Bulk Microphysical Sensitivities within the MM5 for Orographic Precipitation. Part I: The Sierra 1986 Event

Brian A. Colle Institute for Terrestrial and Planetary Atmospheres, State University of New York at Stony Brook, Stony Brook, New York

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Yanguang Zeng Institute for Terrestrial and Planetary Atmospheres, State University of New York at Stony Brook, Stony Brook, New York

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Abstract

This paper investigates the microphysical pathways and sensitivities within the Reisner2 bulk microphysical parameterization (BMP) of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) for a precipitation event over the central Sierra Nevada on 12 February 1986. Using a single sounding initialization, the MM5 was run two-dimensionally at 2-km horizontal grid spacing, which was needed to realistically simulate the embedded convective cells within the orographic cloud. Unlike previous modeling studies of this event, a microphysical budget over the windward slope was calculated for each experiment, in which the importance of each microphysical process was quantified relative to the water vapor loss (WVL) rate. For the control MM5, the largest microphysical processes that contribute to surface precipitation over the Sierra windward slope are condensation (63% of WVL), snow deposition (33%), riming to form graupel (35%), and melting of graupel (28%). The amount of supercooled water aloft is larger than observed and in previous modeling studies of this event using the Regional Atmospheric Modeling System (RAMS). The surface precipitation and microphysical processes over the Sierra Nevada are most sensitive to those parameters associated with the snow distribution, cloud condensation nuclei (CCN) concentrations, and snow/graupel fall speeds, while there is less sensitivity to ice initiation and autoconversions; however, all experiments overpredict the surface precipitation over the windward slope. If ice production is turned off in the cloud-ice region (above 7 km or <250 K), deposition acting on the small amount of cloud ice nucleated at warmer temperatures can still generate a similar snow cloud below 4 km and surface precipitation. The precipitation differences between the BMPs in the MM5 are greater than any single process experiment within Reisner2. The process experiments do help reveal some of the fundamental differences between BMP schemes.

Corresponding author address: Dr. B. A. Colle, Marine Sciences Research Center, State University of New York at Stony Brook, Stony Brook, NY 11794-5000. Email: bcolle@notes.cc.sunysb.edu

Abstract

This paper investigates the microphysical pathways and sensitivities within the Reisner2 bulk microphysical parameterization (BMP) of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) for a precipitation event over the central Sierra Nevada on 12 February 1986. Using a single sounding initialization, the MM5 was run two-dimensionally at 2-km horizontal grid spacing, which was needed to realistically simulate the embedded convective cells within the orographic cloud. Unlike previous modeling studies of this event, a microphysical budget over the windward slope was calculated for each experiment, in which the importance of each microphysical process was quantified relative to the water vapor loss (WVL) rate. For the control MM5, the largest microphysical processes that contribute to surface precipitation over the Sierra windward slope are condensation (63% of WVL), snow deposition (33%), riming to form graupel (35%), and melting of graupel (28%). The amount of supercooled water aloft is larger than observed and in previous modeling studies of this event using the Regional Atmospheric Modeling System (RAMS). The surface precipitation and microphysical processes over the Sierra Nevada are most sensitive to those parameters associated with the snow distribution, cloud condensation nuclei (CCN) concentrations, and snow/graupel fall speeds, while there is less sensitivity to ice initiation and autoconversions; however, all experiments overpredict the surface precipitation over the windward slope. If ice production is turned off in the cloud-ice region (above 7 km or <250 K), deposition acting on the small amount of cloud ice nucleated at warmer temperatures can still generate a similar snow cloud below 4 km and surface precipitation. The precipitation differences between the BMPs in the MM5 are greater than any single process experiment within Reisner2. The process experiments do help reveal some of the fundamental differences between BMP schemes.

