130<2917:ABSFMN>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., J. C. Kievel, and M. D. Parker, 2006: A multimodel assessment of RKW theory’s relevance to squall-line characteristics. Mon. Wea. Rev., 134, 27722792, https://doi.org/10.1175/MWR3226.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Byers, H. R., and R. R. Braham, 1949: The Thunderstorm. U.S. Government Printing Office, 287 pp.

  • Charba, J., 1974: Application of gravity current model to analysis of squall-line gust front. Mon. Wea. Rev., 102, 140156, https://doi.org/10.1175/1520-0493(1974)102<0140:AOGCMT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cohen, C., and E. W. McCaul, 2006: The sensitivity of simulated convective storms to variations in prescribed single-moment microphysics parameters that describe particle distributions, sizes, and numbers. Mon. Wea. Rev., 134, 25472565, https://doi.org/10.1175/MWR3195.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Corfidi, S. F., 2003: Cold pools and MCS propagation: Forecasting the motion of downwind-developing MCSs. Wea. Forecasting, 18, 9971017, https://doi.org/10.1175/1520-0434(2003)018<0997:CPAMPF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dawson, D. T., M. Xue, J. A. Milbrandt, and M. K. Yau, 2010: Comparison of evaporation and cold pool development between single-moment and multimoment bulk microphysics schemes in idealized simulations of tornadic thunderstorms. Mon. Wea. Rev., 138, 11521171, https://doi.org/10.1175/2009MWR2956.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deardorff, J. W., 1980: Stratocumulus-capped mixed layers derived from a three-dimensional model. Bound.-Layer Meteor., 18, 495527, https://doi.org/10.1007/BF00119502.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Del Genio, A. D., J. Wu, A. B. Wolf, Y. Chen, M.-S. Yao, and D. Kim, 2015: Constraints on cumulus parameterization from simulations of observed MJO events. J. Climate, 28, 64196442, https://doi.org/10.1175/JCLI-D-14-00832.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gilmore, M. S., J. M. Straka, and E. N. Rasmussen, 2004: Precipitation uncertainty due to variations in precipitation particle parameters within a simple microphysics scheme. Mon. Wea. Rev., 132, 26102627, https://doi.org/10.1175/MWR2810.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goff, C. R., 1976: Vertical structure of thunderstorm outflows. Mon. Wea. Rev., 104, 14291440, https://doi.org/10.1175/1520-0493(1976)104<1429:VSOTO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grandpeix, J.-Y., and J.-P. Lafore, 2010: A density current parameterization coupled with Emanuel’s convection scheme. Part I: The models. J. Atmos. Sci., 67, 881897, https://doi.org/10.1175/2009JAS3044.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grant, L. D., and S. C. van den Heever, 2015: Cold pool and precipitation responses to aerosol loading: Modulation by dry layers. J. Atmos. Sci., 72, 13981408, https://doi.org/10.1175/JAS-D-14-0260.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hallett, J., and S. C. Mossop, 1974: Production of secondary ice particles during the riming process. Nature, 249, 2628, https://doi.org/10.1038/249026a0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Igel, A. L., M. R. Igel, and S. C. van den Heever, 2015: Make it a double? Sobering results from simulations using single-moment microphysics schemes. J. Atmos. Sci., 72, 910925, https://doi.org/10.1175/JAS-D-14-0107.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • IPCC, 2013: Climate Change 2013: The Physical Science Basis. Cambridge University Press, 1535 pp, https://doi.org/10.1017/CBO9781107415324.

