Cold Pool and Precipitation Responses to Aerosol Loading: Modulation by Dry Layers

Leah D. Grant Colorado State University, Fort Collins, Colorado

Search for other papers by Leah D. Grant in
Current site
Google Scholar
PubMed
Close
and
Susan C. van den Heever Colorado State University, Fort Collins, Colorado

Search for other papers by Susan C. van den Heever in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The relative sensitivity of midlatitude deep convective precipitation to aerosols and midlevel dry layers has been investigated in this study using high-resolution cloud-resolving model simulations. Nine simulations, including combinations of three moisture profiles and three aerosol number concentration profiles, were performed. Because of the veering wind profile of the initial sounding, the convection splits into a left-moving storm that is multicellular in nature and a right-moving storm, a supercell, which are analyzed separately.

The results demonstrate that while changes to the moisture profile always induce larger changes in precipitation than do variations in aerosol concentrations, multicells are sensitive to aerosol perturbations whereas supercells are less so. The multicellular precipitation sensitivity arises through aerosol impacts on the cold pool forcing. It is shown that the altitude of the dry layer influences whether cold pools are stronger or weaker and hence whether precipitation increases or decreases with increasing aerosol concentrations. When the dry-layer altitude is located near cloud base, cloud droplet evaporation rates and hence latent cooling rates are greater with higher aerosol loading, which results in stronger low-level downdrafts and cold pools. However, when the dry-layer altitude is located higher above cloud base, the low-level downdrafts and cold pools are weaker with higher aerosol loading because of reduced raindrop evaporation rates. The changes to the cold pool strength initiate positive feedbacks that further modify the cold pool strength and subsequent precipitation totals. Aerosol impacts on deep convection are therefore found to be modulated by the altitude of the dry layer and to vary inversely with the storm organization.

Corresponding author address: Leah D. Grant, Colorado State University, 1371 Campus Delivery, Fort Collins, CO 80523. E-mail: ldgrant@atmos.colostate.edu

Abstract

The relative sensitivity of midlatitude deep convective precipitation to aerosols and midlevel dry layers has been investigated in this study using high-resolution cloud-resolving model simulations. Nine simulations, including combinations of three moisture profiles and three aerosol number concentration profiles, were performed. Because of the veering wind profile of the initial sounding, the convection splits into a left-moving storm that is multicellular in nature and a right-moving storm, a supercell, which are analyzed separately.

The results demonstrate that while changes to the moisture profile always induce larger changes in precipitation than do variations in aerosol concentrations, multicells are sensitive to aerosol perturbations whereas supercells are less so. The multicellular precipitation sensitivity arises through aerosol impacts on the cold pool forcing. It is shown that the altitude of the dry layer influences whether cold pools are stronger or weaker and hence whether precipitation increases or decreases with increasing aerosol concentrations. When the dry-layer altitude is located near cloud base, cloud droplet evaporation rates and hence latent cooling rates are greater with higher aerosol loading, which results in stronger low-level downdrafts and cold pools. However, when the dry-layer altitude is located higher above cloud base, the low-level downdrafts and cold pools are weaker with higher aerosol loading because of reduced raindrop evaporation rates. The changes to the cold pool strength initiate positive feedbacks that further modify the cold pool strength and subsequent precipitation totals. Aerosol impacts on deep convection are therefore found to be modulated by the altitude of the dry layer and to vary inversely with the storm organization.

Corresponding author address: Leah D. Grant, Colorado State University, 1371 Campus Delivery, Fort Collins, CO 80523. E-mail: ldgrant@atmos.colostate.edu
Save
  • Altaratz, O., I. Koren, T. Reisin, A. Kostinski, G. Feingold, Z. Levin, and Y. Yin, 2008: Aerosols’ influence on the interplay between condensation, evaporation and rain in warm cumulus cloud. Atmos. Chem. Phys., 8, 1524, doi:10.5194/acp-8-15-2008.

    • Search Google Scholar
    • Export Citation
  • Andreae, M. O., D. Rosenfeld, P. Artaxo, A. A. Costa, G. P. Frank, K. M. Longo, and M. A. F. Silva-Dias, 2004: Smoking rain clouds over the Amazon. Science, 303, 13371342, doi:10.1126/science.1092779.

    • Search Google Scholar
    • Export Citation
  • Berg, W., T. L’Ecuyer, and S. van den Heever, 2008: Evidence for the impact of aerosols on the onset and microphysical properties of rainfall from a combination of satellite observations and cloud-resolving model simulations. J. Geophys. Res., 113, D14S23, doi:10.1029/2007JD009649.

