Editorial Type:
Article
Article Type:
Research Article

Comparison of Disdrometer and X-Band Mobile Radar Observations in Convective Precipitation

Evan A. Kalina Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado

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Katja Friedrich Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado

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Scott M. Ellis National Center for Atmospheric Research, Boulder, Colorado

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Donald W. Burgess Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and National Severe Storms Laboratory, Norman, Oklahoma

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Print Publication:
01 Jul 2014
DOI:
https://doi.org/10.1175/MWR-D-14-00039.1
Page(s):
2414–2435
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Abstract

Microphysical data from thunderstorms are sparse, yet they are essential to validate microphysical schemes in numerical models. Mobile, dual-polarization, X-band radars are capable of providing a wealth of data that include radar reflectivity, drop shape, and hydrometeor type. However, X-band radars suffer from beam attenuation in heavy rainfall and hail, which can be partially corrected with attenuation correction schemes. In this research, the authors compare surface disdrometer observations to results from a differential phase-based attenuation correction scheme. This scheme is applied to data recorded by the National Oceanic and Atmospheric Administration (NOAA) X-band dual-polarized (NOXP) mobile radar, which was deployed during the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2). Results are presented from five supercell thunderstorms and one squall line (183 min of data). The median disagreement (radar–disdrometer) in attenuation-corrected reflectivity Z and differential reflectivity ZDR is just 1.0 and 0.19 dB, respectively. However, two data subsets reveal much larger discrepancies in Z (ZDR): 5.8 (1.6) dB in a hailstorm and −13 (−0.61) dB when the radar signal quality index (SQI) is less than 0.8. The discrepancies are much smaller when disdrometer and S-band Weather Surveillance Radar-1988 Doppler (WSR-88D) Z are compared, with differences of −1.5 dB (hailstorm) and −0.66 dB (NOXP SQI < 0.8). A comparison of the hydrometeor type retrieved from disdrometer and NOXP radar data is also presented, in which the same class is assigned 63% of the time.

Corresponding author address: Evan A. Kalina, Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, UCB 311, Boulder, CO 80309. E-mail: evan.kalina@colorado.edu

Abstract

Microphysical data from thunderstorms are sparse, yet they are essential to validate microphysical schemes in numerical models. Mobile, dual-polarization, X-band radars are capable of providing a wealth of data that include radar reflectivity, drop shape, and hydrometeor type. However, X-band radars suffer from beam attenuation in heavy rainfall and hail, which can be partially corrected with attenuation correction schemes. In this research, the authors compare surface disdrometer observations to results from a differential phase-based attenuation correction scheme. This scheme is applied to data recorded by the National Oceanic and Atmospheric Administration (NOAA) X-band dual-polarized (NOXP) mobile radar, which was deployed during the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2). Results are presented from five supercell thunderstorms and one squall line (183 min of data). The median disagreement (radar–disdrometer) in attenuation-corrected reflectivity Z and differential reflectivity ZDR is just 1.0 and 0.19 dB, respectively. However, two data subsets reveal much larger discrepancies in Z (ZDR): 5.8 (1.6) dB in a hailstorm and −13 (−0.61) dB when the radar signal quality index (SQI) is less than 0.8. The discrepancies are much smaller when disdrometer and S-band Weather Surveillance Radar-1988 Doppler (WSR-88D) Z are compared, with differences of −1.5 dB (hailstorm) and −0.66 dB (NOXP SQI < 0.8). A comparison of the hydrometeor type retrieved from disdrometer and NOXP radar data is also presented, in which the same class is assigned 63% of the time.

Corresponding author address: Evan A. Kalina, Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, UCB 311, Boulder, CO 80309. E-mail: evan.kalina@colorado.edu
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  • Anagnostou, M. N., E. N. Anagnostou, and J. Vivekanandan, 2006: Correction for rain path specific and differential attenuation of X-band dual-polarization observations. IEEE Geosci. Remote Sens., 44, 2470–2480, doi:10.1109/TGRS.2006.873204.

    • Search Google Scholar
    • Export Citation

  • Atlas, D., R. C. Srivastava, and R. S. Sekhon, 1973: Doppler radar characteristics of precipitation at vertical incidence. Rev. Geophys. Space Phys., 11, 1–35, doi:10.1029/RG011i001p00001.