    • Crossref
    • Export Citation
  • James, R. P., and P. M. Markowski, 2010: A numerical investigation of the effects of dry air aloft on deep convection. Mon. Wea. Rev., 138, 140161, https://doi.org/10.1175/2009MWR3018.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • James, R. P., P. M. Markowski, and J. M. Fritsch, 2006: Bow echo sensitivity to ambient moisture and cold pool strength. Mon. Wea. Rev., 134, 950964, https://doi.org/10.1175/MWR3109.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jensen, M. P., and Coauthors, 2016: The Midlatitude Continental Convective Clouds Experiment (MC3E). Bull. Amer. Meteor. Soc., 97, 16671686, https://doi.org/10.1175/BAMS-D-14-00228.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johnson, D. E., P. K. Wang, and J. M. Straka, 1993: Numerical simulations of the 2 August 1981 CCOPE supercell storm with and without ice microphysics. J. Appl. Meteor., 32, 745759, https://doi.org/10.1175/1520-0450(1993)032<0745:NSOTAC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jung, Y., M. Xue, and M. Tong, 2012: Ensemble Kalman filter analyses of the 29–30 May 2004 Oklahoma tornadic thunderstorm using one- and two-moment bulk microphysics schemes, with verification against polarimetric radar data. Mon. Wea. Rev., 140, 14571475, https://doi.org/10.1175/MWR-D-11-00032.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalina, E. A., K. Friedrich, H. Morrison, and G. H. Bryan, 2014: Aerosol effects on idealized supercell thunderstorms in different environments. J. Atmos. Sci., 71, 45584580, https://doi.org/10.1175/JAS-D-14-0037.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Knupp, K. R., 1988: Downdrafts within High Plains cumulonimbi. Part II: Dynamics and thermodynamics. J. Atmos. Sci., 45, 39653982, https://doi.org/10.1175/1520-0469(1988)045<3965:DWHPCP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, S. S., and L. J. Donner, 2011: Effects of cloud parameterization on radiation and precipitation: A comparison between single-moment microphysics and double-moment microphysics. Terr. Atmos. Oceanic Sci., 22, 403420, https://doi.org/10.3319/TAO.2011.03.03.01(A).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mansell, E. R., C. L. Ziegler, and E. C. Bruning, 2010: Simulated electrification of a small thunderstorm with two-moment bulk microphysics. J. Atmos. Sci., 67, 171194, https://doi.org/10.1175/2009JAS2965.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marion, G. R., and R. J. Trapp, 2019: The dynamical coupling of convective updrafts, downdrafts, and cold pools in simulated supercell thunderstorms. J. Geophys. Res. Atmos., 124, 664683, https://doi.org/10.1029/2018JD029055.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McCumber, M., W.-K. Tao, J. Simpson, R. Penc, and S.-T. Soong, 1991: Comparison of ice-phase microphysical parameterization schemes using numerical simulations of tropical convection. J. Appl. Meteor., 30, 9851004, https://doi.org/10.1175/1520-0450-30.7.985.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morrison, H., and J. Milbrandt, 2011: Comparison of two-moment bulk microphysics schemes in idealized supercell thunderstorm simulations. Mon. Wea. Rev., 139, 11031130, https://doi.org/10.1175/2010MWR3433.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morrison, H., G. Thompson, and V. Tatarskii, 2009: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Mon. Wea. Rev., 137, 9911007, https://doi.org/10.1175/2008MWR2556.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Park, S., 2014: A unified convection scheme (UNICON). Part I: Formulation. J. Atmos. Sci., 71, 39023930, https://doi.org/10.1175/JAS-D-13-0233.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peters, J. M., and R. S. Schumacher, 2015: Mechanisms for organization and echo training in a flash-flood-producing mesoscale convective system. Mon. Wea. Rev., 143, 10581085, https://doi.org/10.1175/MWR-D-14-00070.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Phillips, V. T. J., P. J. DeMott, and C. Andronache, 2008: An empirical parameterization of heterogeneous ice nucleation for multiple chemical species of aerosol. J. Atmos. Sci., 65, 27572783, https://doi.org/10.1175/2007JAS2546.