Corresponding author address: Dr. B. A. Colle, Marine Sciences Research Center, State University of New York at Stony Brook, Stony Brook, NY 11794-5000. Email: bcolle@notes.cc.sunysb.edu

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  • Berry, E. X., and R. L. Reinhardt, 1974: An analysis of cloud drop growth by collection. Part IV: A new parameterization. J. Atmos. Sci, 31 , 21272135.

    • Search Google Scholar
    • Export Citation
  • Bosart, L. F., 2003: Whither the weather analysis and forecasting process? Wea. Forecasting, 18 , 520529.

  • Braun, S. A., and W-K. Tao, 2000: Sensitivity of high-resolution simulations of Hurricane Bob (1991) to planetary boundary layer parameterizations. Mon. Wea. Rev, 128 , 39413961.

    • Search Google Scholar
    • Export Citation
  • Brown, P. R. A., and H. A. Swann, 1997: Evaluation of key microphysical parameters in three-dimensional cloud-model simulation using aircraft and multiparameter radar data. Quart. J. Roy. Meteor. Soc, 123 , 22452275.

    • Search Google Scholar
    • Export Citation
  • Bruintjes, R. T., T. L. Clark, and W. D. Hall, 1994: Interactions between topographic airflow and cloud/precipitation development during the passage of a winter storm in Arizona. J. Atmos. Sci, 51 , 4867.

    • Search Google Scholar
    • Export Citation
  • Burrows, D. A., 1992: Evaluation of a two-dimensional kinematic cloud model using data from a central Sierra Nevada orographic cloud system. J. Appl. Meteor, 31 , 5163.

    • Search Google Scholar
    • Export Citation
  • Charba, J. P., D. W. Reynolds, B. E. McDonald, and G. M. Carter, 2003: Comparative verification of recent quantitative precipitation forecasts in the National Weather Service: A simple approach for scoring forecast accuracy. Wea. Forecasting, 18 , 161183.

    • Search Google Scholar
    • Export Citation
  • Colle, B. A., 2004: Sensitivity of orographic precipitation to changing ambient conditions and terrain geometries: An idealized modeling perspective. J. Atmos. Sci, 61 , 588606.

    • Search Google Scholar
    • Export Citation
  • Colle, B. A., and C. F. Mass, 2000: The 5–9 February 1996 flooding event over the Pacific Northwest: Sensitivity studies and evaluation of the MM5 precipitation forecasts. Mon. Wea. Rev, 128 , 593617.

    • Search Google Scholar
    • Export Citation
  • Colle, B. A., and Y. Zeng, 2004: Bulk microphysical sensitivities within the MM5 for orographic precipitation. Part II: Impact of barrier width and freezing level. Mon. Wea. Rev.,132, 2802–2815.

    • Search Google Scholar
    • Export Citation
  • Colle, B. A., K. J. Westrick, and C. F. Mass, 1999: Evaluation of the MM5 and Eta-10 precipitation forecasts over the Pacific Northwest during the cool season. Wea. Forecasting, 14 , 137154.

    • Search Google Scholar
    • Export Citation
  • Colle, B. A., C. F. Mass, and K. J. Westrick, 2000: MM5 precipitation verification over the Pacific Northwest during the 1997–1999 cool seasons. Wea. Forecasting, 15 , 730744.

    • Search Google Scholar
    • Export Citation
  • Cooper, W. A., 1986: Ice initiation in natural clouds. Precipitation Enhancement—A Scientific Challenge, Meteor. Monogr., No. 21, Amer. Meteor. Soc., 29–32.

    • Search Google Scholar
    • Export Citation
  • Cox, G. P., 1988: Modeling precipitation in frontal rainbands. Quart. J. Roy. Meteor. Soc, 114 , 115127.

  • Doyle, J. D., and Coauthors, 2000: An intercomparison of model-predicted wave breaking for the 11 January 1972 Boulder windstorm. Mon. Wea. Rev, 128 , 901914.

    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci, 46 , 30773107.