    • Search Google Scholar
    • Export Citation

  • Aydin, K., S. H. Park, and T. M. Walsh, 1998: Bistatic dual-polarization scattering from rain and hail at S- and C-band frequencies. J. Atmos. Oceanic Technol., 15, 1110–1121, doi:10.1175/1520-0426(1998)015<1110:BDPSFR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Balakrishnan, N., and D. S. Zrnić, 1990: Use of polarization to characterize precipitation and discriminate large hail. J. Atmos. Sci., 47, 1525–1540, doi:10.1175/1520-0469(1990)047<1525:UOPTCP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Barthazy, E., S. Göke, R. Schefold, and D. Högl, 2004: An optical array instrument for shape and fall velocity measurements of hydrometeors. J. Atmos. Oceanic Technol., 21, 1400–1416, doi:10.1175/1520-0426(2004)021<1400:AOAIFS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Beard, K. V., and C. H. Chuang, 1987: A new model for the equilibrium shape of raindrops. J. Atmos. Sci., 44, 1509–1524, doi:10.1175/1520-0469(1987)044<1509:ANMFTE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Borowska, L., A. Ryzhkov, D. Zrnić, C. Simmer, and R. Palmer, 2011: Attenuation and differential attenuation of 5-cm-wavelength radiation in melting hail. J. Appl. Meteor. Climatol., 50, 59–76, doi:10.1175/2010JAMC2465.1.

    • Search Google Scholar
    • Export Citation

  • Bringi, V. N., and V. Chandrasekar, 2001: Polarimetric Doppler Weather Radar: Principles and Applications. Cambridge University Press, 662 pp.

    • Search Google Scholar
    • Export Citation

  • Bringi, V. N., T. D. Keenan, and V. Chandrasekar, 2001: Correcting C-band radar reflectivity and differential reflectivity data for rain attenuation: A self-consistent method with constraints. IEEE Trans. Geosci. Remote Sens., 39, 1906–1915, doi:10.1109/36.951081.

    • Search Google Scholar
    • Export Citation

  • Bringi, V. N., V. Chandrasekar, J. Hubbert, E. Gorgucci, W. L. Randeu, and M. Schoenhuber, 2003: Raindrop size distribution in different climatic regimes from disdrometer and dual-polarized radar analysis. J. Atmos. Sci., 60, 354–365, doi:10.1175/1520-0469(2003)060<0354:RSDIDC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Burgess, D. W., E. R. Mansell, C. M. Schwarz, and B. J. Allen, 2010: Tornado and tornadogenesis events seen by the NOXP X-band, dual-polarization radar during VORTEX2 2010. Preprints, 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., 5.2. [Available online at http://ams.confex.com/ams/25SLS/techprogram/paper_176164.htm.]

  • Carey, L. D., S. A. Rutledge, D. A. Ahijevych, and T. D. Keenan, 2000: Correcting propagation effects in C-band polarimetric radar observations of tropical convection using differential propagation phase. J. Appl. Meteor., 39, 1405–1433, doi:10.1175/1520-0450(2000)039<1405:CPEICB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Dolan, B., and S. A. Rutledge, 2009: A theory-based hydrometeor identification algorithm for X-band polarimetric radars. J. Oceanic Atmos. Technol., 26, 2071–2088, doi:10.1175/2009JTECHA1208.1.

    • Search Google Scholar
    • Export Citation

  • Friedrich, K., S. A. Higgins, F. J. Masters, and C. R. Lopez, 2013a: Articulating and stationary PARSIVEL disdrometer measurements in conditions with strong winds and heavy rainfall. J. Atmos. Oceanic Technol., 30, 2063–2080, doi:10.1175/JTECH-D-12-00254.1.

    • Search Google Scholar
    • Export Citation

  • Friedrich, K., E. A. Kalina, F. J. Masters, and C. R. Lopez, 2013b: Drop-size distributions in thunderstorms measured by optical disdrometers during VORTEX2. Mon. Wea. Rev., 141, 1182–1203, doi:10.1175/MWR-D-12-00116.1.

    • Search Google Scholar
    • Export Citation

  • Geotis, S. G., 1978: Comparison of reflectivity measurements by radar and by disdrometer. J. Appl. Meteor., 17, 1403–1405, doi:10.1175/1520-0450(1978)017<1403:CORMBR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Goddard, J. W. F., S. M. Cherry, and V. N. Bringi, 1982: Comparison of dual-polarization radar measurements of rain with ground-based disdrometer measurements. J. Appl. Meteor., 21, 252–256, doi:10.1175/1520-0450(1982)021<0252:CODPRM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Gorgucci, E., V. Chandrasekar, and L. Baldini, 2006: Correction of X-band radar observation for propagation effects based on the self-consistency principle. J. Atmos. Oceanic Technol., 23, 1668–1681, doi:10.1175/JTECH1950.1.

