• Boucher, R. J., R. Wexler, D. Atlas, and R. M. Lhermitte, 1965: Mesoscale wind structure revealed by Doppler radar. J. Appl. Meteor., 4, 590597, doi:10.1175/1520-0450(1965)004<0590:MWSRBD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Browne, I. C., 1952: Precipitation streaks as a cause of radar upper bands. Quart. J. Roy. Meteor. Soc., 78, 590595, doi:10.1002/qj.49707833809.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, F., and J. Dudhia, 2001: Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569585, doi:10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chu, Y., 2002: Beam broadening effect on oblique MST radar Doppler spectrum. J. Atmos. Oceanic Technol., 19, 19551967, doi:10.1175/1520-0426(2002)019<1955:BBEOOM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Colle, B. A., D. Stark, and S. E. Yuter, 2014: Surface microphysical observations within East Coast winter storms on Long Island, New York. Mon. Wea. Rev., 142, 31263146, doi:10.1175/MWR-D-14-00035.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Douglas, R. H., K. L. S. Gunn, and J. S. Marshall, 1957: Pattern in the vertical of snow generation. J. Meteor., 14, 95114, doi:10.1175/1520-0469(1957)014<0095:PITVOS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doviak, R. J., and D. S. Zrnić, 1993: Doppler Radar and Weather Observations. 2nd ed. Academic Press, 562 pp.

  • Ellis, S. M., and J. Vivekanandan, 2010: Water vapor estimates using simultaneous dual-wavelength radar observations. Radio Sci., 45, RS5002, doi:10.1029/2009RS004280.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ellis, S. M., and J. Vivekanandan, 2011: Liquid water content estimates using simultaneous S and Ka band radar measurements. Radio Sci., 46, RS2021, doi:10.1029/2010RS004361.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1988: Observational evidence of slantwise convective adjustment. Mon. Wea. Rev., 116, 18051816, doi:10.1175/1520-0493(1988)116<1805:OEOSCA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ganetis, S. A., and B. A. Colle, 2015: The thermodynamic and microphysical evolution of an intense snowband during the Northeast U.S. blizzard of 8–9 February 2013. Mon. Wea. Rev., 143, 41044125, doi:10.1175/MWR-D-14-00407.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Geerts, B., and P. V. Hobbs, 1991: Organization and structure of clouds and precipitation on the mid-Atlantic coast of the United States. Part IV: Retrieval of the thermodynamic and microphysical structures of a frontal rainband from Doppler radar data. J. Atmos. Sci., 48, 12871305, doi:10.1175/1520-0469(1991)048<1287:OASOCA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffin, E. M., T. J. Schuur, A. V. Ryzhkov, H. D. Reeves, and J. C. Picca, 2014: A polarimetric and microphysical investigation of the Northeast blizzard of 8–9 February 2013. Wea. Forecasting, 29, 12711294, doi:10.1175/WAF-D-14-00056.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gunn, K. L. S., M. P. Langleben, A. S. Dennis, and B. A. Power, 1954: Radar evidence of a generating level for snow. J. Meteor., 11, 2026, doi:10.1175/1520-0469(1954)011<0020:REOAGL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gunn, R. E. S., and J. S. Marshall, 1955: The effect of wind shear on falling precipitation. J. Meteor., 12, 339349, doi:10.1175/1520-0469(1955)012<0339:TEOWSO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Herzegh, P. H., and P. V. Hobbs, 1980: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. II: Warm-frontal clouds. J. Atmos. Sci., 37, 597611, doi:10.1175/1520-0469(1980)037<0597:TMAMSA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hobbs, P. V., and J. D. Locatelli, 1978: Rainbands, precipitation cores and generating cells in a cyclonic storm. J. Atmos. Sci., 35, 230241, doi:10.1175/1520-0469(1978)035<0230:RPCAGC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., N. Gaussiat, and A. J. Illingworth, 2005: Stratocumulus liquid water content from dual-wavelength radar. J. Atmos. Oceanic Technol., 22, 12071218, doi:10.1175/JTECH1768.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341, doi:10.1175/MWR3199.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houze, R. A., Jr., S. A. Rutledge, T. J. Matejka, and P. V. Hobbs, 1981: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. III: Air motions and precipitation growth in a warm frontal rainband. J. Atmos. Sci., 38, 639649, doi:10.1175/1520-0469(1981)038<0639:TMAMSA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Iacono, M., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, doi:10.1029/2008JD009944.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiménez, P. A., J. Dudhia, J. F. González-Rouco, J. Navarro, J. P. Montávez, and E. García-Bustamante, 2012: A revised scheme for the WRF surface layer formulation. Mon. Wea. Rev., 140, 898918, doi:10.1175/MWR-D-11-00056.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jurewicz, M. L., Sr., and M. S. Evans, 2004: A comparison of two banded, heavy snowstorms with very different synoptic settings. Wea. Forecasting, 19, 10111028, doi:10.1175/WAF-823.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Keeler, J. M., B. F. Jewett, R. M. Rauber, G. M. McFarquhar, R. M. Rasmussen, L. Xue, C. Liu, and G. Thompson, 2016: Dynamics of cloud-top generating cells in winter cyclones. Part I: Idealized simulations in the context of field observations. J. Atmos. Sci., 73, 15071527, doi:10.1175/JAS-D-15-0126.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kennedy, P. C., and S. A. Rutledge, 2011: S-band dual-polarization radar observations of winter storms. J. Appl. Meteor. Climatol., 50, 844858, doi:10.1175/2010JAMC2558.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kocin, P. J., and L. W. Uccellini, 2004: Overview. Vol. 1, Northeast Snowstorms, Meteor. Monogr., No. 54, Amer. Meteor. Soc., 289 pp.

