• Bohren, C. F., and D. R. Huffman, 1983: Absorption and Scattering of Light by Small Particles. John Wiley and Sons, 530 pp.

  • Boucher, R. J., and J. G. Wieler, 1985: Radar determination of snowfall rate and accumulation. J. Climate Appl. Meteor., 24, 6873, doi:10.1175/1520-0450(1985)024<0068:RDOSRA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Braham, R. R., Jr., 1990: Snow particle size spectra in lake effect snow. J. Appl. Meteor., 29, 200207, doi:10.1175/1520-0450(1990)029<0200:SPSSIL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • 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, 410414, doi:10.1175/1520-0426(1995)012<0410:IMOTIW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Deng, M., G. G. Mace, Z. Wang, and H. Okamoto, 2010: Tropical Composition, Cloud and Climate Coupling Experiment validation for cirrus cloud profiling retrieval using CloudSat radar and CALIPSO lidar. J. Geophys. Res., 115, D00J15, doi:10.1029/2009JD013104.

    • Search Google Scholar
    • Export Citation
  • Deng, M., G. G. Mace, Z. Wang, and R. P. Lawson, 2013: Evaluation of several A-Train ice cloud retrieval products with in situ measurements collected during the SPARTICUS campaign. J. Appl. Meteor. Climatol., 52, 10141030, doi:10.1175/JAMC-D-12-054.1.

    • Search Google Scholar
    • Export Citation
  • Field, P. R., A. J. Heymsfield, and A. Bansemer, 2006: Shattering and particle interarrival times measured by optical array probes in ice clouds. J. Atmos. Oceanic Technol., 23, 13571371, doi:10.1175/JTECH1922.1.

    • Search Google Scholar
    • Export Citation
  • Fujiyoshi, Y., T. Endoh, T. Yamada, K. Tsuboki, Y. Tachibana, and G. Wakahama, 1990: Determination of a ZR relationship for snowfall using a radar and high sensitivity snow gauges. J. Appl. Meteor., 29, 147152, doi:10.1175/1520-0450(1990)029<0147:DOARFS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gaussiat, N., H. Sauvageot, and A. J. Illingworth, 2003: Cloud liquid water and ice content retrieval by multiwavelength radar. J. Atmos. Oceanic Technol., 20, 12641275, doi:10.1175/1520-0426(2003)020<1264:CLWAIC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hammonds, K. D., G. G. Mace, and S. Y. Matrosov, 2014: Characterizing the radar backscatter-cross-section sensitivities of ice-phase hydrometeor size distributions via a simple scaling of the Clausius–Mossotti factor. J. Appl. Meteor. Climatol., 53, 27612774, doi:10.1175/JAMC-D-13-0280.1.

    • Search Google Scholar
    • Export Citation
  • Hanesch, M., 1999: Fall velocity and shape of snowflakes. Ph.D. thesis, Swiss Federal Institute of Technology, Zurich, Switzerland, 123 pp. [Available online at http://e-collection.library.ethz.ch/eserv/eth:23207/eth-23207-02.pdf.]

