• Andreae, M. O., D. Rosenfeld, P. Artaxo, A. A. Costa, G. P. Frank, K. M. Longo, and M. A. F. Silva-Dias, 2004: Smoking rain clouds over the Amazon. Science, 303, 13371342, doi:10.1126/science.1092779.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Avila, L. A., and J. Cangialosi, 2011: Tropical cyclone report, Hurricane Irene. National Hurricane Center, National Weather Service, 45 pp. [Available online at http://www.nhc.noaa.gov/data/tcr/AL092011_Irene.pdf.]

  • Balakrishnan, N., and D. S. Zrnić, 1990: Use of polarization to characterize precipitation and discriminate large hail. J. Atmos. Sci., 47, 15251540, doi:10.1175/1520-0469(1990)047<1525:UOPTCP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berg, R., 2015: Tropical cyclone report, Hurricane Arthur. National Hurricane Center, National Weather Service, 43 pp. [Available online at http://www.nhc.noaa.gov/data/tcr/AL012014_Arthur.pdf.]

  • 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, doi:10.1175/1520-0469(1996)053<1887:VMCOTC>2.0.CO;2.

    • Crossref
    • 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, doi:10.1175/1520-0450(1990)029<0955:RRIWCR>2.0.CO;2.

    • Crossref
    • 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, doi:10.1175/1520-0469(1986)043<0802:OOTDOI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Black, R. A., and J. Hallett, 1999: Electrification of the hurricane. J. Atmos. Sci., 56, 20042028, doi:10.1175/1520-0469(1999)056<2004:EOTH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Black, R. A., H. B. Bluestein, and M. L. Black, 1994: Unusually strong vertical motions in a Caribbean hurricane. Mon. Wea. Rev., 122, 27222739, doi:10.1175/1520-0493(1994)122<2722:USVMIA>2.0.CO;2.

    • Crossref
    • 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:10.1029/2003GL017864.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bluestein, H. B., M. M. French, R. L. Tanamachi, S. Frasier, K. Hardwick, F. Junyent, and A. L. Pazmany, 2007: Close-range observations of tornadoes in supercells made with a dual-polarization, X-band, mobile Doppler radar. Mon. Wea. Rev., 135, 15221543, doi:10.1175/MWR3349.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bringi, V. N., and V. Chandrasekar, 2001: Polarimetric Doppler Weather Radar: Principles and Applications. Cambridge University Press, 636 pp.

    • Crossref
    • Export Citation
  • Brown, B. R., M. M. Bell, and A. J. Frambach, 2016: Validation of simulated hurricane drop size distributions using polarimetric radar. Geophys. Res. Lett., 43, 910917, doi:10.1002/2015GL067278.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chan, K. T. F., and J. C. L. Chan, 2016: Sensitivity of the simulation of tropical cyclone size to microphysics schemes. Adv. Atmos. Sci., 33, 10241035, doi:10.1007/s00376-016-5183-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cione, J. G., E. A. Kalina, J. A. Zhang, and E. W. Uhlhorn, 2013: Observations of air–sea interaction and intensity change in hurricanes. Mon. Wea. Rev., 141, 23682382, doi:10.1175/MWR-D-12-00070.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Crum, T. D., and R. L. Alberty, 1993: The WSR-88D and the WSR-88D Operational Support Facility. Bull. Amer. Meteor. Soc., 74, 16691687, doi:10.1175/1520-0477(1993)074<1669:TWATWO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Didlake, A. C., Jr., and R. A. Houze Jr., 2009: Convective-scale downdrafts in the principal rainband of Hurricane Katrina (2005). Mon. Wea. Rev., 137, 32693293, doi:10.1175/2009MWR2827.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fovell, R. G., and H. Su, 2007: Impact of cloud microphysics on hurricane track forecasts. Geophys. Res. Lett., 34, L24810, doi:10.1029/2007GL031723.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fovell, R. G., K. L. Corbosiero, and H.-C. Kuo, 2009: Cloud microphysics impact on hurricane track as revealed in idealized experiments. J. Atmos. Sci., 66, 17641778, doi:10.1175/2008JAS2874.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fovell, R. G., Y. P. Bu, K. L. Corbosiero, W.-W. Tung, Y. Cao, H.-C. Kuo, L.-H. Hsu, and H. Su, 2016: Influence of cloud microphysics and radiation on tropical cyclone structure and motion. Multiscale Convection-Coupled Systems in the Tropics: A Tribute to Dr. Michio Yanai, Meteor. Monogr., No. 56, Amer. Meteor. Soc., doi:10.1175/AMSMONOGRAPHS-D-15-0006.1.