    • Crossref
    • Export Citation
  • Kreitzberg, C. W., and H. A. Brown, 1970: Mesoscale weather systems within an occlusion. J. Appl. Meteor., 9, 417432, doi:10.1175/1520-0450(1970)009<0417:MWSWAO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumjian, M. R., S. Rutledge, R. Rasmussen, P. Kennedy, and M. Dixon, 2014: High-resolution polarimetric radar observations of snow-generating cells. J. Appl. Meteor. Climatol., 53, 16361658, doi:10.1175/JAMC-D-13-0312.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Langleben, M. P., 1956: The plan pattern of snow echoes at the generating level. J. Meteor., 13, 554560, doi:10.1175/1520-0469(1956)013<0554:TPPOSE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, W. C., P. Dodge, F. D. Marks, and P. H. Hildebrand, 1994: Mapping of airborne Doppler radar data. J. Atmos. Oceanic Technol., 11, 572578, doi:10.1175/1520-0426(1994)011<0572:MOADRD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lhermitte, R., 1987: A 94-GHz Doppler radar for cloud observations. J. Atmos. Oceanic Technol., 4, 3648, doi:10.1175/1520-0426(1987)004<0036:AGDRFC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, L., and Coauthors, 2000: Ice cloud extinction retrieval using ground-based and airborne millimeter-wave cloud radar measurements. Proc. 10th ARM Science Team Meeting, San Antonio, TX, Atmospheric Radiation Measurement Program, 1–6. [Available online at www.arm.gov/publications/proceedings/conf10/extended_abs/li_l.pdf.]

  • Marshall, J. S., 1953: Precipitation trajectories and patterns. J. Meteor., 10, 2529, doi:10.1175/1520-0469(1953)010<0025:PTAP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, D., R. F. Reinking, R. A. Kropfli, B. E. Martner, and B. W. Bartram, 2001: On the use of radar depolarization ratios for estimating shapes of ice hydrometeors in winter clouds. J. Appl. Meteor., 40, 479490, doi:10.1175/1520-0450(2001)040<0479:OTUORD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., and A. Battaglia, 2009: Influence of multiple scattering on CloudSat measurements in snow: A model study. Geophys. Res. Lett., 36, L12806, doi:10.1029/2009GL038704.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mittermaier, M. P., R. J. Hogan, and A. J. Illingworth, 2004: Using mesoscale model winds for correcting wind-drift errors in radar estimates of surface rainfall. Quart. J. Roy. Meteor. Soc., 130, 21052123, doi:10.1256/qj.03.156.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nathanson, F., 1969: Radar Design Principles. McGraw-Hill, 626 pp.