    • Search Google Scholar
    • Export Citation

  • Grzych, M. L., B. D. Lee, and C. A. Finley, 2007: Thermodynamic analysis of supercell rear-flank downdrafts from Project ANSWERS. Mon. Wea. Rev., 135, 240–246, doi:10.1175/MWR3288.1.

    • Search Google Scholar
    • Export Citation

  • Gu, J.-Y., A. Ryzhkov, P. Zhang, P. Neilley, M. Knight, B. Wolf, and D.-I. Lee, 2011: Polarimetric attenuation correction in heavy rain at C band. J. Appl. Meteor. Climatol., 50, 39–58, doi:10.1175/2010JAMC2258.1.

    • Search Google Scholar
    • Export Citation

  • Gunn, R., and G. D. Kinzer, 1949: The terminal velocity of fall for water droplets in stagnant air. J. Meteor., 6, 243–248, doi:10.1175/1520-0469(1949)006<0243:TTVOFF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Huang, G. J., V. N. Bringi, S. van den Heever, and W. Cotton, 2005: Polarimetric radar signatures from RAMS microphysics. Preprints, 32nd Int. Conf. on Radar Meteorology, Albuquerque, NM, Amer. Meteor. Soc., P11R.6. [Available online at http://ams.confex.com/ams/pdfpapers/96261.pdf.]

  • Huang, G. J., V. N. Bringi, and M. Thurai, 2008: Orientation angle distributions after an 80-m fall using a 2D video disdrometer. J. Atmos. Oceanic Technol., 25, 1717–1723, doi:10.1175/2008JTECHA1075.1.

    • Search Google Scholar
    • Export Citation

  • Huang, G. J., V. N. Bringi, R. Cifelli, D. Hudak, and W. A. Petersen, 2010: A methodology to derive radar reflectivity–liquid equivalent snow rate relations using C-band radar and a 2D video disdrometer. J. Atmos. Oceanic Technol., 27, 637–651, doi:10.1175/2009JTECHA1284.1.

    • Search Google Scholar
    • Export Citation

  • Hubbert, J., and V. N. Bringi, 1995: An iterative filtering technique for the analysis of coplanar differential phase and dual-frequency radar measurements. J. Atmos. Oceanic Technol., 12, 643–648, doi:10.1175/1520-0426(1995)012<0643:AIFTFT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Hubbert, J., S. M. Ellis, M. Dixon, and G. Meymaris, 2010a: Modeling, error analysis, and evaluation of dual-polarization variables obtained from simultaneous horizontal and vertical polarization transmit radar. Part I: Modeling and antenna errors. J. Atmos. Oceanic Technol., 27, 1583–1598, doi:10.1175/2010JTECHA1336.1.

    • Search Google Scholar
    • Export Citation

  • Hubbert, J., S. M. Ellis, M. Dixon, and G. Meymaris, 2010b: Modeling, error analysis, and evaluation of dual-polarization variables obtained from simultaneous horizontal and vertical polarization transmit radar. Part II: Experimental data. J. Atmos. Oceanic Technol., 27, 1599–1607, doi:10.1175/2010JTECHA1337.1.

    • Search Google Scholar
    • Export Citation

  • Illingworth, A. J., and C. J. Stevens, 1987: An optical disdrometer for the measurement of raindrop size spectra in windy conditions. J. Atmos. Oceanic Technol., 4, 411–421, doi:10.1175/1520-0426(1987)004<0411:AODFTM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Iwanami, K., K. Kusunoki, N. Orikasa, M. Maki, R. Misumi, and M. Murakami, 2007: Hydrometeor type classification in winter clouds using X-band polarimetric radar measurements—Comparison of X-band polarimetric radar data with in-situ measurements by HYVIS. Preprints, 33rd Conf. on Radar Meteorology, Cairns, QLD, Australia, Amer. Meteor. Soc., P10.11. [Available online at http://ams.confex.com/ams/pdfpapers/123072.pdf.]