    • Search Google Scholar
    • Export Citation
  • Brown, R. G., and C. Zhang, 1997: Variability of midtropospheric moisture and its effect on cloud-top height distribution during TOGA COARE. J. Atmos. Sci., 54, 27602774, doi:10.1175/1520-0469(1997)054<2760:VOMMAI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Carlson, T. N., and F. H. Ludlam, 1968: Conditions for the occurrence of severe local storms. Tellus, 20, 203226, doi:10.1111/j.2153-3490.1968.tb00364.x.

    • Search Google Scholar
    • Export Citation
  • Cotton, W. R., and Coauthors, 2003: RAMS 2001: Current status and future directions. Meteor. Atmos. Phys., 82, 529, doi:10.1007/s00703-001-0584-9.

    • Search Google Scholar
    • Export Citation
  • Cui, Z., K. S. Carslaw, and A. M. Blyth, 2011: The coupled effect of mid-tropospheric moisture and aerosol abundance on deep convective cloud dynamics and microphysics. Atmosphere, 2, 222241, doi:10.3390/atmos2030222.

    • Search Google Scholar
    • Export Citation
  • Davies-Jones, R., 2002: Linear and nonlinear propagation of supercell storms. J. Atmos. Sci., 59, 31783205, doi:10.1175/1520-0469(2003)059<3178:LANPOS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • DeMott, P. J., and Coauthors, 2010: Predicting global atmospheric ice nuclei distributions and their impacts on climate. Proc. Natl. Acad. Sci. USA, 107, 11 21711 222, doi:10.1073/pnas.0910818107.

    • Search Google Scholar
    • Export Citation
  • Droegemeier, K. K., S. M. Lazarus, and R. Davies-Jones, 1993: The influence of helicity on numerically simulated convective storms. Mon. Wea. Rev., 121, 20052029, doi:10.1175/1520-0493(1993)121<2005:TIOHON>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Ekman, A. M. L., A. Engström, and C. Wang, 2007: The effect of aerosol composition and concentration on the development and anvil properties of a continental deep convective cloud. Quart. J. Roy. Meteor. Soc., 133, 14391452, doi:10.1002/qj.108.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1994: Atmospheric Convection.Oxford University Press, 580 pp.

  • Feingold, G., and A. J. Heymsfield, 1992: Parameterizations of condensational growth of droplets for use in general circulation models. J. Atmos. Sci., 49, 23252342, doi:10.1175/1520-0469(1992)049<2325:POCGOD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Fovell, R. G., and P.-H. Tan, 1998: The temporal behavior of numerically simulated multicell-type storms. Part II: The convective cell life cycle and cell regeneration. Mon. Wea. Rev., 126, 551577, doi:10.1175/1520-0493(1998)126<0551:TTBONS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gilmore, M. S., and L. J. Wicker, 1998: The influence of midtropospheric dryness on supercell morphology and evolution. Mon. Wea. Rev., 126, 943958, doi:10.1175/1520-0493(1998)126<0943:TIOMDO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Grant, L. D., and S. C. van den Heever, 2014: Microphysical and dynamical characteristics of low-precipitation and classic supercells. J. Atmos. Sci., 71, 26042624, doi:10.1175/JAS-D-13-0261.1.

    • Search Google Scholar
    • 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, doi:10.1175/2009MWR3018.1.

    • Search Google Scholar
    • Export Citation
  • Johnson, R. H., and P. J. Hamilton, 1988: The relationship of surface pressure features to the precipitation and airflow structure of an intense midlatitude squall line. Mon. Wea. Rev., 116, 14441473, doi:10.1175/1520-0493(1988)116<1444:TROSPF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Khain, A., and B. Lynn, 2009: Simulation of a supercell storm in clean and dirty atmosphere using weather research and forecast model with spectral bin microphysics. J. Geophys. Res., 114, D19209, doi:10.1029/2009JD011827.

    • Search Google Scholar
    • Export Citation
  • Khain, A., D. Rosenfeld, and A. Pokrovsky, 2005: Aerosol impact on the dynamics and microphysics of deep convective clouds. Quart. J. Roy. Meteor. Soc., 131, 26392663, doi:10.1256/qj.04.62.

    • Search Google Scholar
    • Export Citation
  • Khain, A., N. BenMoshe, and A. Pokrovsky, 2008: Factors determining the impact of aerosols on surface precipitation from clouds: An attempt at classification. J. Atmos. Sci., 65, 17211748, doi:10.1175/2007JAS2515.1.

    • Search Google Scholar
    • Export Citation
  • Khain, A., D. Rosenfeld, A. Pokrovsky, U. Blahak, and A. Ryzhkov, 2011: The role of CCN in precipitation and hail in a mid-latitude storm as seen in simulations using a spectral (bin) microphysics model in a 2D dynamic frame. Atmos. Res., 99, 129146, doi:10.1016/j.atmosres.2010.09.015.

