Editorial Type:
Article
Article Type:
Research Article

The 4–5 December 2001 IMPROVE-2 Event: Observed Microphysics and Comparisons with the Weather Research and Forecasting Model

Yanluan Lin School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York

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Brian A. Colle School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York

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Print Publication:
01 Apr 2009
DOI:
https://doi.org/10.1175/2008MWR2653.1
Page(s):
1372–1392
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Abstract

This paper highlights the observed and simulated microphysical evolution of a moderate orographic rainfall event over the central Oregon Cascade Range during 4–5 December 2001 of the Second Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2). Airborne in situ measurements illustrate the spatial variations in ice crystal distributions and amounts over the windward Cascades and within some convective cells. The in situ microphysical observations, ground radars, and surface observations are compared with four bulk microphysical parameterizations (BMPs) within the Weather Research and Forecasting (WRF) model. Those WRF BMP schemes that overpredict surface precipitation along the Cascade windward slopes are shown to have too rapid graupel (rimed snow) fallout. Most BMP schemes overpredict snow in the maximum snow depositional growth region aloft, which results in excessive precipitation spillover into the immediate lee of the Cascades. Meanwhile, there is underprediction to the east of the Cascades in all BMP schemes. Those BMPs that produce more graupel than snow generate nearly twice as much precipitation over the Oregon Coast Range as the other BMPs given the cellular convection in this region. Sensitivity runs suggest that the graupel accretion of snow generates too much graupel within select WRF BMPs. Those BMPs that generate more graupel than snow have shorter cloud residence times and larger removal of available water vapor. Snow depositional growth may be overestimated by 2 times within the BMPs when a capacitance for spherical particles is used rather than for snow aggregates. Snow mass–diameter relationships also have a large impact on the snow and cloud liquid water generation. The positive definite advection scheme for moisture and hydrometeors in the WRF reduces the surface precipitation by 20%–30% over the Coast Range and improves water conservation, especially where there are convective cells.

Corresponding author address: Dr. Brian A. Colle, School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794-5000. Email: brian.colle@stonybrook.edu

Abstract

This paper highlights the observed and simulated microphysical evolution of a moderate orographic rainfall event over the central Oregon Cascade Range during 4–5 December 2001 of the Second Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2). Airborne in situ measurements illustrate the spatial variations in ice crystal distributions and amounts over the windward Cascades and within some convective cells. The in situ microphysical observations, ground radars, and surface observations are compared with four bulk microphysical parameterizations (BMPs) within the Weather Research and Forecasting (WRF) model. Those WRF BMP schemes that overpredict surface precipitation along the Cascade windward slopes are shown to have too rapid graupel (rimed snow) fallout. Most BMP schemes overpredict snow in the maximum snow depositional growth region aloft, which results in excessive precipitation spillover into the immediate lee of the Cascades. Meanwhile, there is underprediction to the east of the Cascades in all BMP schemes. Those BMPs that produce more graupel than snow generate nearly twice as much precipitation over the Oregon Coast Range as the other BMPs given the cellular convection in this region. Sensitivity runs suggest that the graupel accretion of snow generates too much graupel within select WRF BMPs. Those BMPs that generate more graupel than snow have shorter cloud residence times and larger removal of available water vapor. Snow depositional growth may be overestimated by 2 times within the BMPs when a capacitance for spherical particles is used rather than for snow aggregates. Snow mass–diameter relationships also have a large impact on the snow and cloud liquid water generation. The positive definite advection scheme for moisture and hydrometeors in the WRF reduces the surface precipitation by 20%–30% over the Coast Range and improves water conservation, especially where there are convective cells.

Corresponding author address: Dr. Brian A. Colle, School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794-5000. Email: brian.colle@stonybrook.edu

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  • Baumgardner, D., 1983: An analysis and comparison of five water droplet measuring instruments. J. Climate Appl. Meteor., 22 , 891–910.

  • Bougeault, P., and Coauthors, 2001: The MAP special observing period. Bull. Amer. Meteor. Soc., 82 , 433–462.

  • Braun, S. A., 2006: High-resolution simulation of Hurricane Bonnie (1968). Part II: Water budget. J. Atmos. Sci., 63 , 43–64.

  • Brown, P. R. A., and P. N. Francis, 1995: Improved measurements of the ice water content in cirrus using a total-water probe. J. Atmos. Oceanic Technol., 12 , 410–414.

    • Search Google Scholar
    • Export Citation

  • Chen, S-H., and W-Y. Sun, 2002: A one-dimensional time dependent cloud model. J. Meteor. Soc. Japan, 80 , 99–118.

  • Colle, B. A., 2008: Two-dimensional idealized simulations of the impact of multiple windward ridges on orographic precipitation. J. Atmos. Sci., 65 , 509–523.

    • 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 , 593–617.

    • Search Google Scholar
    • Export Citation

  • Colle, B. A., M. F. Garvert, J. B. Wolfe, C. F. Mass, and C. P. Woods, 2005a: The 13–14 December 2001 IMPROVE-2 event. Part III: Simulated microphysical budgets and sensitivity studies. J. Atmos. Sci., 62 , 3535–3558.