  • Jaffrain, J., and A. Berne, 2011: Experimental quantification of the sampling uncertainty associated with measurements from PARSIVEL disdrometers. J. Hydrometeor., 12, 352–370, doi:10.1175/2010JHM1244.1.

    • Search Google Scholar
    • Export Citation

  • Kanofsky, L., and P. B. Chilson, 2008: An analysis of errors in drop size distribution retrievals and rain bulk parameters with a UHF wind profiling radar and a two-dimensional video disdrometer. J. Atmos. Oceanic Technol., 25, 2282–2292, doi:10.1175/2008JTECHA1061.1.

    • Search Google Scholar
    • Export Citation

  • Knight, N. C., 1986: Hailstone shape factor and its relationship to radar interpretation of hail. J. Climate Appl. Meteor., 25, 1956–1958, doi:10.1175/1520-0450(1986)025<1956:HSFAIR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Knight, N. C., and A. J. Heymsfield, 1983: Measurement and interpretation of hailstone density and terminal velocity. J. Atmos. Sci., 40, 1510–1516, doi:10.1175/1520-0469(1983)040<1510:MAIOHD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kruger, A., and W. F. Krajewski, 2002: Two-dimensional video disdrometer: A description. J. Atmos. Oceanic Technol., 19, 602–617, doi:10.1175/1520-0426(2002)019<0602:TDVDAD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kwiatkowski, J. M., A. B. Kostinski, and A. R. Jameson, 1995: The use of optimal polarizations for studying the microphysics of precipitation: Nonattenuating wavelengths. J. Atmos. Oceanic Technol., 12, 96–114, doi:10.1175/1520-0426(1995)012<0096:TUOOPF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Lesins, G. B., and R. List, 1986: Sponginess and drop shedding of gyrating hailstones in a pressure-controlled icing wind tunnel. J. Atmos. Sci., 43, 2813–2825, doi:10.1175/1520-0469(1986)043<2813:SADSOG>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Liu, H., and V. Chandrasekar, 2000: Classification of hydrometeors based on polarimetric radar measurements: Development of fuzzy logic and neuro-fuzzy systems, and in situ verification. J. Atmos. Oceanic Technol., 17, 140–164, doi:10.1175/1520-0426(2000)017<0140:COHBOP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Locatelli, J. D., and P. Hobbs, 1974: Fall speed and masses of solid precipitation particles. J. Geophys. Res., 79, 2185–2197, doi:10.1029/JC079i015p02185.

    • Search Google Scholar
    • Export Citation

  • Löffler-Mang, M., and J. Joss, 2000: An optical disdrometer for measuring size and velocity of hydrometeors. J. Atmos. Oceanic Technol., 17, 130–139, doi:10.1175/1520-0426(2000)017<0130:AODFMS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Löffler-Mang, M., and U. Blahak, 2001: Estimation of the equivalent radar reflectivity factor from measured snow size spectra. J. Appl. Meteor., 40, 843–849, doi:10.1175/1520-0450(2001)040<0843:EOTERR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Markowski, P. M., J. M. Straka, and E. N. Rasmussen, 2002: Direct surface thermodynamic observations within the rear-flank downdrafts of nontornadic and tornadic supercells. Mon. Wea. Rev., 130, 1692–1721, doi:10.1175/1520-0493(2002)130<1692:DSTOWT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Neŝpor, V., W. F. Krajewski, and A. Kruger, 2000: Wind-induced error of raindrop size distribution measurement using a two-dimensional video disdrometer. J. Atmos. Oceanic Technol., 17, 1483–1492, doi:10.1175/1520-0426(2000)017<1483:WIEORS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Palmer, R., and Coauthors, 2009: Weather radar education at the University of Oklahoma—An integrated interdisciplinary approach. Bull. Amer. Meteor. Soc., 90, 1277–1282, doi:10.1175/2009BAMS2738.1.

    • 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, 730–748, doi:10.1175/2008WAF2222205.1.

    • Search Google Scholar
    • Export Citation

  • Park, S. G., V. N. Bringi, V. Chandrasekar, M. Maki, and K. Iwanami, 2005: Correction of radar reflectivity and differential reflectivity for rain attenuation at X band. Part I: Theoretical and empirical basis. J. Atmos. Oceanic Technol., 22, 1621–1632, doi:10.1175/JTECH1803.1.