    • Search Google Scholar
    • Export Citation
  • Khairoutdinov, M., and D. Randall, 2006: High-resolution simulation of shallow-to-deep convection transition over land. J. Atmos. Sci., 63, 34213436, doi:10.1175/JAS3810.1.

    • Search Google Scholar
    • Export Citation
  • Klemp, J. B., and R. B. Wilhelmson, 1978: The simulation of three-dimensional convective storm dynamics. J. Atmos. Sci., 35, 10701096, doi:10.1175/1520-0469(1978)035<1070:TSOTDC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kuang, Z., and C. S. Bretherton, 2006: A mass-flux scheme view of a high-resolution simulation of a transition from shallow to deep cumulus convection. J. Atmos. Sci., 63, 18951909, doi:10.1175/JAS3723.1.

    • Search Google Scholar
    • Export Citation
  • Lee, S. S., 2011: Dependence of aerosol-precipitation interactions on humidity in a multiple-cloud system. Atmos. Chem. Phys., 11, 21792196, doi:10.5194/acp-11-2179-2011.

    • Search Google Scholar
    • Export Citation
  • Lee, S. S., L. J. Donner, V. T. J. Phillips, and Y. Ming, 2008: Examination of aerosol effects on precipitation in deep convective clouds during the 1997 ARM summer experiment. Quart. J. Roy. Meteor. Soc., 134, 12011220, doi:10.1002/qj.287.

    • Search Google Scholar
    • Export Citation
  • Lim, K.-S. S., S.-Y. Hong, S. S. Yum, J. Dudhia, and J. B. Klemp, 2011: Aerosol effects on the development of a supercell storm in a double-moment bulk-cloud microphysics scheme. J. Geophys. Res., 116, D02204, doi:10.1029/2010JD014128.

    • Search Google Scholar
    • Export Citation
  • Lin, Y.-L., R. L. Deal, and M. S. Kulie, 1998: Mechanisms of cell regeneration, development, and propagation within a two-dimensional multicell storm. J. Atmos. Sci., 55, 18671886, doi:10.1175/1520-0469(1998)055<1867:MOCRDA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Loftus, A. M., and W. R. Cotton, 2014: Examination of CCN impacts on hail in a simulated supercell storm with triple-moment hail bulk microphysics. Atmos. Res., 147–148, 183204, doi:10.1016/j.atmosres.2014.04.017.

    • Search Google Scholar
    • Export Citation
  • May, P. T., V. N. Bringi, and M. Thurai, 2011: Do we observe aerosol impacts on DSDs in strongly forced tropical thunderstorms? J. Atmos. Sci., 68, 19021910, doi:10.1175/2011JAS3617.1.

    • Search Google Scholar
    • Export Citation
  • Meyers, M. P., R. L. Walko, J. Y. Harrington, and W. R. Cotton, 1997: New RAMS cloud microphysics parameterization. Part II: The two-moment scheme. Atmos. Res., 45, 339, doi:10.1016/S0169-8095(97)00018-5.

    • Search Google Scholar
    • Export Citation
  • Morrison, H., 2012: On the robustness of aerosol effects on an idealized supercell storm simulated with a cloud system-resolving model. Atmos. Chem. Phys., 12, 76897705, doi:10.5194/acp-12-7689-2012.

    • Search Google Scholar
    • Export Citation
  • Prospero, J. M., P. Ginoux, O. Torres, S. E. Nicholson, and T. E. Gill, 2002: Environmental characterization of global sources of atmospheric soil dust identified with the NIMBUS 7 Total Ozone Mapping Spectrometer (TOMS) absorbing aerosol product. Rev. Geophys., 40, 1002, doi:10.1029/2000RG000095.

    • Search Google Scholar
    • Export Citation
  • Ridout, J. A., 2002: Sensitivity of tropical Pacific convection to dry layers at mid- to upper levels: Simulation and parameterization tests. J. Atmos. Sci., 59, 33623381, doi:10.1175/1520-0469(2002)059<3362:SOTPCT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rotunno, R., and J. B. Klemp, 1982: The influence of the shear-induced pressure gradient on thunderstorm motion. Mon. Wea. Rev., 110, 136151, doi:10.1175/1520-0493(1982)110<0136:TIOTSI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Saleeby, S. M., and W. R. Cotton, 2004: A large-droplet mode and prognostic number concentration of cloud droplets in the Colorado State University Regional Atmospheric Modeling System (RAMS). Part I: Module descriptions and supercell test simulations. J. Appl. Meteor., 43, 182195, doi:10.1175/1520-0450(2004)043<0182:ALMAPN>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Saleeby, S. M., and W. R. Cotton, 2008: A binned approach to cloud-droplet riming implemented in a bulk microphysics model. J. Appl. Meteor. Climatol., 47, 694703, doi:10.1175/2007JAMC1664.1.