  • Novak, D. R., L. F. Bosart, D. Keyser, and J. S. Waldstreicher, 2004: An observational study of cold season-banded precipitation in Northeast U.S. cyclones. Wea. Forecasting, 19, 9931010, doi:10.1175/815.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Novak, D. R., L. F. Bosart, and S. E. Yuter, 2008: High-resolution observations and model simulations of the life cycle of an intense mesoscale snowband over the northeastern United States. Mon. Wea. Rev., 136, 14331456, doi:10.1175/2007MWR2233.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Novak, D. R., L. F. Bosart, and A. R. Aiyyer, 2010: Evolution of mesoscale precipitation band environments within the comma head of Northeast U.S. cyclones. Mon. Wea. Rev., 138, 23542374, doi:10.1175/2010MWR3219.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oue, M., M. Kumjian, Y. Lu, J. Verlinde, K. Aydin, and E. E. Clothiaux, 2015: Linear depolarization ratios of columnar ice crystals in a deep precipitating system over the Arctic observed by zenith-pointing Ka-band Doppler radar. J. Appl. Meteor. Climatol., 54, 10601068, doi:10.1175/JAMC-D-15-0012.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Picca, J. C., D. M. Schultz, B. A. Colle, S. Ganetis, D. R. Novak, and M. J. Sienkiewicz, 2014: The value of dual-polarization radar in diagnosing the complex microphysical evolution of an intense snowband. Bull. Amer. Meteor. Soc., 95, 18251834, doi:10.1175/BAMS-D-13-00258.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Plank, V. G., D. Atlas, and W. H. Paulsen, 1955: The nature and detectability of clouds and precipitation as determined by 1.25-centimeter radar. J. Meteor., 12, 358378, doi:10.1175/1520-0469(1955)012<0358:TNADOC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Plummer, D. M., G. M. McFarquhar, R. M. Rauber, B. F. Jewett, and D. C. Leon, 2014: Structure and statistical analysis of the microphysical properties of generating cells in the comma head region of continental winter cyclones. J. Atmos. Sci., 71, 41814203, doi:10.1175/JAS-D-14-0100.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Plummer, D. M., G. M. McFarquhar, R. M. Rauber, B. F. Jewett, and D. C. Leon, 2015: Microphysical properties of convectively generated fall streaks in the comma-head region of continental winter cyclones. J. Atmos. Sci., 72, 24652483, doi:10.1175/JAS-D-14-0354.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rauber, R. M., and Coauthors, 2014a: Stability and charging characteristics of the comma head region of continental winter cyclones. J. Atmos. Sci., 71, 15591582, doi:10.1175/JAS-D-13-0253.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rauber, R. M., M. K. Macomber, D. M. Plummer, A. A. Rosenow, G. M. McFarquhar, B. F. Jewett, D. Leon, and J. M. Keeler, 2014b: Finescale radar and airmass structure of the comma head of a continental winter cyclone: The role of three airstreams. Mon. Wea. Rev., 142, 42074229, doi:10.1175/MWR-D-14-00057.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rauber, R. M., and Coauthors, 2015: The role of cloud-top generating cells and boundary-layer circulations in the finescale radar structure of a winter cyclone over the Great Lakes. Mon. Wea. Rev., 143, 22912318, doi:10.1175/MWR-D-14-00350.