    • Search Google Scholar
    • Export Citation

  • Colle, B. A., J. B. Wolfe, W. J. Steenburgh, D. E. Kingsmill, J. A. Cox, and J. C. Shafer, 2005b: High-resolution simulations and microphysical validation of an orographic precipitation event over the Wasatch Mountains during IPEX IOP3. Mon. Wea. Rev., 133 , 2947–2971.

    • Search Google Scholar
    • Export Citation

  • Colle, B. A., Y. Lin, S. Medina, and B. Smull, 2008: Orographic modification of convection and flow kinematics by the Oregon coastal range and Cascades during IMPROVE-2. Mon. Wea. Rev., 136 , 3894–3916.

    • Search Google Scholar
    • Export Citation

  • Cooper, W. A., 1986: Ice initiation in natural clouds. Precipitation Enhancement—A Scientific Challenge, Meteor. Monogr., No. 43, Amer. Meteor. Soc., 29–32.

    • 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 , 3077–3107.

    • Search Google Scholar
    • Export Citation

  • Field, P. R., R. J. Hogan, P. R. A. Brown, A. J. Illingworth, T. W. Choularton, and R. J. Cotton, 2005: Parametrization of ice-particle size distributions for mid-latitude stratiform cloud. Quart. J. Roy. Meteor. Soc., 131 , 1997–2017.

    • Search Google Scholar
    • Export Citation

  • Fukuta, N., and T. Takahashi, 1999: The growth of atmospheric ice crystals: A summary of findings in vertical supercooled cloud tunnel studies. J. Atmos. Sci., 56 , 1963–1979.

    • Search Google Scholar
    • Export Citation

  • Garvert, M. F., B. A. Colle, and C. F. Mass, 2005a: The 13–14 December 2001 IMPROVE-2 event. Part I: Synoptic and mesoscale evolution and comparison with a mesoscale model simulation. J. Atmos. Sci., 62 , 3474–3492.

    • Search Google Scholar
    • Export Citation

  • Garvert, M. F., C. P. Woods, B. A. Colle, C. F. Mass, P. V. Hobbs, M. T. Stoelinga, and J. B. Wolfe, 2005b: The 13–14 December 2001 IMPROVE-2 event. Part II: Comparisons of MM5 model simulations of clouds and precipitation with observations. J. Atmos. Sci., 62 , 3520–3534.

    • Search Google Scholar
    • Export Citation

  • Grubisić, V., R. K. Vellore, and A. W. Huggins, 2005: Quantitative precipitation forecasting of wintertime storms in the Sierra Nevada: Sensitivity to the microphysical parameterization and horizontal resolution. Mon. Wea. Rev., 133 , 2834–2859.

    • Search Google Scholar
    • Export Citation

  • Heymsfield, A. J., A. Bansemer, S. Lewis, J. Iaquinta, M. Kajikawa, C. Twohy, M. R. Poellot, and L. M. Miloshevich, 2002: A general approach for deriving the properties of cirrus and stratiform ice cloud particles. J. Atmos. Sci., 59 , 3–29.

    • Search Google Scholar
    • Export Citation

  • Hong, S-Y., and J. J. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6), 2006. J. Korean Meteor. Soc., 42 , 129–151.

  • Hong, S-Y., J. Dudhia, and S-H. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev., 132 , 103–120.

    • Search Google Scholar
    • Export Citation

  • Houze, R. A., and S. Medina, 2005: Turbulence as a mechanism for orographic precipitation enhancement. J. Atmos. Sci., 62 , 3599–3623.

  • Houze, R. A., P. V. Hobbs, P. H. Herzegh, and D. B. Parsons, 1979: Size distributions of precipitation particles in frontal clouds. J. Atmos. Sci., 36 , 156–162.

    • Search Google Scholar
    • Export Citation

  • Jiang, Q., and R. B. Smith, 2003: Cloud timescales and orographic precipitation. J. Atmos. Sci., 60 , 1159–1172.

  • Kain, J., and M. Fritsch, 1993: Convective parameterization for mesoscale models: The Kain–Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, Meteor. Monogr., No. 24, Amer. Meteor. Soc., 165–170.

    • Search Google Scholar
    • Export Citation

  • 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

  • King, W. D., D. A. Parkin, and R. J. Handsoworth, 1978: A hot wire liquid water device having fully calculated response characteristics. J. Appl. Meteor., 17 , 1809–1813.

    • Search Google Scholar
    • Export Citation

  • Koenig, L. R., 1971: Numerical modeling of ice deposition. J. Atmos. Sci., 28 , 226–237.

  • 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 , 1065–1092.

    • Search Google Scholar
    • Export Citation

  • Manning, K. W., and C. A. Davis, 1997: Verification and sensitivity experiments for the WISP94 MM5 forecasts. Wea. Forecasting, 12 , 719–735.