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Purdom, J. F. W., 1976: Some uses of high-resolution GOES imagery in the mesoscale forecasting of convection and its behavior. Mon. Wea. Rev., 104, 14741483, https://doi.org/10.1175/1520-0493(1976)104<1474:SUOHRG>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qian, L., G. S. Young, and W. M. Frank, 1998: A convective wake parameterization scheme for use in general circulation models. Mon. Wea. Rev., 126, 456469, https://doi.org/10.1175/1520-0493(1998)126<0456:ACWPSF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Redl, R., A. H. Fink, and P. Knippertz, 2015: An objective detection method for convective cold pool events and its application to northern Africa. Mon. Wea. Rev., 143, 50555072, https://doi.org/10.1175/MWR-D-15-0223.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rio, C., F. Hourdin, J.-Y. Grandpeix, and J.-P. Lafore, 2009: Shifting the diurnal cycle of parameterized deep convection over land. Geophys. Res. Lett., 36, L07809, https://doi.org/10.1029/2008GL036779.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schlemmer, L., and C. Hohenegger, 2014: The formation of wider and deeper clouds as a result of cold-pool dynamics. J. Atmos. Sci., 71, 28422858, https://doi.org/10.1175/JAS-D-13-0170.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Simpson, J. E., 1969: A comparison between laboratory and atmospheric density currents. Quart. J. Roy. Meteor. Soc., 95, 758765, https://doi.org/10.1002/qj.49709540609.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Srivastava, R. C., 1987: A model of intense downdrafts driven by the melting and evaporation of precipitation. J. Atmos. Sci., 44, 17521774, https://doi.org/10.1175/1520-0469(1987)044<1752:AMOIDD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tao, W.-K., X. Li, A. Khain, T. Matsui, S. Lang, and J. Simpson, 2007: Role of atmospheric aerosol concentration on deep convective precipitation: Cloud-resolving model simulations. J. Geophys. Res., 112, D24S18, https://doi.org/10.1029/2007JD008728.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trapp, R. J., and J. M. Woznicki, 2017: Convectively induced stabilizations and subsequent recovery with supercell thunderstorms during the Mesoscale Predictability Experiment (MPEX). Mon. Wea. Rev., 145, 17391754, https://doi.org/10.1175/MWR-D-16-0266.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Twomey, S., 1959: The nuclei of natural cloud formation. Part II: The supersaturation in natural clouds and the variation of cloud droplet concentration. Geofis. Pura Appl., 43, 243249, https://doi.org/10.1007/BF01993560.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van den Heever, S. C., and W. R. Cotton, 2004: The impact of hail size on simulated supercell storms. J. Atmos. Sci., 61, 15961609, https://doi.org/10.1175/1520-0469(2004)061<1596:TIOHSO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Van Weverberg, K., A. M. Vogelmann, H. Morrison, and J. A. Milbrandt, 2012: Sensitivity of idealized squall-line simulations to the level of complexity used in two-moment bulk microphysics schemes. Mon. Wea. Rev., 140, 18831907, https://doi.org/10.1175/MWR-D-11-00120.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Villanueva-Birriel, C. M., S. Lasher-Trapp, R. J. Trapp, and N. S. Diffenbaugh, 2014: Sensitivity of the warm rain process in convective clouds to regional climate change in the contiguous U.S. J. Clouds Aerosols Rad., 1, 117.

    • Search Google Scholar
    • Export Citation
  • Warner, C., J. Simpson, G. V. Helvoirt, D. W. Martin, D. Suchman, and G. L. Austin, 1980: Deep convection on day 261 of GATE. Mon. Wea. Rev., 108, 169194, https://doi.org/10.1175/1520-0493(1980)108<0169:DCODOG>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weaver, J. F., and S. P. Nelson, 1982: Multiscale aspects of thunderstorm gust fronts and their effects on subsequent storm development. Mon. Wea. Rev., 110, 707718, https://doi.org/10.1175/1520-0493(1982)110<0707:MAOTGF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 720 178 38
PDF Downloads 655 170 45