An Evaluation of Microphysics Fields from Mesoscale Model Simulations of Tropical Cyclones. Part I: Comparisons with Observations

Robert F. Rogers NOAA/AOML Hurricane Research Division, Miami, Florida

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Michael L. Black NOAA/AOML Hurricane Research Division, Miami, Florida

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Shuyi S. Chen Department of Meteorology and Physical Oceanography, Rosenstiel School for Marine and Atmospheric Science, University of Miami, Miami, Florida

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Robert A. Black NOAA/AOML Hurricane Research Division, Miami, Florida

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Abstract

This study presents a framework for comparing hydrometeor and vertical velocity fields from mesoscale model simulations of tropical cyclones with observations of these fields from a variety of platforms. The framework is based on the Yuter and Houze constant frequency by altitude diagram (CFAD) technique, along with a new hurricane partitioning technique, to compare the statistics of vertical motion and reflectivity fields and hydrometeor concentrations from two datasets: one consisting of airborne radar retrievals and microphysical probe measurements collected from tropical cyclone aircraft flights over many years, and another consisting of cloud-scale (1.67-km grid length) tropical cyclone simulations using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). Such comparisons of the microphysics fields can identify biases in the simulations that may lead to an identification of deficiencies in the modeling system, such as the formulation of various physical parameterization schemes used in the model. Improvements in these schemes may potentially lead to better forecasts of tropical cyclone intensity and rainfall.

In Part I of this study, the evaluation framework is demonstrated by comparing the radar retrievals and probe measurements to MM5 simulations of Hurricanes Bonnie (1998) and Floyd (1999). Comparisons of the statistics from the two datasets show that the model reproduces many of the gross features seen in the observations, though notable differences are evident. The general distribution of vertical motion is similar between the observations and simulations, with the strongest up- and downdrafts making up a small percentage of the overall population in both datasets, but the magnitudes of vertical motion are weaker in the simulations. The model-derived reflectivities are much higher than observed, and correlations between vertical motion and hydrometeor concentration and reflectivity show a much stronger relationship in the model than what is observed. Possible errors in the data processing are discussed as potential sources of differences between the observed and simulated datasets in Part I. In Part II, attention will be focused on using the evaluation framework to investigate the role that different model configurations (i.e., different resolutions and physical parameterizations) play in producing different microphysics fields in the simulation of Hurricane Bonnie. The microphysical and planetary boundary layer parameterization schemes, as well as higher horizontal and vertical resolutions, will be tested in the simulation to identify the extent to which changes in these schemes are reflected in improvements of the statistical comparisons with the observations.

Corresponding author address: Robert F. Rogers, NOAA/AOML Hurricane Research Division, 4301 Rickenbacker Causeway, Miami, FL 33149. Email: robert.rogers@noaa.gov

Abstract

This study presents a framework for comparing hydrometeor and vertical velocity fields from mesoscale model simulations of tropical cyclones with observations of these fields from a variety of platforms. The framework is based on the Yuter and Houze constant frequency by altitude diagram (CFAD) technique, along with a new hurricane partitioning technique, to compare the statistics of vertical motion and reflectivity fields and hydrometeor concentrations from two datasets: one consisting of airborne radar retrievals and microphysical probe measurements collected from tropical cyclone aircraft flights over many years, and another consisting of cloud-scale (1.67-km grid length) tropical cyclone simulations using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). Such comparisons of the microphysics fields can identify biases in the simulations that may lead to an identification of deficiencies in the modeling system, such as the formulation of various physical parameterization schemes used in the model. Improvements in these schemes may potentially lead to better forecasts of tropical cyclone intensity and rainfall.

