• Bougeault, P., and Coauthors, 2001: The MAP Special Observing Period. Bull. Amer. Meteor. Soc., 82 , 433462.

  • Brewster, K. A., 2003: Phase-correcting data assimilation and application to storm-scale numerical weather prediction. Part I: Model description and simulation testing. Mon. Wea. Rev., 131 , 480492.

    • 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 , 28022815.

    • Search Google Scholar
    • Export Citation
  • Colle, B. A., K. J. Westrick, and C. F. Mass, 1999: Evaluation of 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., M. F. Garvert, J. B. Wolfe, C. F. Mass, and C. P. Woods, 2005: The 13–14 December 2001 IMPROVE-2 event. Part III: Simulated microphysical budgets and sensitivity studies. J. Atmos. Sci., 62 , 35353558.

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

  • Davis, C., 1974: Ph.D. thesis, University of Wyoming, Dept. of Environ. Sci. (as cited in Pruppacher and Klett 1997).

  • Doswell III, C. A., C. Ramis, R. Romero, and S. Alonso, 1998: A diagnostic study of three heavy precipitation episodes in the Western Mediterranean region. Wea. Forecasting, 13 , 102124.

    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1993: A nonhydrostatic version of the Penn State–NCAR Mesoscale Model: Validation tests and simulation of an Atlantic cyclone and cold front. Mon. Wea. Rev., 121 , 14931513.

    • Search Google Scholar
    • Export Citation
  • Faccani, C., and R. Ferretti, 2005: Data assimilation of high density observations: Part I. Impact on the initial conditions for the MAP/SOP IOP2b. Quart. J. Roy. Meteor. Soc., 131 , 2142.

    • Search Google Scholar
    • Export Citation
  • Ferretti, R., and C. Faccani, 2005: Data assimilation of high density observations: Part II. Impact on the forecast of the precipitation for the MAP/SOP IOP2b. Quart. J. Roy. Meteor. Soc., 131 , 4361.

    • Search Google Scholar
    • Export Citation
  • Ferretti, R., T. Paolucci, G. Giuliani, T. Cherubini, L. Bernardini, and G. Visconti, 2003: Verification of high-resolution real-time forecasts over the Alpine region during the MAP SOP. Quart. J. Roy. Meteor. Soc., 129B , 587607.

    • Search Google Scholar
    • Export Citation
  • Fritsch, J., and J. Kain, 1993: Convective parameterization for mesoscale models: The Kain–Fritsch scheme. The Representation of Cumulus in Numerical Models, Meteor. Monogr., No. 46, Amer. Meteor. Soc., 165–177.

  • Garvert, M. F., C. P. Woods, B. A. Colle, C. F. Mass, P. V. Hobbs, M. T. Stoelinga, and J. B. Wolfe, 2005: The 13–14 December 2001 IMPROVE-2 event. Part II: Comparison of MM5 model simulations of clouds and precipitation with observations. J. Atmos. Sci., 62 , 35203534.

    • Search Google Scholar
    • Export Citation
  • Gilmore, M. S., J. M. Straka, and E. N. Rasmussen, 2004: Precipitation and evolution sensitivity in simulated deep convective storms: Comparisons between liquid-only and simple ice and liquid phase microphysics. Mon. Wea. Rev., 132 , 18971916.

    • Search Google Scholar
    • Export Citation
  • Grell, G., J. Dudhia, and D. Stauffer, 1994: A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5). NCAR Tech. Rep. NCAR/TN-389+IA, 122 pp.

  • 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
  • Jiusto, J., and G. Bosworth, 1971: Fall velocity of snowflakes. J. Appl. Meteor., 10 , 13521354.

  • Jolliffe, I. T., and D. B. Stephenson, 2004: Forecast verification: A Practitioner’s Guide in Atmospheric Science. John Wiley and Sons, 254 pp.

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

  • Lynn, B. H., A. P. Khain, J. Dudhia, D. Rosenfeld, A. Pokrovsky, and A. Seifert, 2005a: Spectral (bin) microphysics coupled with a mesoscale model (MM5). Part I: Model description and first results. Mon. Wea. Rev., 133 , 4458.

    • Search Google Scholar
    • Export Citation
  • Lynn, B. H., A. P. Khain, J. Dudhia, D. Rosenfeld, A. Pokrovsky, and A. Seifert, 2005b: Spectral (bin) microphysics coupled with a mesoscale model (MM5). Part II: Simulation of a CaPE rain event with a squall line. Mon. Wea. Rev., 133 , 5971.

    • Search Google Scholar
    • Export Citation
  • Marshall, J., and W. Palmer, 1948: The distribution of raindrops with size. J. Meteor., 5 , 165166.

  • Medina, S., and R. A. Houze, 2003: Airmotions and precipitation growth in alpine storms. Quart. J. Roy. Meteor. Soc., 129B , 342372.

  • Medina, S., B. F. Smull, and R. A. Houze, 2005: Cross-barrier flow during orographic precipitation events: Results from MAP and IMPROVE. J. Atmos. Sci., 62 , 35803598.

    • Search Google Scholar
    • Export Citation
  • Pruppacher, H. R., and J. D. Klett, 1997: Microphysics of Clouds and Precipitation. 2d ed. Kluwer Academic, 954 pp.

  • Reisner, J., R. Rasmussen, and R. Bruintjes, 1998: Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model. Quart. J. Roy. Meteor. Soc., 124 , 10711107.

