Editorial Type:
Article
Article Type:
Research Article

An Improved Modeling Scheme for Freezing Precipitation Forecasts

André Tremblay Cloud Physics Research Division, Atmospheric Environment Service, Dorval, Quebec, Canada

Search for other papers by André Tremblay in
Current site
Google Scholar
PubMed Close
and
Anna Glazer Cloud Physics Research Division, Atmospheric Environment Service, Dorval, Quebec, Canada

Search for other papers by Anna Glazer in
Current site
Google Scholar
PubMed Close
Print Publication:
01 May 2000
DOI:
https://doi.org/10.1175/1520-0493(2000)128<1289:AIMSFF>2.0.CO;2
Page(s):
1289–1308
Restricted access

Abstract

To improve forecasts of various weather elements (snow, rain, and freezing precipitation) in numerical weather prediction models, a new mixed-phase cloud scheme has been developed. The scheme is based on a single prognostic equation for total water content and includes parameterization of key cloud microphysical processes. The three-dimensional forecasts of solid particles, liquid, and supercooled cloud droplets and different precipitation types are typical outputs of the cloud scheme. It is shown that the scheme compares reasonably well with available meteorological observations. A novel aspect embodied in the scheme is the explicit inclusion of physical processes for the formation of supercooled liquid water. Thus, it is possible to model freezing precipitation and supercooled cloud droplets in the absence of the melting ice mechanism. The inclusion of the supercooled liquid water mechanism increased significantly the probability of detection of freezing precipitation and improved the bias score over the melting ice algorithm alone.

Corresponding author address: Dr. André Tremblay, Cloud Physics Research Division, Atmospheric Environment Service, 2121 Trans Canada Highway, Dorval, PQ H9P 1J3, Canada.

Email: andre.tremblay@ec.gc.ca

Abstract

To improve forecasts of various weather elements (snow, rain, and freezing precipitation) in numerical weather prediction models, a new mixed-phase cloud scheme has been developed. The scheme is based on a single prognostic equation for total water content and includes parameterization of key cloud microphysical processes. The three-dimensional forecasts of solid particles, liquid, and supercooled cloud droplets and different precipitation types are typical outputs of the cloud scheme. It is shown that the scheme compares reasonably well with available meteorological observations. A novel aspect embodied in the scheme is the explicit inclusion of physical processes for the formation of supercooled liquid water. Thus, it is possible to model freezing precipitation and supercooled cloud droplets in the absence of the melting ice mechanism. The inclusion of the supercooled liquid water mechanism increased significantly the probability of detection of freezing precipitation and improved the bias score over the melting ice algorithm alone.

Corresponding author address: Dr. André Tremblay, Cloud Physics Research Division, Atmospheric Environment Service, 2121 Trans Canada Highway, Dorval, PQ H9P 1J3, Canada.

Email: andre.tremblay@ec.gc.ca

Save
Cover Monthly Weather Review
Monthly Weather Review

  • Appleman, H., 1954: Design of a cloud-phase chart. Bull. Amer. Meteor. Soc.,35, 223–225.

  • Asai, T., 1965: A numerical study of air-mass transformation over the Japan sea in winter. J. Meteor. Soc. Japan,43, 1–15.

  • Benoit, R., M. Desgagne, P. Pellerin, S. Pellerin, Y. Chartier, and S. Desjardins, 1997: The Canadian MC2: A semi-Lagrangian, semi-implicit wideband atmospheric model suited for finescale process studies and simulation. Mon. Wea. Rev.,125, 2382–2415.

  • Bocchieri, J. R., 1980: The objective use of upper air sounding to specify precipitation type. Mon. Wea. Rev.,108, 596–603.

  • Brooks, C. F., 1920: The nature of sleet and how it is formed. Mon. Wea. Rev.,48, 69–73.

  • Brown, B. G., 1996: Verification of in-flight icing forecasts: Methods and issues. Proc. FAA Int. Conf. on In-Flight Aircraft Icing, Springfield, VA, Department of Transportation, Federal Aviation Administration, 319–330.