In Part I of this study, the evaluation framework is demonstrated by comparing the radar retrievals and probe measurements to MM5 simulations of Hurricanes Bonnie (1998) and Floyd (1999). Comparisons of the statistics from the two datasets show that the model reproduces many of the gross features seen in the observations, though notable differences are evident. The general distribution of vertical motion is similar between the observations and simulations, with the strongest up- and downdrafts making up a small percentage of the overall population in both datasets, but the magnitudes of vertical motion are weaker in the simulations. The model-derived reflectivities are much higher than observed, and correlations between vertical motion and hydrometeor concentration and reflectivity show a much stronger relationship in the model than what is observed. Possible errors in the data processing are discussed as potential sources of differences between the observed and simulated datasets in Part I. In Part II, attention will be focused on using the evaluation framework to investigate the role that different model configurations (i.e., different resolutions and physical parameterizations) play in producing different microphysics fields in the simulation of Hurricane Bonnie. The microphysical and planetary boundary layer parameterization schemes, as well as higher horizontal and vertical resolutions, will be tested in the simulation to identify the extent to which changes in these schemes are reflected in improvements of the statistical comparisons with the observations.

Corresponding author address: Robert F. Rogers, NOAA/AOML Hurricane Research Division, 4301 Rickenbacker Causeway, Miami, FL 33149. Email: robert.rogers@noaa.gov

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  • Barnes, G. M., and M. D. Powell, 1995: Evolution of the inflow boundary layer of Hurricane Gilbert (1988). Mon. Wea. Rev., 123 , 23482368.

    • Search Google Scholar
    • Export Citation
  • Black, M. L., R. W. Burpee, and F. D. Marks Jr., 1996: Vertical motion characteristics of tropical cyclones determined with airborne Doppler radial velocities. J. Atmos. Sci., 53 , 18871909.

    • Search Google Scholar
    • Export Citation
  • Black, R. A., 1990: Radar reflectivity-ice water content relationships for use above the melting level in hurricanes. J. Appl. Meteor., 29 , 955961.

    • Search Google Scholar
    • Export Citation
  • Black, R. A., and J. Hallett, 1986: Observations of the distribution of ice in hurricanes. J. Atmos. Sci., 43 , 802822.

  • Black, R. A., H. B. Bluestein, and M. L. Black, 1994: Unusually strong vertical motions in a Caribbean hurricane. Mon. Wea. Rev., 122 , 27222739.

    • Search Google Scholar
    • Export Citation
  • Black, R. A., G. M. Heymsfield, and J. Hallett, 2003: Extra large particle images at 12 km in a hurricane eyewall: Evidence of high-altitude supercooled water? Geophys. Res. Lett., 30 .2124, doi:10:1029/2003GF017864.

    • Search Google Scholar
    • Export Citation
  • Blackadar, A. K., 1979: High resolution models of the planetary boundary layer. Advances in Environmental Science and Engineering, Vol. 1, J. Pfafflin and E. Ziegler, Eds., Gordon and Breach Science, 50–85.

    • Search Google Scholar
    • Export Citation
  • Braun, S. A., 2002: A cloud-resolving simulation of Hurricane Bob (1991): Storm structure and eyewall buoyancy. Mon. Wea. Rev., 130 , 15731592.

    • Search Google Scholar
    • Export Citation
  • Braun, S. A., and R. A. Houze Jr., 1994: The transition zone and secondary maximum of radar reflectivity behind a midlatitude squall line: Results retrieved from Doppler radar data. J. Atmos. Sci., 51 , 27332755.

    • Search Google Scholar
    • Export Citation
  • 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
  • Bryan, G. H., J. Wyngaard, and J. M. Fritsch, 2003: Resolution requirements for the simulation of deep moist convection. Mon. Wea. Rev., 131 , 23942416.

    • Search Google Scholar
    • Export Citation
  • Cangialosi, J., and S. S. Chen, 2004: A numerical study of the topographic effects on structure and rainfall in Hurricane Georges (1998). Preprints, 26th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., CD-ROM, 13D.4.

  • Davis, C., and L. F. Bosart, 2002: Numerical simulations of the genesis of Hurricane Diana (1984). Part II: Sensitivity of track and intensity prediction. Mon. Wea. Rev., 130 , 11001124.

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., and J. M. Gross, 2003: Evolution of prediction models. Hurricane! Coping with Disaster, R. Simpson, Ed., Amer. Geophys. Union, 103–126.

    • 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
  • Farley, R. D., 1987: Numerical modeling of hailstorms and hailstone growth. Part III: Simulation of an Alberta hailstorm—Natural and seeded cases. J. Appl. Meteor., 26 , 789812.