    • Crossref
    • Export Citation
  • Frame, J., P. Markowski, Y. Richardson, J. Straka, and J. Wurman, 2009: Polarimetric and dual-Doppler radar observations of the Lipscomb County, Texas, supercell thunderstorm on 23 May 2002. Mon. Wea. Rev., 137, 544561, doi:10.1175/2008MWR2425.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Friedrich, K., E. A. Kalina, J. Aikins, D. Gochis, and R. Rasmussen, 2016a: Precipitation and cloud structures of intense rain during the 2013 Great Colorado Flood. J. Hydrometeor., 17, 2752, doi:10.1175/JHM-D-14-0157.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Friedrich, K., E. A. Kalina, J. Aikins, M. Steiner, D. Gochis, P. A. Kucera, K. Ikeda, and J. Sun, 2016b: Raindrop size distribution and rain characteristics during the 2013 Great Colorado Flood. J. Hydrometeor., 17, 5372, doi:10.1175/JHM-D-14-0184.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffin, E. M., T. J. Schuur, D. R. MacGorman, M. R. Kumjian, and A. O. Fierro, 2014: An electrical and polarimetric analysis of the overland reintensification of Tropical Storm Erin (2007). Mon. Wea. Rev., 142, 23212344, doi:10.1175/MWR-D-13-00360.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Herzegh, P. H., and A. R. Jameson, 1992: Observing precipitation through dual-polarization radar measurements. Bull. Amer. Meteor. Soc., 73, 13651374, doi:10.1175/1520-0477(1992)073<1365:OPTDPR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., 1972: Ice crystal terminal velocities. J. Atmos. Sci., 29, 13481357, doi:10.1175/1520-0469(1972)029<1348:ICTV>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., S. Lewis, S. L. Durden, and T. P. Bui, 2006: Ice microphysics observations in Hurricane Humberto: Comparison with non-hurricane generated ice cloud layers. J. Atmos. Sci., 63, 288308, doi:10.1175/JAS3603.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., M. P. Mittermaier, and A. J. Illingworth, 2006: The retrievals of ice water content from radar reflectivity factor and temperature and its use in evaluating a mesoscale model. J. Appl. Meteor. Climatol., 45, 301317, doi:10.1175/JAM2340.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houze, R. A., F. D. Marks Jr., and R. A. Black, 1992: Dual-aircraft investigation of the inner core of Hurricane Norbert. Part II: Mesoscale distribution of ice particles. J. Atmos. Sci., 49, 943963, doi:10.1175/1520-0469(1992)049<0943:DAIOTI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hubbert, J. C., S. M. Ellis, W.-Y. Chang, S. Rutledge, and M. Dixon, 2014a: Modeling and interpretation of S-band ice crystal depolarization signatures from data obtained by simultaneously transmitting horizontally and vertically polarized. J. Appl. Meteor. Climatol., 53, 16591677, doi:10.1175/JAMC-D-13-0158.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hubbert, J. C., S. M. Ellis, W.-Y. Chang, and Y.-C. Liou, 2014b: X-band polarimetric observations of cross coupling in the ice phase of convective storms in Taiwan. J. Appl. Meteor. Climatol., 53, 16781695, doi:10.1175/JAMC-D-13-0360.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Islam, T., P. K. Srivastava, M. A. Rico-Ramirez, Q. Dai, M. Gupta, and S. K. Singh, 2015: Tracking a tropical cyclone through WRF–ARW simulation and sensitivity of model physics. Nat. Hazards, 76, 14731495, doi:10.1007/s11069-014-1494-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Iwabuchi, H., P. Yang, K. N. Liou, and P. Minnis, 2012: Physical and optical properties of persistent contrails: Climatology and interpretation. J. Geophys. Res., 117, D06215, doi:10.1029/2011JD017020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalina, E. A., K. Friedrich, S. M. Ellis, and D. W. Burgess, 2014: Comparison of disdrometer and X-band mobile radar observations in convective precipitation. Mon. Wea. Rev., 142, 24142435, doi:10.1175/MWR-D-14-00039.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalina, E. A., K. Friedrich, B. C. Motta, W. Deierling, G. T. Stano, and N. N. Rydell, 2016: Colorado plowable hailstorms: Synoptic weather, radar, and lightning characteristics. Wea. Forecasting, 31, 663693, doi:10.1175/WAF-D-15-0037.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumjian, M. R., 2013: Principles and applications of dual-polarization weather radar. Part III: Artifacts. J. Oper. Meteor., 1, 265274, doi:10.15191/nwajom.2013.0121.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumjian, M. R., and A. V. Ryzhkov, 2008: Polarimetric signatures in supercell thunderstorms. J. Appl. Meteor. Climatol., 47, 19401961, doi:10.1175/2007JAMC1874.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumjian, M. R., and W. Deierling, 2015: Analysis of thundersnow storms over northern Colorado. Wea. Forecasting, 30, 14691490, doi:10.1175/WAF-D-15-0007.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, C.-L., and A. J. Illingworth, 2000: Toward more accurate retrievals of ice water content from radar measurement of clouds. J. Appl. Meteor., 39, 11301146, doi:10.1175/1520-0450(2000)039<1130:TMAROI>2.0.CO;2.