    • Search Google Scholar
    • Export Citation

  • Rasmussen, R. M., and A. J. Heymsfield, 1987: Melting and shedding of graupel and hail. Part I: Model physics. J. Atmos. Sci., 44, 2754–2763, doi:10.1175/1520-0469(1987)044<2754:MASOGA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Rinehart, R. E., 2004: Radar for Meteorologists. Rinehart Publications, 482 pp.

  • Ryzhkov, A. V., and D. S. Zrnić, 2007: Depolarization in ice crystals and its effect on radar polarimetric measurements. J. Atmos. Oceanic Technol., 24, 1256–1267, doi:10.1175/JTECH2034.1.

    • Search Google Scholar
    • Export Citation

  • Ryzhkov, A. V., M. Pinsky, A. Pokrovsky, and A. Khain, 2011: Polarimetric radar observation operator for a cloud model with spectral microphysics. J. Appl. Meteor. Climatol., 50, 873–894, doi:10.1175/2010JAMC2363.1.

    • Search Google Scholar
    • Export Citation

  • Ryzhkov, A. V., M. R. Kumjian, S. M. Ganson, and A. P. Khain, 2013a: Polarimetric radar characteristics of melting hail. Part I: Theoretical simulations using spectral microphysical modeling. J. Appl. Meteor. Climatol., 52, 2849–2870, doi:10.1175/JAMC-D-13-073.1.

    • Search Google Scholar
    • Export Citation

  • Ryzhkov, A. V., M. R. Kumjian, S. M. Ganson, and P. Zhang, 2013b: Polarimetric radar characteristics of melting hail. Part II: Practical implications. J. Appl. Meteor. Climatol., 52, 2871–2886, doi:10.1175/JAMC-D-13-074.1.

    • Search Google Scholar
    • Export Citation

  • Schuur, T. J., A. V. Ryzhkov, D. S. Zrnić, and M. Schönhuber, 2001: Drop size distributions measured by a 2D video disdrometer: Comparison with dual-polarization radar data. J. Appl. Meteor., 40, 1019–1034, doi:10.1175/1520-0450(2001)040<1019:DSDMBA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Sevruk, B., 1982: Methods of correction for systematic error in point precipitation measurement for operational use. Operational Hydrology Rep. 21, Publ. 589, 91 pp. [Available from WMO, Case Postale 2300, CH-1211, Geneva, Switzerland.]

  • Shabbott, C. J., and P. M. Markowski, 2006: Surface in situ observations within the outflow of forward-flank down drafts of supercell thunderstorms. Mon. Wea. Rev., 134, 1422–1441, doi:10.1175/MWR3131.1.

    • Search Google Scholar
    • Export Citation

  • SIGMET, 2009: Vaisala user’s manual: Digital IF receiver/Doppler signal processor RVP8. SIGMET, 451 pp. [Available online at ftp://ftp.sigmet.com/outgoing/manuals/RVP8_Users_Manual.pdf.]

  • 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, 1979–2001, doi:10.1175/2010JTECHA1356.1.

    • Search Google Scholar
    • Export Citation

  • Solheim, F. S., R. Vivekanandan, R. H. Ware, and C. Rocken, 1999: Propagation delays induced in GPS signals by dry air, water vapor, hydrometeors, and other particulates. J. Geophys. Res., 104, 9663–9670, doi:10.1029/1999JD900095.

    • Search Google Scholar
    • Export Citation

  • Steiner, M., G. Lee, S. M. Ellis, and J. Vivekanandan, 2009: Quantitative precipitation estimation and hydrometeor identification using dual-polarization radar—Phase II. NCAR Tech. Rep., 74 pp. [Available online at ftp://ftp.eol.ucar.edu/pub/temp/users/sellis/Steiner_etal_2009/2009%20KMA-NIMR%20Report.pdf.]

  • Straka, J. M., 2009: Cloud and Precipitation Microphysics: Principles and Parameterizations. Cambridge University Press, 406 pp.

  • Tabary, P., G. Vulpiani, J. J. Gourley, A. J. Illingworth, and O. Bousquet, 2009: Unusually high differential attenuation at C band: Results from a two-year analysis of the French Trappes polarimetric radar data. J. Appl. Meteor. Climatol., 48, 2037–2053, doi:10.1175/2009JAMC2039.1.