    • Search Google Scholar
    • Export Citation
  • 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
  • Fovell, R. G., and Y. Ogura, 1988: Numerical simulation of a midlatitude squall line in two dimensions. J. Atmos. Sci., 45 , 38463879.

    • 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.

  • Jorgensen, D. P., 1984: Mesoscale and convective-scale characteristics of mature hurricanes. Part II: Inner core structure of Hurricane Allen (1980). J. Atmos. Sci., 41 , 12871311.

    • Search Google Scholar
    • Export Citation
  • Jorgensen, D. P., and M. A. LeMone, 1989: Vertical velocity characteristics of oceanic convection. J. Atmos. Sci., 46 , 621640.

  • Jorgensen, D. P., E. J. Zipser, and M. A. Lemone, 1985: Vertical motions in intense hurricanes. J. Atmos. Sci., 42 , 839856.

  • Jorgensen, D. P., T. J. Matejka, D. Johnson, and M. A. LeMone, 1994: A TOGA-COARE squall line seen by multiple airborne Doppler radars. Preprints, Sixth Conf. on Mesoscale Processes, Portland, OR, Amer. Meteor. Soc., 25–28.

  • Kain, J. S., and J. M. Fritsch, 1993: Convective parameterization for mesoscale models: The Kain–Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, Meteor. Monogr., No. 46, Amer. Meteor. Soc., 165–170.

  • Karyampudi, V. M., G. S. Lai, and J. Manobianco, 1998: Impact of initial conditions, rainfall assimilation, and cumulus parameterization on simulations of Hurricane Florence (1988). Mon. Wea. Rev., 126 , 30773101.

    • Search Google Scholar
    • Export Citation
  • Lawrence, M. B., L. A. Avila, J. L. Beven, J. L. Franklin, J. L. Guiney, and R. J. Pasch, 2001: Atlantic hurricane season of 1999. Mon. Wea. Rev., 129 , 30573084.

    • Search Google Scholar
    • Export Citation
  • 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 , 10651092.

    • Search Google Scholar
    • Export Citation
  • Liu, Y., D-L. Zhang, and M. K. Yau, 1997: A multiscale numerical study of Hurricane Andrew (1992). Part I: Explicit simulation and verification. Mon. Wea. Rev., 125 , 30733093.

    • Search Google Scholar
    • Export Citation
  • Marchok, T., R. Rogers, and R. Tuleya, 2007: Validation schemes for tropical cyclone quantitative precipitation forecasts: Evaluation of operational models for U.S. landfalling cases. Wea. Forecasting, in press.

    • Search Google Scholar
    • Export Citation
  • Marks, F. D., and R. A. Houze Jr., 1987: Inner core structure of Hurricane Alicia from airborne Doppler radar observations. J. Atmos. Sci., 44 , 12961317.

    • Search Google Scholar
    • Export Citation
  • Marks, F. D., R. A. Houze Jr., and J. F. Gamache, 1992: Dual-aircraft investigation of the inner core of Hurricane Norbert. Part I: Kinematic structure. J. Atmos. Sci., 49 , 919942.

    • Search Google Scholar
    • Export Citation
  • McFarquhar, G. M., and R. A. Black, 2004: Observations of particle size and phase in tropical cyclones: Implications for mesoscale modeling of microphysical processes. J. Atmos. Sci., 61 , 422439.

    • Search Google Scholar
    • Export Citation
  • Olson, W. S., C. D. Kummerow, Y. Hong, and W-K. Tao, 1999: Atmospheric latent heating distributions in the Tropics derived from satellite passive microwave radiometer measurements. J. Appl. Meteor., 38 , 633664.

    • Search Google Scholar
    • Export Citation
  • Orville, H. D., and F. J. Kopp, 1990: A numerical simulation of the 22 July 1979 HIPLEX-1 Case. J. Appl. Meteor., 29 , 539550.

  • Orville, H. D., R. D. Farley, and J. H. Hirsch, 1984: Some surprising results from simulated seeding of stratiform-type clouds. J. Appl. Meteor., 23 , 15851600.

    • Search Google Scholar
    • Export Citation
  • Pagowski, M., and G. W. K. Moore, 2001: A numerical study of an extreme cold-air outbreak over the Labrador Sea: Sea ice, air–sea interaction, and development of polar lows. Mon. Wea. Rev., 129 , 4772.