    • Crossref
    • 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, doi:10.1029/JC079i015p02185.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lord, S. J., H. E. Willoughby, and J. M. Piotrowicz, 1984: Role of a parameterized ice-phase microphysics in an axisymmetric, nonhydrostatic tropical cyclone model. J. Atmos. Sci., 41, 28362848, doi:10.1175/1520-0469(1984)041<2836:ROAPIP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marks, F. D., Jr., and R. A. Houze Jr., 1987: Inner core structure of Hurricane Alicia from airborne Doppler radar observations. J. Atmos. Sci., 44, 12961317, doi:10.1175/1520-0469(1987)044<1296:ICSOHA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., 2011: CloudSat measurements of landfalling Hurricanes Gustav and Ike (2008). J. Geophys. Res., 116, D01203, doi:10.1029/2010JD014506.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., 2015: The use of CloudSat data to evaluate retrievals of total ice content in precipitating cloud systems from ground-based operational radar measurements. J. Appl. Meteor. Climatol., 54, 16631674, doi:10.1175/JAMC-D-15-0032.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., R. Cifelli, P. J. Neiman, and A. B. White, 2016: Radar rain-rate estimators and their variability due to rainfall type: An assessment based on hydrometeorology testbed data from the southeastern United States. J. Appl. Meteor. Climatol., 55, 13451358, doi:10.1175/JAMC-D-15-0284.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • May, P. T., J. D. Kepert, and T. D. Keenan, 2008: Polarimetric radar observations of the persistently asymmetric structure of tropical cyclone Ingrid. Mon. Wea. Rev., 136, 616630, doi:10.1175/2007MWR2077.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McFarquhar, G. M., H. Zhang, G. Heymsfield, R. Hood, J. Dudhia, J. B. Halverson, and F. Marks, 2006: Factors affecting the evolution of Hurricane Erin (2001) and the distributions of hydrometeors: Role of microphysical processes. J. Atmos. Sci., 63, 127150, doi:10.1175/JAS3590.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Melnikov, V. M., D. S. Zrnić, R. J. Doviak, P. B. Chilson, D. B. Mechem, and Y. L. Kogan, 2011: Prospects of the WSR-88D radar for cloud studies. J. Appl. Meteor. Climatol., 50, 859872, doi:10.1175/2010JAMC2303.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Melnikov, V. M., D. S. Zrnić, D. W. Burgess, and E. R. Mansell, 2015: Vertical extent of thunderstorm inflows revealed by polarimetric radar. J. Atmos. Oceanic Technol., 32, 18601865, doi:10.1175/JTECH-D-15-0096.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nousiainen, T., and G. McFarquhar, 2004: Light scattering by quasi-spherical ice crystals. J. Atmos. Sci., 61, 22292248, doi:10.1175/1520-0469(2004)061<2229:LSBQIC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • OFCM, 2016: WSR-88D meteorological observations. Part A: System concepts, responsibilities, and procedures. Federal Meteorological Handbook 11, FCM-H11A-2016, Office of the Federal Coordinator for Meteorological Services and Supporting Research, 21 pp. [Available online at http://www.ofcm.gov/publications/fmh/FMH11/2016FMH11PTA.pdf.]