    • Search Google Scholar
    • Export Citation
  • Richard, E., N. Asencio, R. Benoit, A. Buzzi, R. Ferretti, P. Malguzzi, S. Serafin, G. Zängl, and J-F. Georgis, 2002: Intercomparison of the simulated precipitation fields of the MAP/IOP2b with different high-resolution models. Proc. 10th Conf. on Mountain Meteorology and MAP Meeting, Park City, UT, Amer. Meteor. Soc., 167–170.

  • Rotunno, R., and R. Ferretti, 2003: Orographic effects on rainfall in MAP cases IOP2b and IOP8. Quart. J. Roy. Meteor. Soc., 129B , 373390.

    • Search Google Scholar
    • Export Citation
  • Stoelinga, M. T., and Coauthors, 2003: Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE). Bull. Amer. Meteor. Soc., 84 , 18071826.

    • Search Google Scholar
    • Export Citation
  • Tao, W-K., and J. Simpson, 1993: 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
  • Wilks, D. S., 1995: Statistical Methods in the Atmospheric Sciences. An Introduction. Academic Press, 467 pp.

  • Zampieri, M., P. Malguzzi, and A. Buzzi, 2005: Sensitivity of quantitative precipitation forecasts to boundary layer parameterization: A flash flood case study in the Western Mediterranean. Nat. Hazards Earth Syst. Sci., 5 , 603612.

    • Search Google Scholar
    • Export Citation
  • Zängl, G., 2004: The sensitivity of simulated orographic precipitation to model components other than cloud microphysics. Quart. J. Roy. Meteor. Soc., 130 , 18571875.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 32 32 32
PDF Downloads 2 2 2

Sensitivity of a Mesoscale Model to Microphysical Parameterizations in the MAP SOP Events IOP2b and IOP8

View More View Less
  • 1 Department of Physics/CETEMPS, University of L’Aquila, L’Aquila, Italy
Restricted access

Abstract

The sensitivity of a mesoscale model to different microphysical parameterizations is investigated for two events of precipitation in the Mediterranean region, that is, the Mesoscale Alpine Program (MAP) intensive observation periods (IOP) 2b (19–21 September 1999) and 8 (20–22 October 1999). Simulations are performed with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5); the most commonly used bulk microphysical parameterization schemes are evaluated, with a particular focus on their impact on the forecast of rainfall. To evaluate the forecast skill, the verification is carried out quantitatively by using the observations recorded by a high-resolution rain gauge network during the MAP campaign. The results show that, for the surface rainfall forecast, all microphysical schemes produce a similar precipitation field and none of them perform significantly better than the others. The ability of different schemes to reproduce events with different ongoing microphysical processes is briefly discussed by comparing model simulations and knowledge of hydrometeor fields from radar observations. The vertical profiles of hydrometeors from two of the analyzed schemes show gross similarities with available radar observations. Last, the role of one of the parameterizations appearing in a typical bulk microphysical scheme, that is, the one of the snowfall speed, is evaluated in detail. Adjustments in the semiempirical relationships describing the fall speed of snow particles have a large impact, because a reduced snowfall speed enhances precipitation on the lee side of mountain ridges and diminishes it on the windward side. Anyway, this effect does not appear to be able to largely improve or reduce the forecast skill of the MM5 systematically; the impact of changes in the parameterization of the snow deposition velocity very likely depends on the dynamics of the event under investigation.

* Current affiliation: Department of Civil and Environmental Engineering, University of Trento, Trento, Italy

Corresponding author address: Rossella Ferretti, Dept. of Physics/CETEMPS, University of L’Aquila, Via Vetoio, L’Aquila 67010, Italy. Email: rossella.ferretti@aquila.infn.it

Abstract

The sensitivity of a mesoscale model to different microphysical parameterizations is investigated for two events of precipitation in the Mediterranean region, that is, the Mesoscale Alpine Program (MAP) intensive observation periods (IOP) 2b (19–21 September 1999) and 8 (20–22 October 1999). Simulations are performed with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5); the most commonly used bulk microphysical parameterization schemes are evaluated, with a particular focus on their impact on the forecast of rainfall. To evaluate the forecast skill, the verification is carried out quantitatively by using the observations recorded by a high-resolution rain gauge network during the MAP campaign. The results show that, for the surface rainfall forecast, all microphysical schemes produce a similar precipitation field and none of them perform significantly better than the others. The ability of different schemes to reproduce events with different ongoing microphysical processes is briefly discussed by comparing model simulations and knowledge of hydrometeor fields from radar observations. The vertical profiles of hydrometeors from two of the analyzed schemes show gross similarities with available radar observations. Last, the role of one of the parameterizations appearing in a typical bulk microphysical scheme, that is, the one of the snowfall speed, is evaluated in detail. Adjustments in the semiempirical relationships describing the fall speed of snow particles have a large impact, because a reduced snowfall speed enhances precipitation on the lee side of mountain ridges and diminishes it on the windward side. Anyway, this effect does not appear to be able to largely improve or reduce the forecast skill of the MM5 systematically; the impact of changes in the parameterization of the snow deposition velocity very likely depends on the dynamics of the event under investigation.

* Current affiliation: Department of Civil and Environmental Engineering, University of Trento, Trento, Italy

Corresponding author address: Rossella Ferretti, Dept. of Physics/CETEMPS, University of L’Aquila, Via Vetoio, L’Aquila 67010, Italy. Email: rossella.ferretti@aquila.infn.it

Save