• Auer Jr., A. H., and J. D. Marwitz, 1968: Estimates of air and moisture flux into hailstorms on the High Plains. J. Appl. Meteor., 7 , 196198.

    • Search Google Scholar
    • Export Citation
  • Brooks, H. E., and R. B. Wilhelmson, 1992: Numerical simulation of a low-precipitation supercell thunderstorm. Meteor. Atmos. Phys., 49 , 317.

    • Search Google Scholar
    • Export Citation
  • Browning, K. A., C. W. Pardoe, and F. F. Hill, 1975: The nature of orographic rain at wintertime cold fronts. Quart. J. Roy. Meteor. Soc., 101 , 333352.

    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., and J. M. Fritsch, 2002: A benchmark simulation for moist nonhydrostatic numerical models. Mon. Wea. Rev., 130 , 29172928.

    • Search Google Scholar
    • Export Citation
  • Cohen, C., and E. W. McCaul Jr., 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.

    • Search Google Scholar
    • Export Citation
  • Cooper, H. J., M. Garstang, and J. Simpson, 1982: The diurnal interaction between convective and peninsular-scale forcing over south Florida. Mon. Wea. Rev., 110 , 486503.

    • Search Google Scholar
    • Export Citation
  • Cotton, W. R., M-S. Lin, R. L. McAnelly, and C. J. Tremback, 1989: A composite model of mesoscale convective complexes. Mon. Wea. Rev., 117 , 765783.

    • Search Google Scholar
    • Export Citation
  • Cui, Z., and K. S. Carslaw, 2006: Enhanced vertical transport efficiency of aerosol in convective clouds due to increases in tropospheric aerosol abundance. J. Geophys. Res., 111 .D15212, doi:10.1029/2005JD006781.

    • Search Google Scholar
    • Export Citation
  • Del Genio, A. D., W. Kovari, M-S. Yao, and J. Jonas, 2005: Cumulus microphysics and climate sensitivity. J. Climate, 18 , 23762387.

  • Doswell, C. A., H. E. Brooks, and R. A. Maddox, 1996: Flash flood forecasting: An ingredients-based methodology. Wea. Forecasting, 11 , 560581.

    • Search Google Scholar
    • Export Citation
  • Fankhauser, J. C., 1988: Estimates of thunderstorm precipitation efficiency from field measurements in CCOPE. Mon. Wea. Rev., 116 , 663684.

    • Search Google Scholar
    • Export Citation
  • Ferrier, B. S., J. Simpson, and W-K. Tao, 1996: Factors responsible for precipitation efficiencies in midlatitude and tropical squall simulations. Mon. Wea. Rev., 124 , 21002125.

    • Search Google Scholar
    • Export Citation
  • Frank, W. M., and C. Cohen, 1987: Simulation of tropical convective systems. Part I: A cumulus parameterization. J. Atmos. Sci., 44 , 37873799.

    • Search Google Scholar
    • Export Citation
  • Hudak, D. R., and R. List, 1988: Precipitation development in natural and seeded cumulus clouds in southern Africa. J. Appl. Meteor., 27 , 734756.

    • Search Google Scholar
    • Export Citation
  • Knight, C. A., and N. C. Knight, 2001: Hailstorms. Severe Convective Storms, Meteor. Monogr., No. 50, Amer. Meteor. Soc., 223–254.

  • Lau, K. M., and H. T. Wu, 2003: Warm rain processes over tropical oceans and climate implications. Geophys. Res. Lett., 30 .2290, doi:10.1029/2003GL018567.

    • Search Google Scholar
    • Export Citation
  • Lindzen, R. S., M-D. Chou, and A. Hou, 2001: Does the earth have an adaptive infrared iris? Bull. Amer. Meteor. Soc., 82 , 417432.

  • Lucas, C., E. J. Zipser, and B. S. Ferrier, 2000: Sensitivity of tropical west Pacific oceanic squall lines to tropospheric winds and moisture profiles. J. Atmos. Sci., 57 , 23512373.

    • Search Google Scholar
    • Export Citation
  • McCaul Jr., E. W., and M. L. Weisman, 2001: The sensitivity of simulated supercell structure and intensity to variations in the shapes of environmental buoyancy and shear profiles. Mon. Wea. Rev., 129 , 664687.

    • Search Google Scholar
    • Export Citation
  • McCaul Jr., E. W., and C. Cohen, 2002: The impact on simulated storm structure and intensity of variations in the mixed layer and moist layer depths. Mon. Wea. Rev., 130 , 17221748.

    • Search Google Scholar
    • Export Citation
  • McCaul Jr., E. W., and C. Cohen, 2004: The initiation, longevity, and morphology of simulated convective storms as a function of free-tropospheric relative humidity. Preprints, 22d Conf. on Severe Local Storms, Hyannis, MA, Amer. Meteor. Soc., CD-ROM, 8A.5.

  • McCaul Jr., E. W., C. Cohen, and C. Kirkpatrick, 2005: The sensitivity of simulated storm structure, intensity, and precipitation efficiency to the temperature at the lifted condensation level. Mon. Wea. Rev., 133 , 30153037.

    • Search Google Scholar
    • Export Citation
  • Medvigy, D., P. R. Moorcroft, R. Avissar, and R. L. Walko, 2005: Mass conservation and atmospheric dynamics in the Regional Atmospheric Modeling System (RAMS). Environ. Fluid Mech., 5 , 109134.

    • Search Google Scholar
    • Export Citation
  • Mohamed, Y. A., B. J. J. M. van den Hurk, H. H. G. Savenije, and W. G. M. Bastiaanssen, 2005a: Hydroclimatology of the Nile: Results from a regional climate model. Hydrol. Earth Syst. Sci., 9 , 261276.