  • Palmer, R. D., and Coauthors, 2011: Observations of the 10 May 2010 tornado outbreak using OU-PRIME: Potential for new science with high-resolution polarimetric radar. Bull. Amer. Meteor. Soc., 92, 871891, doi:10.1175/2011BAMS3125.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Park, H., A. V. Ryzhkov, D. S. Zrnić, and K. Kim, 2009: The hydrometeor classification algorithm for the polarimetric WSR-88D: Description and application to an MCS. Wea. Forecasting, 24, 730748, doi:10.1175/2008WAF2222205.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Protat, A., and C. R. Williams, 2011: The accuracy of radar estimates of ice terminal fall speed from vertically pointing Doppler radar measurements. J. Appl. Meteor. Climatol., 50, 21202138, doi:10.1175/JAMC-D-10-05031.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Romine, G. S., D. W. Burgess, and R. B. Wilhelmson, 2008: A dual-polarization-radar-based assessment of the 8 May 2003 Oklahoma City area tornadic supercell. Mon. Wea. Rev., 136, 28492870, doi:10.1175/2008MWR2330.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rosenfeld, D., 1999: TRMM observed first direct evidence of smoke from forest fires inhibiting rainfall. Geophys. Res. Lett., 26, 31053108, doi:10.1029/1999GL006066.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rosenfeld, D., W. L. Woodley, A. Khain, W. R. Cotton, G. Carrió, I. Ginis, and J. H. Golden, 2012: Aerosol effects on microstructure and intensity of tropical cyclones. Bull. Amer. Meteor. Soc., 93, 9871001, doi:10.1175/BAMS-D-11-00147.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., 2007: The impact of beam broadening on the quality of radar polarimetric data. J. Atmos. Oceanic Technol., 24, 729744, doi:10.1175/JTECH2003.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., D. S. Zrnić, and B. A. Gordon, 1998: Polarimetric method for ice water content determination. J. Appl. Meteor., 37, 125134, doi:10.1175/1520-0450(1998)037<0125:PMFIWC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Snyder, J. C., H. B. Bluestein, G. Zhang, and S. J. Frasier, 2010: Attenuation correction and hydrometeor classification of high-resolution, X-band, dual-polarized mobile radar measurements in severe convective storms. J. Atmos. Oceanic Technol., 27, 19792001, doi:10.1175/2010JTECHA1356.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Steiner, M., R. A. Houze, and S. E. Yuter, 1995: Climatological characterization of three-dimensional storm structure from operational radar and rain gauge data. J. Appl. Meteor., 34, 19782007, doi:10.1175/1520-0450(1995)034<1978:CCOTDS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tanamachi, R. L., and P. L. Heinselman, 2016: Rapid-scan, polarimetric observations of central Oklahoma severe storms on 31 May 2013. Wea. Forecasting, 31, 1942, doi:10.1175/WAF-D-15-0111.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Van Den Broeke, M. S., 2013: Polarimetric radar observations of biological scatters in Hurricanes Irene (2011) and Sandy (2012). J. Atmos. Oceanic Technol., 30, 27542767, doi:10.1175/JTECH-D-13-00056.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vivekanandan, J., S. M. Ellis, R. Oye, D. S. Zrnić, A. V. Ryzhkov, and J. Straka, 1999: Cloud microphysics retrieval using S-band dual-polarization radar measurements. Bull. Amer. Meteor. Soc., 80, 381388, doi:10.1175/1520-0477(1999)080<0381:CMRUSB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • White, A. B., J. R. Jordan, B. E. Martner, F. M. Ralph, and B. W. Bartram, 2000: Extending the dynamic range of an S-band radar for cloud and precipitation studies. J. Atmos. Oceanic Technol., 17, 12261234, doi:10.1175/1520-0426(2000)017<1226:ETDROA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wurman, J., D. Dowell, Y. Richardson, P. Markowski, E. Rasmussen, D. Burgess, L. Wicker, and H. Bluestein, 2012: The second Verification of the Origins of Rotation in Tornadoes Experiment: VORTEX2. Bull. Amer. Meteor. Soc., 93, 11471170, doi:10.1175/BAMS-D-11-00010.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yuter, S. E., and R. A. Houze Jr., 1997: Measurements of raindrop size distributions over the Pacific warm pool and implications for ZR relations. J. Appl. Meteor., 36, 847867, doi:10.1175/1520-0450(1997)036<0847:MORSDO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zrnić, D. S., and A. V. Ryzhkov, 1999: Polarimetry for weather surveillance radars. Bull. Amer. Meteor. Soc., 80, 389406, doi:10.1175/1520-0477(1999)080<0389:PFWSR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zrnić, D. S., A. V. Ryzhkov, J. Straka, Y. Liu, and J. Vivekanandan, 2001: Testing a procedure for automatic classification of hydrometeor types. J. Atmos. Oceanic Technol., 18, 892913, doi:10.1175/1520-0426(2001)018<0892:TAPFAC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
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The Ice Water Paths of Small and Large Ice Species in Hurricanes Arthur (2014) and Irene (2011)