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reinking, R. F., S. Y. Matrosov, L. Kropfli, and B. W. Bartram, 2002: Evaluation of a slant quasi-linear radar polarization state for distinguishing drizzle droplets, pristine ice crystals, and less regular ice particles. J. Atmos. Oceanic Technol., 19, 296321, doi:10.1175/1520-0426-19.3.296.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reuter, G. W., and M. K. Yau, 1990: Observations of slantwise convective instability in winter cyclones. Mon. Wea. Rev., 118, 447458, doi:10.1175/1520-0493(1990)118<0447:OOSCII>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rosenow, A. A., D. M. Plummer, R. M. Rauber, G. M. McFarquhar, B. F. Jewett, and D. Leon, 2014: Vertical velocity and physical structure of generating cells and convection in the comma head region of continental winter cyclones. J. Atmos. Sci., 71, 15381558, doi:10.1175/JAS-D-13-0249.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A., P. Zhang, H. Reeves, M. Kumjian, T. Schallener, S. Trömel, and C. Simmer, 2016: Quasi-vertical profiles—A new way to look at polarimetric radar data. J. Atmos. Oceanic Technol., 33, 551562, doi:10.1175/JTECH-D-15-0020.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sanders, F., 1986: Frontogenesis and symmetric stability in a major New England snowstorm. Mon. Wea. Rev., 114, 18471862, doi:10.1175/1520-0493(1986)114<1847:FASSIA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sanders, F., and L. F. Bosart, 1985: Mesoscale structure in the megalopolitan snowstorm, 11–12 February 1983. Part II: Doppler radar study of the New England snowband. J. Atmos. Sci., 42, 13981407, doi:10.1175/1520-0469(1985)042<1398:MSITMS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schrom, R. S., and M. R. Kumjian, 2016: Connecting microphysical processes in Colorado winter storms with vertical profiles of radar observations. J. Appl. Meteor. Climatol., 55, 17711787, doi:10.1175/JAMC-D-15-0338.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seltzer, M. A., R. E. Passarelli, and K. A. Emanuel, 1985: The possible role of symmetric instability in the formation of precipitation bands. J. Atmos. Sci., 42, 22072219, doi:10.1175/1520-0469(1985)042<2207:TPROSI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stark, D., B. A. Colle, and S. E. Yuter, 2013: Observed microphysical evolution for two East Coast winter storms and the associated snow bands. Mon. Wea. Rev., 141, 20372057, doi:10.1175/MWR-D-12-00276.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Syrett, W. J., B. A. Albrecht, and E. E. Clothiaux, 1995: Vertical cloud structure in a midlatitude cyclone from a 94-GHz radar. Mon. Wea. Rev., 123, 33933407, doi:10.1175/1520-0493(1995)123<3393:VCSIAM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Szyrmer, W., and I. Zawadzki, 2014: Snow studies. Part IV: Ensemble retrieval of snow microphysics from dual-wavelength vertically pointing radars. J. Atmos. Sci., 71, 11581170, doi:10.1175/JAS-D-12-0285.1.