  • Carlson, T. N., 1980: Airflow through midlatitude cyclones and the comma cloud pattern. Mon. Wea. Rev.,108, 1498–1509.

  • Cober, S. G., J. W. Strapp, and G. A. Isaac, 1996: An example of supercooled drizzle drop formed through a collision-coalescence process. J. Appl. Meteor.,35, 2250–2260.

  • Czys, R. R., R. W. Scott, K. C. Tang, R. W. Przybylinski, and M. E. Sabones, 1996: A physically based, non-dimensional parameter for discriminating between locations of freezing rain and ice pellets. Wea. Forecasting,11, 591–598.

  • Doswell, C. A., R. Davies-Jones, and D. L. Keller, 1990: On summary measures of skill in rare event forecasting based on contingency tables. Wea. Forecasting,5, 576–585.

  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon using a mesoscale two-dimensional model. J. Atmos. Sci.,46, 3077–3107.

  • Glazer, A., A. Tremblay, J. Mailhot, B. Bilodeau, S. Belair, and G. Isaac, 1999: Mesoscale modeling during FIRE.ACE: 2. Modeled arctic clouds and aircraft observations. Preprints, Fifth Conf. on Polar Meteorology and Oceanography, Dallas, TX, Amer. Meteor. Soc., 180–185.

  • Huffman, G. J., and G. A. Norman, 1988: The supercooled warm rain process and the specification of freezing precipitation. Mon. Wea. Rev.,116, 2172–2182.

  • Isaac, G. A., S. G. Cober, A. V. Korolev, J. W. Strapp, A. Tremblay, and D. L. Marcotte, 1998: Overview of the Canadian Freezing Drizzle Experiments I, II, and III. Preprints, Conf. on Cloud Physics, Everett, WA, Amer. Meteor. Soc., 447–450.

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

  • Laprise, R., 1995: The formulation of Andre Robert MC2 (Mesoscale Compressible Community) model. Atmos.–Ocean,35, 195–200.

  • Lin, Y. L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor.,22, 1065–1092.

  • Locatelli, J. D., and P. V. Hobbs, 1974: Fall speeds and masses of solid precipitation particles. J. Geophys. Res.,79, 2185–2197.

  • Marshall, J. S., and W. McK. Palmer, 1948: The distribution of raindrops with size. J. Meteor.,5, 165–166.

  • Marwitz J., M. Politovich, B. Bernstein, F. Ralph, P. Neiman, R. Ashenden, and J. Bresch, 1997: Meteorological conditions associated with the ATR72 aircraft accident near Roselawn, Indiana, on 31 October 1994. Bull. Amer. Meteor. Soc.,78, 41–52.

  • Meyers, M. P., P. J. DeMott, and W. R. Cotton, 1992: New primary ice-nucleation parameterizations in an explicit cloud model. J. Appl. Meteor.,31, 708–721.

  • Mitchell, D. L., 1991: Evolution of snow-size spectra in cyclonic storms. Part II: Deviation of the exponential form. J. Atmos. Sci.,48, 1885–1898.

  • ——, 1994: A model predicting the evolution of ice particle size spectra and radiative properties of cirrus clouds. Part I: Microphysics. J. Atmos. Sci.,51, 797–816.

  • Moss, S. J., and D. W. Johnson, 1994: Aircraft measurements to validate and improve numerical model parameterizations of ice to water ratios in clouds. Atmos. Res.,34, 1–25.

  • Murphy, A. H., and R. L. Winkler, 1987: A general framework for forecast verification. Mon. Wea. Rev.,115, 1330–1338.

  • Ogura, Y., and T. Takahashi, 1971: Numerical simulation of the life cycle of a thunderstorm cell. Mon. Wea. Rev.,99, 895–911.

  • Penn, S., 1957: The prediction of snow vs. rain. Forecasting Guide No. 2, U.S. Weather Bureau, 29 pp.

  • Robert, A., 1993: Bubble convection experiments with a semi-implicit formulation of the Euler equations. J. Atmos. Sci.,50, 1865–1873.