    • Search Google Scholar
    • Export Citation
  • Pasch, R. J., L. A. Avila, and J. L. Guiney, 2001: Atlantic hurricane season of 1998. Mon. Wea. Rev., 129 , 30853123.

  • Powell, M. D., 1990a: Boundary layer structure and dynamics in outer hurricane rainbands. Part I: Mesoscale rainfall and kinematic structure. Mon. Wea. Rev., 118 , 891917.

    • Search Google Scholar
    • Export Citation
  • Powell, M. D., 1990b: Boundary layer structure and dynamics in outer hurricane rainbands. Part II: Downdraft modification and mixed layer recovery. Mon. Wea. Rev., 118 , 918938.

    • Search Google Scholar
    • Export Citation
  • Rogers, R. F., S. S. Chen, J. E. Tenerelli, and H. E. Willoughby, 2003: A numerical study of the impact of vertical shear on the distribution of rainfall in Hurricane Bonnie (1998). Mon. Wea. Rev., 131 , 15771599.

    • Search Google Scholar
    • Export Citation
  • Smagorinsky, J., S. Manabe, and J. L. Holloway Jr., 1965: Numerical results from a nine-level general circulation model of the atmosphere. Mon. Wea. Rev., 93 , 727768.

    • Search Google Scholar
    • Export Citation
  • Smith Jr., P. L., C. G. Myers, and H. D. Orville, 1975: Radar reflectivity factor calculations in numerical cloud models using bulk parameterization of precipitation. J. Appl. Meteor., 14 , 11561165.

    • 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.

  • Tao, W-K., and Coauthors, 2001: Retrieved vertical profiles of latent heat release using TRMM rainfall products for February 1998. J. Appl. Meteor., 40 , 957982.

    • Search Google Scholar
    • Export Citation
  • Tenerelli, J. E., and S. S. Chen, 2002: Intensity change and eyewall replacement in Hurricane Floyd (1999). Preprints, 25th Conf. on Hurricanes and Tropical Meteorology, San Diego, CA, Amer. Meteor. Soc., 168–169.

  • Tenerelli, J. E., and S. S. Chen, 2004: Influence of initial vortex structure on the simulation of hurricane lifecycles. Preprints, 26th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., CD-ROM, 15C.3.

  • Turpeinen, O., and M. K. Yau, 1981: Comparisons of results from a three-dimensional cloud model with statistics of radar echoes on Day 261 of GATE. Mon. Wea. Rev., 109 , 14951511.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., W. C. Skamarock, and J. B. Klemp, 1997: The resolution dependence of explicitly modeled convective systems. Mon. Wea. Rev., 125 , 527548.

    • Search Google Scholar
    • Export Citation
  • Willis, P. T., and D. P. Jorgensen, 1981: Reflectivity relationships for hurricanes. Preprints, 20th Conf. on Radar Meteorology, Boston, MA, Amer. Meteor. Soc., 85–90.

  • Willoughby, H. E., 1995: Mature structure and evolution. Global Perspectives on Tropical Cyclones, WMO Tech. Doc. 693, R. L. Elsberry, Ed., WMO, 21–62.

    • Search Google Scholar
    • Export Citation
  • Yuter, S. E., and R. A. Houze Jr., 1995: Three-dimensional kinematic and microphysical evolution of Florida cumulonimbus. Part III: Vertical mass transport, mass divergence, and synthesis. Mon. Wea. Rev., 123 , 19641983.

    • Search Google Scholar
    • Export Citation
  • Zhang, D-L., and R. A. Anthes, 1982: A high-resolution model of the planetary boundary layer–sensitivity tests and comparisons with SESAME-79 data. J. Appl. Meteor., 21 , 15941609.

    • Search Google Scholar
    • Export Citation
  • Zhang, D-L., Y. Liu, and M. K. Yau, 2000: A multiscale numerical study of Hurricane Andrew (1992). Part III: Dynamically induced vertical motion. Mon. Wea. Rev., 128 , 37723788.

    • Search Google Scholar
    • Export Citation
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