    • Crossref
    • 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, 50955115, doi:10.1175/2008MWR2387.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • UCAR/NCAR, 2014: HIAPER cloud radar (HCR). Earth Observing Laboratory, 2014-present, accessed 15 March 2016, doi:10.5065/D6BP00TP.

    • Crossref
    • Export Citation
  • UCAR/NCAR, 2015: HIAPER Gulfstream GV. Earth Observing Laboratory, 2005-present, accessed 15 March 2016, doi:10.5065/D6DR2SJP.

    • Crossref
    • Export Citation
  • Vivekanandan, J., D. S. Zrnić, S. M. Ellis, R. Oye, 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
  • Vivekanandan, J., and Coauthors, 2015: A wing pod-based millimeter wavelength airborne cloud radar. Geosci. Instrum. Methods Data Syst., 4, 161176, doi:10.5194/gi-4-161-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wexler, R., 1955: Radar analysis of precipitation streamers observed 25 February 1954. J. Atmos. Sci., 12, 391393, doi:10.1175/1520-0469(1955)012<0391:RAOPSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wexler, R., and D. Atlas, 1959: Precipitation generating cells. J. Meteor., 16, 327332, doi:10.1175/1520-0469(1959)016<0327:PGC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wexler, R., A. C. Chmela, and G. M. Armstrong, 1967: Wind field observations by Doppler radar in a New England snowstorm. Mon. Wea. Rev., 95, 929935, doi:10.1175/1520-0493(1967)095<0929:WFOBDR>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wolfsberg, D. G., K. A. Emanuel, and R. E. Passarelli, 1986: Band formation in a New England winter storm. Mon. Wea. Rev., 114, 15521569, doi:10.1175/1520-0493(1986)114<1552:BFIANE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • View in gallery
    Fig. 1.

    Illustration of the HCR airborne configuration. The large underwing pod is pictured to the left. The radome is the white section that extends in front of the leading edge of the wing. Inside the large pod is the pressure vessel, as illustrated in the upper right. Many of the important components are located in the pressure vessel including the transceiver, modulator, and data system. A single rack is required in the cabin, saving valuable room for research equipment and staff.

  • View in gallery
    Fig. 2.

    Composite radar analysis of the 2 Feb 2015 cyclone at 1500 UTC. The thin white lines are sea level pressure (hPa), the dashed yellow line is the 0°C surface isotherm, and the solid yellow line is the flight track of the GV aircraft. The red line denotes the track of the low pressure center during the flight, with positions and minimum sea level pressures noted at 1800 and 2100 UTC 2 Feb, and 0000 UTC 3 Feb.

  • View in gallery
    Fig. 3.

    Total snowfall distribution (in.) associated with the 2 Feb 2015 storm [image (with changes) courtesy of www.weather.com, used with permission].

  • View in gallery
    Fig. 4.

    (a) Cross section along flight track between 1418 and 1533 UTC from the WRF simulation showing equivalent potential temperature (K, black lines) and wind component normal to cross section [m s−1, hot (cold) colors into (out of) cross section]. (b) As in (a), but for wind component parallel to cross section. Key temperatures (°C) are denoted with red lines. The GV flight track is denoted at the top of the cross section. Vertical gray bars denote the locations of HCR cross sections in Figs. 611.

  • View in gallery
    Fig. 5.

    WSR-88D 0.5° scans showing the radar reflectivity factor from (a) Bangor (KGYX) at 1434 UTC; (b) Boston (KBOX) at 1448 UTC; (c) Upton, NY (KOKX), at 1457 UTC; (d) KOKX at 1503 UTC, (e) Mount Holly, NJ (KDIX), at 1515 UTC; and (f) KDIX at 1529 UTC 2 Feb 2015. Locations of cross sections in Figs. 611 are shown in the small circles in (a)–(f), respectively.

  • View in gallery
    Fig. 6.

    (a) Equivalent radar reflectivity factor, (b) vertical radial velocity, (c) spectral width, and (d) linear depolarization ratio measured by the HCR during a 1-min period beginning at 1434 UTC 2 Feb 2015. The location of the cross section is indicated on Figs. 4 and 5.

  • View in gallery
    Fig. 7.

    As in Fig. 6, but for a 1-min period beginning at 1448 UTC 2 Feb 2015.

  • View in gallery
    Fig. 8.

    As in Fig. 6, but for a 1-min period beginning at 1457 UTC 2 Feb 2015.

  • View in gallery
    Fig. 9.

    As in Fig. 6, but for a 1-min period beginning at 1503 UTC 2 Feb 2015.

  • View in gallery
    Fig. 10.

    As in Fig. 6, but for a 1-min period beginning at 1515 UTC 2 Feb 2015.

  • View in gallery
    Fig. 11.