    • Search Google Scholar
    • Export Citation
  • Ferrier, B. S., 1994: A double-moment, multiple-phase, four-class bulk ice scheme. Part I: Description. J. Atmos. Sci, 51 , 249280.

  • Ferrier, B. S., W-K. Tao, and J. Simpson, 1995: A double-moment, multiple-phase, four-class bulk ice scheme. Part II: Simulations of convective storms in different large-scale environments and comparisons with other bulk parameterizations. J. Atmos. Sci, 52 , 10011033.

    • Search Google Scholar
    • Export Citation
  • Flatau, P. J., G. J. Tripoli, J. Verlinde, and W. R. Cotton, 1989: The CSU–RAMS cloud microphysical module: General theory and code documentation. Atmospheric Science Paper 451, 88 pp. [Available from Colorado State University, Dept. of Atmospheric Science, Fort Collins, CO 80523.].

    • Search Google Scholar
    • Export Citation
  • Fletcher, N. H., 1962: Physics of Rain Clouds. Cambridge University Press, 386 pp.

  • Fritsch, J. M., and Coauthors, 1998: Quantitative precipitation forecasting: Report of the eighth prospectus development team, U.S. Weather Research Program. Bull. Amer. Meteor. Soc, 79 , 285299.

    • Search Google Scholar
    • Export Citation
  • Gaudet, B., and W. R. Cotton, 1998: Statistical characteristics of real-time precipitation forecasting model. Wea. Forecasting, 13 , 966982.

    • Search Google Scholar
    • Export Citation
  • Grell, G. A., J. Dudhia, and D. R. Stauffer, 1994: A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5). NCAR Tech. Note NCAR/TN-398+STR, 138 pp. [Available from National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307.].

    • Search Google Scholar
    • Export Citation
  • Hallet, M. F., and S. C. Mossop, 1974: Production of secondary ice particles during the riming process. Nature, 249 , 2628.

  • Hobbs, P. V., 1975: The nature of winter clouds and precipitation in the Cascade Mountains and their modification by artificial seeding. Part I: Natural conditions. J. Appl. Meteor, 14 , 783804.

    • Search Google Scholar
    • Export Citation
  • Hobbs, P. V., and P. O. G. Persson, 1982: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. Part V: The substructure of narrow cold-frontal rainbands. J. Atmos. Sci, 39 , 280295.

    • Search Google Scholar
    • Export Citation
  • Hobbs, P. V., T. J. Matejka, P. H. Herzegh, J. D. Locatelli, and R. A. Houze Jr., 1980: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. I: A case study of a cold front. J. Atmos. Sci, 37 , 568596.

    • Search Google Scholar
    • Export Citation
  • Hong, S-Y., and H-L. Pan, 1996: Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon. Wea. Rev, 124 , 23222339.

    • Search Google Scholar
    • Export Citation
  • Houze, R. A., P. V. Hobbs, and P. H. Herzegh, 1979: Size distributions of precipitation particles in frontal clouds. J. Atmos. Sci, 36 , 156162.

    • Search Google Scholar
    • Export Citation
  • Hsie, E. Y., R. A. Anthes, and D. Keyser, 1984: Numerical simulation of frontogenesis in a moist atmosphere. J. Atmos. Sci, 41 , 25812594.

    • Search Google Scholar
    • Export Citation
  • Jiang, Q., 2003: Moist dynamics and orographic precipitation. Tellus, 55A , 301316.

  • Jiang, Q., and R. B. Smith, 2003: Cloud timescales and orographic precipitation. J. Atmos. Sci, 60 , 11591172.

  • Kessler, E., 1969: On the Distribution and Continuity of Water Substance in Atmospheric Circulations. Meteor. Monogr., No. 32, Amer. Meteor. Soc., 84 pp.

    • Search Google Scholar
    • Export Citation
  • Klemp, J. B., and D. R. Durran, 1983: An upper boundary condition permitting internal gravity wave radiation in numerical mesoscale models. Mon. Wea. Rev, 111 , 430444.