  • ——, T. L. Yee, and H. Ritchie, 1985: A semi-Lagrangian and semi-implicit numerical integration scheme for multilevel atmospheric models. Mon. Wea. Rev.,113, 388–394.

  • Rutledge, S. A., and P. V. Hobbs, 1984: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. XII: A diagnostic modeling study of precipitation development in narrow cold-frontal rainbands. J. Atmos. Sci.,41, 2949–2972.

  • Schultz, P., and M. K. Politovich, 1992: Toward the improvement of aircraft-icing forecasts for the continental United States. Wea. Forecasting,7, 491–500.

  • Sekhon, R. S., and R. C. Srivastava, 1970: Snow size spectra and radar reflectivity. J. Atmos. Sci.,27, 299–307.

  • Smith, R. N. B., 1990: A scheme for predicting layer clouds and their water content in a general circulation model. Quart. J. Roy. Meteor. Soc.,116, 435–460.

  • Stanski, H. R., L. J. Wilson, and W. R. Burrows, 1989: Survey of common verification methods in meteorology. World Weather Watch Tech. Rep. 8, WMO/TD 358, 113 pp.

  • Strapp, J. W., R. A. Stuart, and G. A. Isaac, 1996: A Canadian climatology of freezing precipitation and a detailed study using data from St. John’s, Newfoundland. Proceedings of the FAA International Conference on In-flight Aircraft Icing, Vol. II, DOT/FAA/AR-96/81, II, 45–56.

  • Sundqvist, H., 1993: Inclusion of ice phase of hydrometeors in cloud parameterization for mesoscale and large-scale models. Beitr. Phys. Atmos.,66, 137–147.

  • ——, E. Berge, and J. E. Kristjansson, 1989: Condensation and cloud parameterization studies with a mesoscale numerical weather prediction model. Mon. Wea. Rev.,117, 1641–1657.

  • Tanguay, M., A. Robert, and R. Laprise, 1990: A semi-implicit semi-Lagrangian fully compressible regional forecast model. Mon. Wea. Rev.,118, 1970–1980.

  • Thompson, G., R. T. Bruintjes, B. G. Brown, and F. Hage, 1997: Intercomparison of in-flight icing algorithms. Part I: WISP94 real-time icing prediction and evaluation program. Wea. Forecasting,12, 878–889.

  • Tiedtke, M., 1993: Representation of clouds in large-scale models. Mon. Wea. Rev.,121, 3040–3061.

  • Tremblay, A., 1994: Simulations of the 14 July 1987 squall line using a fully compressible model. Atmos.–Ocean,32, 567–603.

  • ——, A. Glazer, W. Szyrmer, and W. Yu, 1994: Mesoscale simulations of cloud microphysics within a winter storm: some implications for large-scale ice phase schemes. ECMWF/GCSS Workshop on Modeling and Assimilation of Clouds, Reading, United Kingdom, ECMWF, 337–346.

  • ——, ——, ——, G. Isaac, and I. Zawadzki, 1995: Forecasting of supercooled clouds. Mon. Wea. Rev.,123, 2098–2113.

  • ——, S. G. Cober, A. Glazer, and G. Isaac, 1996a: An intercomparison of mesoscale forecasts of aircraft icing using SSM/I retrievals. Wea. Forecasting,11, 66–77.

  • ——, A. Glazer, W. Yu, and R. Benoit, 1996b: An explicit cloud scheme based on a single prognostic equation. Tellus,18A, 483–500.

  • 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, 29–62.

  • Zawadzki, I., L. Ostiguy, and R. Laprise, 1993: Retrieval of the microphysical properties in a CASP storm by numerical integration of a numerical kinematic model. Atmos.–Ocean,31, 201–233.

  • Zhang, D. L., 1989: The effect of parameterized ice microphysics on the simulation of vortex circulation with a mesoscale hydrostatic model. Tellus,41A, 132–147.

  • Zhao, Q., L. B. Black, and M. E. Baldwin, 1997: Implementation of the cloud prediction scheme in the eta model at NCEP. Wea. Forecasting,12, 697–712.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 809 42 10
PDF Downloads 63 26 8