  • Haynes, J. M., T. S. L’Ecuyer, G. L. Stephens, S. D. Miller, C. Mitrescu, N. B. Wood, and S. Tanelli, 2009: Rainfall retrieval over the ocean with spaceborne W-band radar. J. Geophys. Res., 114, D00A22, doi:10.1029/2008JD009973.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., and J. L. Parrish, 1978: A computational technique for increasing the effective sampling volume of the PMS two-dimensional particle size spectrometer. J. Appl. Meteor., 17, 15661572, doi:10.1175/1520-0450(1978)017<1566:ACTFIT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., and A. G. Palmer, 1986: Relationships for deriving thunderstorm anvil mass flux for CCOPE storm water budget estimates. J. Climate Appl. Meteor., 25, 691702, doi:10.1175/1520-0450(1986)025<0691:RFDTAI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., and C. D. Westbrook, 2010: Advances in the estimation of ice particle fall speeds using laboratory and field measurements. J. Atmos. Sci., 67, 24692482, doi:10.1175/2010JAS3379.1.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., A. Bansemer, P. R. Field, S. L. Durden, J. Stith, J. E. Dye, and W. Hall, 2002: Observations and parameterizations of particle size distributions in deep tropical cirrus and stratiform precipitating clouds: Results from in situ observations in TRMM field campaigns. J. Atmos. Sci., 59, 34573491, doi:10.1175/1520-0469(2002)059<3457:OAPOPS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., A. Bansemer, C. Schmitt, C. Twohy, and M. Poellot, 2004: Effective ice particle densities derived from aircraft data. J. Atmos. Sci., 61, 9821003, doi:10.1175/1520-0469(2004)061<0982:EIPDDF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., Z. Wang, and S. Matrosov, 2005: Improved radar ice water content retrieval algorithms using coincident microphysical and radar measurements. J. Appl. Meteor., 44, 13911412, doi:10.1175/JAM2282.1.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., C. Schmitt, and A. Bansemer, 2013: Ice cloud particle size distributions and pressure-dependent terminal velocities from in situ observations at temperatures from 0° to −86°C. J. Atmos. Sci., 70, 41234154, doi:10.1175/JAS-D-12-0124.1.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., A. Bansemer, M. R. Poellot, and N. Wood, 2015: Observations of ice microphysics through the melting layer. J. Atmos. Sci., 72, 29022928, doi:10.1175/JAS-D-14-0363.1.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, G. M., L. Tian, A. J. Heymsfield, L. Li, and S. Guimond, 2010: Characteristics of deep tropical and subtropical convection from nadir-viewing high-altitude airborne Doppler radar. J. Atmos. Sci., 67, 285308, doi:10.1175/2009JAS3132.1.

    • Search Google Scholar
    • Export Citation
  • Hiley, M. J., M. S. Kulie, and R. Bennartz, 2011: Uncertainty analysis for CloudSat snowfall retrievals. J. Appl. Meteor. Climatol., 50, 399418, doi:10.1175/2010JAMC2505.1.

    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., and C. D. Westbrook, 2014: Equation for the microwave backscatter cross section of aggregate snowflakes using the self-similar Rayleigh–Gans approximation. J. Atmos. Sci., 71, 32923301, doi:10.1175/JAS-D-13-0347.1.

    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., M. P. Mittermaier, and A. J. Illingworth, 2006: The retrieval 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.

    • Search Google Scholar
    • Export Citation
  • Hong, G., 2007: Radar backscattering properties of nonspherical ice crystals at 94 GHz. J. Geophys. Res., 112, D22203, doi:10.1029/2007JD008839.

    • Search Google Scholar
    • Export Citation
  • Huang, G. W., V. N. Bringi, D. Moisseev, W. A. Petersen, L. Bliven, and D. Hudak, 2015: Use of 2D-video disdrometer to derive mean density–size and Ze–SR relations: Four snow cases from the Light Precipitation Validation Experiment. Atmos. Res., 153, 3448, doi:10.1016/j.atmosres.2014.07.013.

    • Search Google Scholar
    • Export Citation
  • Imai, I., M. Fujiwara, I. Chimura, and Y. Toyama, 1955: Radar reflectivity of falling snow. Pap. Meteor. Geophys., 6, 130139.

  • Intrieri, J. M., G. L. Stephens, W. L. Eberhard, and T. Uttal, 1993: A method for determining cirrus cloud particle sizes using lidar and radar backscatter technique. J. Appl. Meteor., 32, 10741082, doi:10.1175/1520-0450(1993)032<1074:AMFDCC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • King, W. D., 1986: Air flow and particle trajectories around aircraft fuselages. IV: Orientation of ice crystals. J. Atmos. Oceanic Technol., 3, 433439, doi:10.1175/1520-0426(1986)003<0433:AFAPTA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Korolev, A., and G. Isaac, 2003: Roundness and aspect ratio of particles in ice clouds. J. Atmos. Sci., 60, 17951808, doi:10.1175/1520-0469(2003)060<1795:RAAROP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kulie, M. S., and R. Bennartz, 2009: Utilizing spaceborne radars to retrieve dry snowfall. J. Appl. Meteor. Climatol., 48, 25642580, doi:10.1175/2009JAMC2193.1.

    • Search Google Scholar
    • Export Citation
  • Kulie, M. S., R. Bennartz, T. J. Greenwald, Y. Chen, and F. Weng, 2010: Uncertainties in microwave properties of frozen precipitation: Implications for remote sensing and data assimilation. J. Atmos. Sci., 67, 34713487, doi:10.1175/2010JAS3520.1.