    • Search Google Scholar
    • Export Citation

  • Milbrandt, J. A., M. K. Yau, J. Mailhot, and S. Bélair, 2008: Simulation of an orographic precipitation event during IMPROVE-2. Part I: Evaluation of the control run using a triple-moment bulk microphysics scheme. Mon. Wea. Rev., 136 , 3873–3893.

    • Search Google Scholar
    • Export Citation

  • Reisner, J., R. M. Rasmussen, and R. T. Bruintjes, 1998: Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model. Quart. J. Roy. Meteor. Soc., 124 , 1071–1107.

    • Search Google Scholar
    • Export Citation

  • Richard, E., A. Buzzi, and G. Zängl, 2007: Quantitative precipitation forecasting in the Alps: The advances achieved by the Mesoscale Alpine Programme. Quart. J. Roy. Meteor. Soc., 133 , 831–846.

    • Search Google Scholar
    • Export Citation

  • Rogers, R. R., and M. K. Yau, 1989: A Short Course in Cloud Physics. Pergamon Press, 293 pp.

  • Rutledge, S. A., and P. V. Hobbs, 1983: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. VIII: A model for the “seeder–feeder” process in warm-frontal rainbands. J. Atmos. Sci., 40 , 1185–1206.

    • 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 midlatitude cyclones. XII: A diagnostic modeling study of precipitation development in narrow cold-frontal rainbands. J. Atmos. Sci., 41 , 2949–2972.

    • Search Google Scholar
    • Export Citation

  • Schultz, D. M., 2002: Understanding Utah winter storms: The Intermountain Precipitation Experiment. Bull. Amer. Meteor. Soc., 83 , 189–210.

    • Search Google Scholar
    • Export Citation

  • Skamarock, W. C., 2006: Positive-definite and monotonic limiters for unrestricted-time-step transport schemes. Mon. Wea. Rev., 134 , 2241–2250.

    • Search Google Scholar
    • Export Citation

  • Skamarock, W. C., and M. L. Weisman, 2009: The impact of positive-definite moisture transport on NWP precipitation forecasts. Mon. Wea. Rev., 137 , 488–494.

    • Search Google Scholar
    • Export Citation

  • Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers, 2005: A description of the Advanced Research WRF, version 2. NCAR Tech. Note NCAR/TN-468+STR, 88 pp. [Available from UCAR Communications, P.O. Box 3000, Boulder, CO 80307.].

    • Search Google Scholar
    • Export Citation

  • Smith, R. B., and I. Barstad, 2004: A linear theory of orographic precipitation. J. Atmos. Sci., 61 , 1377–1391.

  • Smith, R. B., Q. Jiang, M. Fearon, P. Tabary, M. Dorninger, and J. Doyle, 2003: Orographic precipitation and air mass transformation: An alpine example. Quart. J. Roy. Meteor. Soc., 129 , 433–454.

    • Search Google Scholar
    • Export Citation

  • Smith, R. B., I. Barstad, and L. Bonneau, 2005: Orographic precipitation and Oregon’s climate transition. J. Atmos. Sci., 62 , 177–191.

    • Search Google Scholar
    • Export Citation

  • Stoelinga, M. T., and Coauthors, 2003: Improvement of microphysical parameterization through observational verification experiment. Bull. Amer. Meteor. Soc., 84 , 1807–1826.

    • Search Google Scholar
    • Export Citation

  • Stoelinga, M. T., J. D. Locatelli, and C. P. Woods, 2007: The occurrence of “irregular” ice particles in stratiform clouds. J. Atmos. Sci., 64 , 2740–2750.

    • Search Google Scholar
    • Export Citation

  • Tao, W-K., and J. S. Simpson, 1993: Goddard cumulus ensemble model. Part I: Model description. Terr. Atmos. Oceanic Sci., 4 , 35–72.

  • Tao, W-K., J. S. Simpson, and M. McCumber, 1989: An ice-water saturation adjustment. Mon. Wea. Rev., 117 , 231–235.

  • 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 , 519–542.

    • Search Google Scholar
    • Export Citation

  • Thompson, G., P. R. Field, R. M. Rasmussen, and W. D. Hall, 2008: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization. Mon. Wea. Rev., 136 , 5095–5115.

    • 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 , 29–62.

    • Search Google Scholar
    • Export Citation

  • Westbrook, C. D., R. J. Hogan, and A. J. Illingworth, 2008: The capacitance of pristine ice crystals and aggregate snowflakes. J. Atmos. Sci., 65 , 206–219.

    • Search Google Scholar
    • Export Citation

  • Woods, C. P., M. T. Stoelinga, J. D. Locatelli, and P. V. Hobbs, 2005: Microphysical processes and synergistic interaction between frontal and orographic forcing of precipitation during the 13 December 2001 IMPROVE-2 event over the Oregon Cascades. J. Atmos. Sci., 62 , 3493–3519.

    • Search Google Scholar
    • Export Citation
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