    • Search Google Scholar
    • Export Citation
  • Saleeby, S. M., and S. C. van den Heever, 2013: Developments in the CSU-RAMS aerosol model: Emissions, nucleation, regeneration, deposition, and radiation. J. Appl. Meteor. Climatol., 52, 26012622, doi:10.1175/JAMC-D-12-0312.1.

    • Search Google Scholar
    • Export Citation
  • Saleeby, S. M., W. Berg, S. van den Heever, and T. L’Ecuyer, 2010: Impact of cloud-nucleating aerosols in cloud-resolving model simulations of warm-rain precipitation in the East China Sea. J. Atmos. Sci., 67, 39163930, doi:10.1175/2010JAS3528.1.

    • Search Google Scholar
    • Export Citation
  • Seifert, A., and K. D. Beheng, 2006: A two-moment cloud microphysics parameterization for mixed-phase clouds. Part 2: Maritime vs. continental deep convective storms. Meteor. Atmos. Phys., 92, 6782, doi:10.1007/s00703-005-0113-3.

    • Search Google Scholar
    • Export Citation
  • Seigel, R. B., S. C. van den Heever, and S. M. Saleeby, 2013: Mineral dust indirect effects and cloud radiative feedbacks of a simulated idealized nocturnal squall line. Atmos. Chem. Phys., 13, 44674485, doi:10.5194/acp-13-4467-2013.

    • Search Google Scholar
    • Export Citation
  • Smagorinsky, J., 1963: General circulation experiments with the primitive equations. I. The basic experiment. Mon. Wea. Rev., 91, 99164, doi:10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Storer, R. L., and S. C. van den Heever, 2013: Microphysical processes evident in aerosol forcing of tropical deep convective clouds. J. Atmos. Sci., 70, 430446, doi:10.1175/JAS-D-12-076.1.

    • Search Google Scholar
    • Export Citation
  • Storer, R. L., S. C. van den Heever, and G. L. Stephens, 2010: Modeling aerosol impacts on convective storms in different environments. J. Atmos. Sci., 67, 39043915, doi:10.1175/2010JAS3363.1.

    • 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, doi:10.1029/2007JD008728.

    • Search Google Scholar
    • Export Citation
  • Tao, W.-K., J.-P. Chen, Z. Li, C. Wang, and C. Zhang, 2012: Impact of aerosols on convective clouds and precipitation. Rev. Geophys., 50, RG2001, doi:10.1029/2011RG000369.

    • Search Google Scholar
    • Export Citation
  • Thorpe, A. J., and M. J. Miller, 1978: Numerical simulations showing the role of the downdraught in cumulonimbus motion and splitting. Quart. J. Roy. Meteor. Soc., 104, 873893, doi:10.1002/qj.49710444203.

    • Search Google Scholar
    • Export Citation
  • Thorpe, A. J., M. J. Miller, and M. W. Moncrieff, 1982: Two-dimensional convection in non-constant shear: A model of mid-latitude squall lines. Quart. J. Roy. Meteor. Soc., 108, 739762, doi:10.1002/qj.49710845802.

    • Search Google Scholar
    • Export Citation
  • van den Heever, S. C., and W. R. Cotton, 2007: Urban aerosol impacts on downwind convective storms. J. Appl. Meteor. Climatol., 46, 828850, doi:10.1175/JAM2492.1.

    • Search Google Scholar
    • Export Citation
  • van den Heever, S. C., G. G. Carrió, W. R. Cotton, P. J. DeMott, and A. J. Prenni, 2006: Impacts of nucleating aerosol on Florida storms. Part I: Mesoscale simulations. J. Atmos. Sci., 63, 17521775, doi:10.1175/JAS3713.1.

    • Search Google Scholar
    • Export Citation
  • Walko, R. L., W. R. Cotton, M. P. Meyers, and J. Y. Harrington, 1995: New RAMS cloud microphysics parameterization. Part I: The single-moment scheme. Atmos. Res., 38, 2962, doi:10.1016/0169-8095(94)00087-T.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., and J. B. Klemp, 1982: The dependence of numerically simulated convective storms on vertical wind shear and buoyancy. Mon. Wea. Rev., 110, 504520, doi:10.1175/1520-0493(1982)110<0504:TDONSC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., and J. B. Klemp, 1984: The structure and classification of numerically simulated convective storms in directionally varying wind shears. Mon. Wea. Rev., 112, 24792498, doi:10.1175/1520-0493(1984)112<2479:TSACON>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 512 158 16
PDF Downloads 395 111 14