    • Search Google Scholar
    • Export Citation
  • Lebsock, M. D., and T. S. L’Ecuyer, 2011: The retrieval of warm rain from CloudSat. J. Geophys. Res., 116, D20209, doi:10.1029/2011JD016076.

    • Search Google Scholar
    • Export Citation
  • Leinonen, J., S. Kneifel, D. Moisseev, J. Tyynela, S. Tanelli, and T. Nousiainen, 2012: Nonspheroidal behavior in millimeter-wavelength radar observations of snowfall. J. Geophys. Res., 117, D18205, doi:10.1029/2012JD017680.

    • Search Google Scholar
    • Export Citation
  • Liao, L., R. Meneghini, L. Tian, and G. Heymsfield, 2008: Retrieval of snow and rain from combined X- and W-band airborne radar measurements. IEEE Trans. Geosci. Remote Sens., 46, 15141524, doi:10.1109/TGRS.2008.916079.

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

    • Search Google Scholar
    • Export Citation
  • Liu, G., 2008: Deriving snow cloud characteristics from CloudSat observations. J. Geophys. Res., 113, D00A09, doi:10.1029/2007JD009766.

  • Marshall, J. S., and W. M. Palmer, 1948: The distribution of raindrops with size. J. Meteor., 5, 165166, doi:10.1175/1520-0469(1948)005<0165:TDORWS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., 1992: Radar reflectivity in snowfall. IEEE Trans. Geosci. Remote Sens., 30, 454461, doi:10.1109/36.142923.

  • Matrosov, S. Y., 1997: Variability of microphysical parameters in high-altitude ice clouds: Results of the remote sensing method. J. Appl. Meteor., 36, 633648, doi:10.1175/1520-0450-36.6.633.

    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., 1998: A dual-wavelength radar method to measure snowfall rate. J. Appl. Meteor., 37, 15101521, doi:10.1175/1520-0450(1998)037<1510:ADWRMT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., 2007: Modeling backscatter properties of snowfall at millimeter wavelengths. J. Atmos. Sci., 64, 17271736, doi:10.1175/JAS3904.1.

    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., and A. J. Heymsfield, 2008: Estimating ice content and extinction in precipitating cloud systems from CloudSat radar measurements. J. Geophys. Res., 113, D00A05, doi:10.1029/2007JD009633.

    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., B. W. Orr, R. A. Kropfli, and J. B. Snider, 1994: Retrieval of vertical profiles of cirrus cloud microphysical parameters from Doppler radar and infrared radiometer measurements. J. Appl. Meteor., 33, 617626, doi:10.1175/1520-0450(1994)033<0617:ROVPOC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., C. Campbell, D. Kingsmill, and E. Sukovich, 2009: Assessing snowfall rates from X-band radar reflectivity measurements. J. Atmos. Oceanic Technol., 26, 23242339, doi:10.1175/2009JTECHA1238.1.

    • Search Google Scholar
    • Export Citation
  • McGill, M. J., D. L. Hlavka, W. D. Hart, E. J. Welton, and J. R. Campbell, 2003: Airborne lidar measurements of aerosol optical properties during SAFARI-2000. J. Geophys. Res., 108, 8493, doi:10.1029/2002JD002370.

    • Search Google Scholar
    • Export Citation
  • Mitchell, D. L., and A. J. Heymsfield, 2005: Refinements in the treatment of ice particle terminal velocities, highlighting aggregates. J. Atmos. Sci., 62, 16371644, doi:10.1175/JAS3413.1.

    • Search Google Scholar
    • Export Citation
  • Mitrescu, C., T. L’Ecuyer, J. Haynes, S. Miller, and J. Turk, 2010: CloudSat precipitation profiling algorithm-model description. J. Appl. Meteor. Climatol., 49, 9911003, doi:10.1175/2009JAMC2181.1.

    • Search Google Scholar
    • Export Citation
  • Ohtake, T., 1970: Factors affecting the size distribution of raindrops and snowflakes. J. Atmos. Sci., 27, 804813, doi:10.1175/1520-0469(1970)027<0804:FATSDO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Petty, G. W., and W. Huang, 2010: Microwave backscatter and extinction by soft ice spheres and complex snow aggregates. J. Atmos. Sci., 67, 769787, doi:10.1175/2009JAS3146.1.