    • Search Google Scholar
    • Export Citation
  • Mohamed, Y. A., B. J. J. M. van den Hurk, H. H. G. Savenije, and W. G. M. Bastiaanssen, 2005b: Impact of the Sudd wetland on the Nile hydroclimatology. Water Resour. Res., 41 .W08420, doi:10.1029/2004WR003792.

    • Search Google Scholar
    • Export Citation
  • Pielke, R. A., and Coauthors, 1992: A comprehensive meteorological modeling system—RAMS. Meteor. Atmos. Phys., 49 , 6991.

  • Raddatz, R. L., 2005: Moisture recycling on the Canadian Prairies for summer droughts and pluvials from 1997 to 2003. Agric. For. Meteor., 131 , 1326.

    • Search Google Scholar
    • Export Citation
  • Rapp, A. D., C. Kummerow, W. Berg, and B. Griffith, 2005: An evaluation of the proposed mechanism of the adaptive infrared iris hypothesis using TRMM VIRS and PR measurements. J. Climate, 18 , 41854194.

    • Search Google Scholar
    • Export Citation
  • Rauber, R. M., N. F. Laird, and H. T. Ochs III, 1996: Precipitation efficiency of trade wind clouds over the north central Pacific Ocean. J. Geophys. Res., 101 , 2624726253.

    • Search Google Scholar
    • Export Citation
  • Schär, C., D. Luthi, U. Beyerle, and E. Heise, 1999: The soil–precipitation feedback: A process study with a regional climate model. J. Climate, 12 , 722741.

    • Search Google Scholar
    • Export Citation
  • Shepherd, J. M., B. S. Ferrier, and P. S. Ray, 2001: Rainfall morphology in Florida convergence zones: A numerical study. Mon. Wea. Rev., 129 , 177197.

    • Search Google Scholar
    • Export Citation
  • Stewart, R. L., K. K. Szeto, R. F. Reinking, S. A. Clough, and S. P. Ballard, 1998: Midlatitude cyclonic cloud systems and their features affecting large scales and climate. Rev. Geophys., 36 , 243273.

    • Search Google Scholar
    • Export Citation
  • Tripoli, G. J., and W. R. Cotton, 1981: The use of ice-liquid water potential temperature as a thermodynamic variable in deep atmospheric models. Mon. Wea. Rev., 109 , 10941102.

    • Search Google Scholar
    • Export Citation
  • Tripoli, G. J., and W. R. Cotton, 1982: The Colorado State University three-dimensional cloud/mesoscale model—1982. Part I: General theoretical framework and sensitivity experiments. J. Rech. Atmos., 16 , 185220.

    • 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.

    • 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.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 70 25 1
PDF Downloads 29 16 1

Further Results on the Sensitivity of Simulated Storm Precipitation Efficiency to Environmental Temperature

View More View Less
  • 1 Universities Space Research Association, Huntsville, Alabama
Restricted access

Abstract

A method is devised for diagnosing the condensation rate in simulations using the Regional Atmospheric Modeling System (RAMS) model, where ice-liquid water potential temperature is a prognostic variable and an iterative procedure must be used to diagnose the temperature and water vapor mixing ratio from ice-liquid water potential temperature. The condensation rate is then used to compute the microphysical precipitation efficiency (PE), which is defined as the ratio of the precipitation rate at the ground to the sum of the condensation and deposition rates. Precipitation efficiency is compared for pairs of numerical simulations, initialized with soundings having all key environmental parameters identical except for their temperature. The authors’ previous study showed that with a colder initial sounding, the conversion of cloud water to precipitation is relatively inefficient, but updrafts are stronger and there is relatively less evaporation of precipitation, with the net result being a larger climatological PE in the colder environment. Here, the authors consider the time lag between condensation and precipitation and demonstrate that in calculating a properly lagged microphysical PE, the combined effect of the decreased production of precipitation and the decreased evaporation is that the temperature of the initial soundings has no significant influence on the microphysical PE. To the authors’ knowledge, this is the first time that the lag has been used to compute PE. These results concerning PE are relevant only to deep convection.

Corresponding author address: Charles Cohen, Universities Space Research Association, 320 Sparkman Drive, Huntsville, AL 35805. Email: cohen@usra.edu

Abstract

A method is devised for diagnosing the condensation rate in simulations using the Regional Atmospheric Modeling System (RAMS) model, where ice-liquid water potential temperature is a prognostic variable and an iterative procedure must be used to diagnose the temperature and water vapor mixing ratio from ice-liquid water potential temperature. The condensation rate is then used to compute the microphysical precipitation efficiency (PE), which is defined as the ratio of the precipitation rate at the ground to the sum of the condensation and deposition rates. Precipitation efficiency is compared for pairs of numerical simulations, initialized with soundings having all key environmental parameters identical except for their temperature. The authors’ previous study showed that with a colder initial sounding, the conversion of cloud water to precipitation is relatively inefficient, but updrafts are stronger and there is relatively less evaporation of precipitation, with the net result being a larger climatological PE in the colder environment. Here, the authors consider the time lag between condensation and precipitation and demonstrate that in calculating a properly lagged microphysical PE, the combined effect of the decreased production of precipitation and the decreased evaporation is that the temperature of the initial soundings has no significant influence on the microphysical PE. To the authors’ knowledge, this is the first time that the lag has been used to compute PE. These results concerning PE are relevant only to deep convection.

Corresponding author address: Charles Cohen, Universities Space Research Association, 320 Sparkman Drive, Huntsville, AL 35805. Email: cohen@usra.edu

Save