    • Search Google Scholar
    • Export Citation

  • Testud, J., E. Le Bouar, E. Obligis, and M. Ali-Mehenni, 2000: The rain profiling algorithm applied to polarimetric weather radar. J. Atmos. Oceanic Technol., 17, 332–356, doi:10.1175/1520-0426(2000)017<0332:TRPAAT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Thomson, A. D., and R. List, 1996: Raindrop spectra and updraft determination by combining Doppler radar and disdrometer. J. Atmos. Oceanic Technol., 13, 465–476, doi:10.1175/1520-0426(1996)013<0465:RSAUDB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Thurai, M., and V. N. Bringi, 2005: Drop axis ratios from a 2D video disdrometer. J. Atmos. Oceanic Technol., 22, 966–978, doi:10.1175/JTECH1767.1.

    • Search Google Scholar
    • Export Citation

  • Thurai, M., M. Szakall, V. N. Bringi, K. V. Beard, S. K. Mitra, and S. Borrmann, 2009: Drop shapes and axis ratio distributions: Comparisons between 2D video disdrometer and wind tunnel measurements. J. Atmos. Oceanic Technol., 26, 1427–1432, doi:10.1175/2009JTECHA1244.1.

    • Search Google Scholar
    • Export Citation

  • Thurai, M., W. A. Petersen, and L. D. Carey, 2010: DSD characteristics of a cool-season tornadic storm using C-band polarimetric radar and two 2D-video disdrometers. Proc. Sixth European Conf. on Radar Meteorology and Hydrology, Sibiu, Romania, European Meteorological Society, 1–6. [Available online at http://www.erad2010.org/pdf/oral/tuesday/radpol1/5_ERAD2010_0101.pdf.]

  • Thurai, M., W. A. Petersen, A. Tokay, C. Schultz, and P. Gatlin, 2011: Drop size distribution comparisons between PARSIVEL and 2-D video disdrometers. Adv. Geosci., 30, 3–9, doi:10.5194/adgeo-30-3-2011.

    • Search Google Scholar
    • Export Citation

  • Ulbrich, C. W., and N. E. Miller, 2001: Experimental test of the effects of Z–R law variations on comparison of WSR-88D rainfall amounts with surface rain gauge and disdrometer data. Wea. Forecasting, 16, 369–375, doi:10.1175/1520-0434(2001)016<0369:ETOTEO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Vivekanandan, J., W. M. Adams, and V. N. Bringi, 1991: Rigorous approach to polarimetric radar modeling of hydrometeor distributions. J. Appl. Meteor., 30, 1053–1063, doi:10.1175/1520-0450(1991)030<1053:RATPRM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Vivekanandan, J., R. Raghavan, and V. N. Bringi, 1993: Polarimetric radar modeling of mixtures of precipitation particles. IEEE Trans. Geosci. Remote Sens., 31, 1017–1030, doi:10.1109/36.263772.

    • 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, 381–388, doi:10.1175/1520-0477(1999)080<0381:CMRUSB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Vulpiani, G., P. Tabary, J. Parent du Chatelet, and F. Marzano, 2008: Comparison of advanced radar polarimetric techniques for operational attenuation correction at C band. J. Atmos. Oceanic Technol., 25, 1118–1135, doi:10.1175/2007JTECHA936.1.

    • 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, 1147–1170, doi:10.1175/BAMS-D-11-00010.1.

    • Search Google Scholar
    • Export Citation

  • Yuter, S. E., D. E. Kingsmill, L. B. Nance, and M. Loffler-Mang, 2006: Observations of precipitation size and fall speed characteristics within coexisting rain and wet snow. J. Appl. Meteor. Climatol., 45, 1450–1464, doi:10.1175/JAM2406.1.

    • Search Google Scholar
    • Export Citation

  • Zhang, G., S. Luchs, A. V. Ryzhkov, M. Xue, L. Ryzhkova, and Q. Cao, 2011: Winter precipitation microphysics characterized by polarimetric radar and video disdrometer observations in central Oklahoma. J. Appl. Meteor. Climatol., 50, 1558–1570, doi:10.1175/2011JAMC2343.1.

    • Search Google Scholar
    • Export Citation

  • Zrnić, D. S., R. J. Doviak, G. Zhang, and A. V. Ryzhkov, 2010: Bias in differential reflectivity due to cross-coupling through the radiation patterns of polarimetric weather radars. J. Atmos. Oceanic Technol., 27, 1624–1637, doi:10.1175/2010JTECHA1350.1.

    • Search Google Scholar
    • Export Citation
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