    • Search Google Scholar
    • Export Citation
  • Lin, Y. L., R. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor, 22 , 10651092.

    • Search Google Scholar
    • Export Citation
  • Locatelli, J. D., and P. V. Hobbs, 1974: Fall speeds and masses of solid precipitation particles. J. Geophys. Res, 79 , 21852197.

  • Meyers, M. P., and W. R. Cotton, 1992: Evaluation of the potential for wintertime quantitative precipitation forecasting over mountainous terrain with an explicit cloud model. Part I: Two-dimensional sensitivity experiments. J. Appl. Meteor, 31 , 2650.

    • Search Google Scholar
    • Export Citation
  • Meyers, M. P., P. J. Demott, and W. R. Cotton, 1992: New primary ice-nucleation parameterization in an explicit cloud model. J. Appl. Meteor, 31 , 708721.

    • Search Google Scholar
    • Export Citation
  • Rasmussen, R. M., and Coauthors, 1992: Winter Icing and Storm Projects (WISP). Bull. Amer. Meteor. Soc, 73 , 951974.

  • Rasmussen, R. M., I. Geresdi, G. Thompson, K. Manning, and E. Karplus, 2002: Freezing drizzle formation in stably stratified layer clouds: The role of radiative cooling of cloud droplets, cloud condensation nuclei, and ice initiation. J. Appl. Meteor, 59 , 837860.

    • Search Google Scholar
    • Export Citation
  • Rauber, R. M., 1992: Microphysical structure and evolution of a Sierra Nevada shallow orographic cloud system. J. Appl. Meteor, 31 , 324.

    • Search Google Scholar
    • Export Citation
  • Reisner, J., R. M. Rasmussen, and R. T. Bruintjes, 1998: Explicit forecasting of supercooled liquid water in winter storm using the MM5 mesoscale model. Quart. J. Roy. Meteor. Soc, 124 , 10711107.

    • Search Google Scholar
    • Export Citation
  • Reynolds, D. W., and A. S. Dennis, 1986: A review of the Sierra Cooperative Pilot Project. Bull. Amer. Meteor. Soc, 67 , 513523.

  • Rutledge, S. A., and P. V. Hobbs, 1983: The mesoscale and microscale structure and organization of clouds and precipitation in mid-latitude cyclones: A model for the “seeder-feeder” process in warm-frontal rainbands. J. Atmos. Sci, 40 , 11851206.

    • Search Google Scholar
    • Export Citation
  • Rutledge, S. A., and P. V. Hobbs, 1984: The mesoscale and microscale structure and organization of clouds and precipitation in mid-latitude cyclones: A diagnostic modeling study of precipitation development in narrow cold-frontal rainbands. J. Atmos. Sci, 41 , 29492972.

    • Search Google Scholar
    • Export Citation
  • Schultz, P., 1995: An explicit cloud physics parameterization for operational numerical weather prediction. Mon. Wea. Rev, 123 , 33313343.

    • Search Google Scholar
    • Export Citation
  • Sekhon, R. S., and R. C. Srivastava, 1970: Snow size spectra and radar reflectivity. J. Atmos. Sci, 27 , 299307.

  • Stoelinga, M., and Coauthors, 2003: Improvement of microphysical parameterizations through observational verification experiments (IMPROVE). Bull. Amer. Meteor. Soc, 84 , 18071826.

    • Search Google Scholar
    • Export Citation
  • Tao, W-K., and J. Simpson, 1993: The Goddard Cumulus Ensemble Model. Part I: Model description. Terr. Atmos. Oceanic Sci, 4 , 3572.

  • Thompson, G., R. M. Rasmussen, and K. Manning, 2004: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis. Mon. Wea. Rev, 132 , 519542.

    • Search Google Scholar
    • Export Citation
  • Twomey, S., and T. A. Wojciechowski, 1969: Observations of the geographic variation of cloud nuclei. J. Atmos. Sci, 26 , 684688.

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