    • Search Google Scholar
    • Export Citation
  • Protat, A., J. Delanoë, D. Bouniol, A. J. Heymsfield, A. Bansemer, and P. Brown, 2007: Evaluation of ice water content retrievals from cloud radar reflectivity and temperature using a large airborne in situ microphysical database. J. Appl. Meteor. Climatol., 46, 557572, doi:10.1175/JAM2488.1.

    • Search Google Scholar
    • Export Citation
  • Puhakka, T., 1975: On the dependence of Z–R relation on the temperature in snowfall. Preprints, 16th Radar Meteorology Conf., Houston, TX, Amer. Meteor. Soc., 504–507.

  • Rasmussen, R., M. Dixon, S. Vasiloff, F. Hage, S. Knight, J. Vivekanandan, and M. Xu, 2003: Snow nowcasting using a real-time correlation of radar reflectivity with snow gauge accumulation. J. Appl. Meteor., 42, 2036, doi:10.1175/1520-0450(2003)042<0020:SNUART>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rodgers, C. D., 2000: Inverse Methods for Atmospheric Sounding: Theory and Practice. World Scientific Publishing, 240 pp.

  • Sekelsky, S. M., W. L. Ecklund, J. M. Firda, K. S. Gage, and R. E. McIntosh, 1999: Particle size estimation in ice-phase clouds using multifrequency radar reflectivity measurements at 95, 33, and 2.8 GHz. J. Appl. Meteor., 38, 528, doi:10.1175/1520-0450(1999)038<0005:PSEIIP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Sekhon, R. S., and R. C. Srivastava, 1970: Snow size spectra and radar reflectivity. J. Atmos. Sci., 27, 299307, doi:10.1175/1520-0469(1970)027<0299:SSSARR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Surussavadee, C., and D. H. Staelin, 2006: Comparison of AMSU millimeter-wave satellite observations, MM5/TBSCAT predicted radiances, and electromagnetic models for hydrometeors. IEEE Trans. Geosci. Remote Sens., 44, 26672678, doi:10.1109/TGRS.2006.873275.

    • Search Google Scholar
    • Export Citation
  • Tinel, C., J. Testud, J. Pelon, R. H. Hogan, A. Protat, J. Delanoë, and D. Bouniol, 2005: The retrieval of ice cloud properties from cloud radar and lidar synergy. J. Appl. Meteor., 44, 860875, doi:10.1175/JAM2229.1.

    • Search Google Scholar
    • Export Citation
  • Toon, O. B., and Coauthors, 2010: Planning, implementation, and first results of the Tropical Composition, Cloud and Climate Coupling Experiment (TC4). J. Geophys. Res., 115, D00J04, doi:10.1029/2009JD013073.

    • Search Google Scholar
    • Export Citation
  • Twohy, C. H., A. J. Schanot, and W. A. Cooper, 1997: Measurement of condensed water content in liquid and ice clouds using an airborne counterflow virtual impactor. J. Atmos. Oceanic Technol., 14, 197202, doi:10.1175/1520-0426(1997)014<0197:MOCWCI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Tyynela, J., J. Leinonen, D. Moisseev, and T. Nousiainen, 2011: Radar backscattering from snowflakes: Comparison of fractal, aggregate, and soft-spheroid models. J. Atmos. Oceanic Technol., 28, 13651372, doi:10.1175/JTECH-D-11-00004.1.

    • Search Google Scholar
    • Export Citation
  • Vasiloff, S., P. Bukovcic, A. Arthur, M. P. Meyers, K. Houck, J. Busto, and L. Tang, 2013: Evaluation of snowfall estimates from the Grand Junction, Colorado WSR-88D during winter 2012-2013. Proc. 36th Conf. on Radar Meteorology, Breckenridge, CO, Amer. Meteor. Soc., 14B.4. [Available online at https://ams.confex.com/ams/36Radar/webprogram/Paper228534.html.]

  • Wang, Z., and K. Sassen, 2002: Cirrus cloud microphysical property retrieval using lidar and radar measurements. Part I: Algorithm description and comparison with in situ data. J. Appl. Meteor., 41, 218229, doi:10.1175/1520-0450(2002)041<0218:CCMPRU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wang, Z., G. M. Heymsfield, L. Li, and A. J. Heymsfield, 2005: Retrieving optically thick ice cloud microphysical properties by using airborne dual-wavelength radar measurements. J. Geophys. Res., 110, D19201, doi:10.1029/2005JD005969.