Evan A. Kalina NOAA/Atlantic Oceanographic and Meteorological Laboratory Hurricane Research Division, Miami, Florida
NOAA/Earth System Research Laboratory Physical Sciences Division, Boulder, Colorado

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Sergey Y. Matrosov Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado
NOAA/Earth System Research Laboratory Physical Sciences Division, Boulder, Colorado

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Joseph J. Cione NOAA/Atlantic Oceanographic and Meteorological Laboratory Hurricane Research Division, Miami, Florida
NOAA/Earth System Research Laboratory Physical Sciences Division, Boulder, Colorado

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Frank D. Marks NOAA/Atlantic Oceanographic and Meteorological Laboratory Hurricane Research Division, Miami, Florida

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Jothiram Vivekanandan Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Robert A. Black NOAA/Atlantic Oceanographic and Meteorological Laboratory Hurricane Research Division, Miami, Florida

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John C. Hubbert Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Michael M. Bell Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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David E. Kingsmill Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado

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Allen B. White NOAA/Earth System Research Laboratory Physical Sciences Division, Boulder, Colorado

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Abstract

Dual-polarization scanning radar measurements, air temperature soundings, and a polarimetric radar-based particle identification scheme are used to generate maps and probability density functions (PDFs) of the ice water path (IWP) in Hurricanes Arthur (2014) and Irene (2011) at landfall. The IWP is separated into the contribution from small ice (i.e., ice crystals), termed small-particle IWP, and large ice (i.e., graupel and snow), termed large-particle IWP. Vertically profiling radar data from Hurricane Arthur suggest that the small ice particles detected by the scanning radar have fall velocities mostly greater than 0.25 m s−1 and that the particle identification scheme is capable of distinguishing between small and large ice particles in a mean sense. The IWP maps and PDFs reveal that the total and large-particle IWPs range up to 10 kg m−2, with the largest values confined to intense convective precipitation within the rainbands and eyewall. Small-particle IWP remains mostly <4 kg m−2, with the largest small-particle IWP values collocated with maxima in the total IWP. PDFs of the small-to-total IWP ratio have shapes that depend on the precipitation type (i.e., intense convective, stratiform, or weak-echo precipitation). The IWP ratio distribution is narrowest (broadest) in intense convective (weak echo) precipitation and peaks at a ratio of about 0.1 (0.3).

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Current affiliations: Cooperative Institute for Research in Environmental Sciences, University of Colorado, and NOAA/Earth System Research Laboratory Global Systems Division, and Developmental Testbed Center, Boulder, Colorado.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Evan A. Kalina, evan.kalina@noaa.gov

Abstract

Dual-polarization scanning radar measurements, air temperature soundings, and a polarimetric radar-based particle identification scheme are used to generate maps and probability density functions (PDFs) of the ice water path (IWP) in Hurricanes Arthur (2014) and Irene (2011) at landfall. The IWP is separated into the contribution from small ice (i.e., ice crystals), termed small-particle IWP, and large ice (i.e., graupel and snow), termed large-particle IWP. Vertically profiling radar data from Hurricane Arthur suggest that the small ice particles detected by the scanning radar have fall velocities mostly greater than 0.25 m s−1 and that the particle identification scheme is capable of distinguishing between small and large ice particles in a mean sense. The IWP maps and PDFs reveal that the total and large-particle IWPs range up to 10 kg m−2, with the largest values confined to intense convective precipitation within the rainbands and eyewall. Small-particle IWP remains mostly <4 kg m−2, with the largest small-particle IWP values collocated with maxima in the total IWP. PDFs of the small-to-total IWP ratio have shapes that depend on the precipitation type (i.e., intense convective, stratiform, or weak-echo precipitation). The IWP ratio distribution is narrowest (broadest) in intense convective (weak echo) precipitation and peaks at a ratio of about 0.1 (0.3).

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Current affiliations: Cooperative Institute for Research in Environmental Sciences, University of Colorado, and NOAA/Earth System Research Laboratory Global Systems Division, and Developmental Testbed Center, Boulder, Colorado.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Evan A. Kalina, evan.kalina@noaa.gov
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