    • Search Google Scholar
    • Export Citation
  • Wolfe, J. P., and J. R. Snider, 2012: A relationship between reflectivity and snow rate for a high-altitude S-band radar. J. Appl. Meteor. Climatol., 51, 11111128, doi:10.1175/JAMC-D-11-0112.1.

    • Search Google Scholar
    • Export Citation
  • Wood, N. B., T. S. L’Ecuyer, A. J. Heymsfield, and G. L. Stephens, 2015: Microphysical constraints on millimeter-wavelength scattering properties of snow particles. J. Appl. Meteor. Climatol., 54, 909931, doi:10.1175/JAMC-D-14-0137.1.

    • Search Google Scholar
    • Export Citation
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Toward Improving Ice Water Content and Snow-Rate Retrievals from Radars. Part I: X and W Bands, Emphasizing CloudSat

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  • 1 National Center for Atmospheric Research,* Boulder, Colorado
  • | 2 Cooperative Institute for Research in Environmental Sciences, University of Colorado, and NOAA/Earth System Research Laboratory, Boulder, Colorado
  • | 3 Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin
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Abstract

Microphysical data and radar reflectivities (Ze, −15 < Ze < 10 dB) measured from flights during the NASA Tropical Clouds, Convection, Chemistry and Climate field program are used to relate Ze at X and W band to measured ice water content (IWC). Because nearly collocated Ze and IWC were each directly measured, ZeIWC relationships could be developed directly. Using the particle size distributions and ice particle masses evaluated based on the direct IWC measurements, reflectivity–snowfall rate (ZeS) relationships were also derived. For −15 < Ze < 10 dB, the relationships herein yield larger IWC and S than given by the retrievals and earlier relationships. The sensitivity of radar reflectivity to particle size distribution and size-dependent mass, shape, and orientation introduces significant uncertainties in retrieved quantities since these factors vary substantially globally. To partially circumvent these uncertainties, a W-band ZeS relationship is developed by relating four years of global CloudSat reflectivity observations measured immediately above the melting layer to retrieved rain rates at the base of the melting layer. The supporting assumptions are that the water mass flux is constant through the melting layer, that the air temperature is nearly 0°C, and that the retrieved rain rates are well constrained. Where Ze > 10 dB, this ZeS relationship conforms well to earlier relationships, but for Ze < 10 dB it yields higher IWC and S. Because not all retrieval algorithms estimate either or both IWC and S, the authors use a large aircraft-derived dataset to relate IWC and S. The IWC can then be estimated from S and vice versa.

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

Corresponding author address: Andrew Heymsfield, NCAR, 3450 Mitchell Lane, Boulder, CO 80301. E-mail: heyms1@ucar.edu

Abstract

Microphysical data and radar reflectivities (Ze, −15 < Ze < 10 dB) measured from flights during the NASA Tropical Clouds, Convection, Chemistry and Climate field program are used to relate Ze at X and W band to measured ice water content (IWC). Because nearly collocated Ze and IWC were each directly measured, ZeIWC relationships could be developed directly. Using the particle size distributions and ice particle masses evaluated based on the direct IWC measurements, reflectivity–snowfall rate (ZeS) relationships were also derived. For −15 < Ze < 10 dB, the relationships herein yield larger IWC and S than given by the retrievals and earlier relationships. The sensitivity of radar reflectivity to particle size distribution and size-dependent mass, shape, and orientation introduces significant uncertainties in retrieved quantities since these factors vary substantially globally. To partially circumvent these uncertainties, a W-band ZeS relationship is developed by relating four years of global CloudSat reflectivity observations measured immediately above the melting layer to retrieved rain rates at the base of the melting layer. The supporting assumptions are that the water mass flux is constant through the melting layer, that the air temperature is nearly 0°C, and that the retrieved rain rates are well constrained. Where Ze > 10 dB, this ZeS relationship conforms well to earlier relationships, but for Ze < 10 dB it yields higher IWC and S. Because not all retrieval algorithms estimate either or both IWC and S, the authors use a large aircraft-derived dataset to relate IWC and S. The IWC can then be estimated from S and vice versa.

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

Corresponding author address: Andrew Heymsfield, NCAR, 3450 Mitchell Lane, Boulder, CO 80301. E-mail: heyms1@ucar.edu
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