    As in Fig. 6, but for a 1-min period beginning at 1529 UTC 2 Feb 2015.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 321 104 8
PDF Downloads 267 97 7

Finescale Structure of a Snowstorm over the Northeastern United States: A First Look at High-Resolution HIAPER Cloud Radar Observations

Robert M. RauberDepartment of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois

Search for other papers by Robert M. Rauber in
Current site
Google Scholar
PubMed
Close
,
Scott M. EllisEarth Observing Laboratory, National Center for Atmospheric Research,* Boulder, Colorado

Search for other papers by Scott M. Ellis in
Current site
Google Scholar
PubMed
Close
,
J. VivekanandanEarth Observing Laboratory, National Center for Atmospheric Research,* Boulder, Colorado

Search for other papers by J. Vivekanandan in
Current site
Google Scholar
PubMed
Close
,
Jeffrey StithEarth Observing Laboratory, National Center for Atmospheric Research,* Boulder, Colorado

Search for other papers by Jeffrey Stith in
Current site
Google Scholar
PubMed
Close
,
Wen-Chau LeeEarth Observing Laboratory, National Center for Atmospheric Research,* Boulder, Colorado

Search for other papers by Wen-Chau Lee in
Current site
Google Scholar
PubMed
Close
,
Greg M. McFarquharDepartment of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois

Search for other papers by Greg M. McFarquhar in
Current site
Google Scholar
PubMed
Close
,
Brian F. JewettDepartment of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois

Search for other papers by Brian F. Jewett in
Current site
Google Scholar
PubMed
Close
, and
Andrew JaniszeskiUniversity of Illinois at Urbana–Champaign, Urbana, Illinois

Search for other papers by Andrew Janiszeski in
Current site
Google Scholar
PubMed
Close
Full access

Abstract

The newly developed High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Cloud Radar (HCR) is an airborne, W-band, dual-polarization, Doppler research radar that fits within an underwing pod on the National Center for Atmospheric Research Gulfstream-V HIAPER aircraft. On 2 February 2015, the HCR was flown on its maiden research voyage over a cyclone along the Northeast coast of the United States. Six straight flight legs were flown over 6 h between the northern tip of Delaware Bay and Bangor, Maine, crossing the rain–snow line, and passing directly over Boston, Massachusetts, which received over 16 in. of snow during the event. The HCR, which recorded reflectivity, radial velocity, spectral width, and linear depolarization ratio with a 0.7° beam, was pointed at nadir from a flight altitude of 12,800 m (42,000 ft). The along-track resolution ranged between 20 and 200 m, depending on range, at aircraft speeds varying between 200 and 275 m s−1. The range resolution was 19.2 m.

Remarkably detailed finescale structures were found throughout the storm system, including cloud-top generating cells, upright elevated convection, layers of turbulence, vertical velocity perturbations across the melting level, gravity waves, boundary layer circulations, and other complex features. Vertical velocities in these features ranged from 1 to 5 m s−1, and many features were on scales of 5 km or less. The purpose of this paper is to introduce the HCR and highlight the remarkable finescale structures revealed within this Northeast U.S. cyclone by the HCR.

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

CORRESPONDING AUTHOR E-MAIL: Robert M. Rauber, r-rauber@illinois.edu

Abstract

The newly developed High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Cloud Radar (HCR) is an airborne, W-band, dual-polarization, Doppler research radar that fits within an underwing pod on the National Center for Atmospheric Research Gulfstream-V HIAPER aircraft. On 2 February 2015, the HCR was flown on its maiden research voyage over a cyclone along the Northeast coast of the United States. Six straight flight legs were flown over 6 h between the northern tip of Delaware Bay and Bangor, Maine, crossing the rain–snow line, and passing directly over Boston, Massachusetts, which received over 16 in. of snow during the event. The HCR, which recorded reflectivity, radial velocity, spectral width, and linear depolarization ratio with a 0.7° beam, was pointed at nadir from a flight altitude of 12,800 m (42,000 ft). The along-track resolution ranged between 20 and 200 m, depending on range, at aircraft speeds varying between 200 and 275 m s−1. The range resolution was 19.2 m.

Remarkably detailed finescale structures were found throughout the storm system, including cloud-top generating cells, upright elevated convection, layers of turbulence, vertical velocity perturbations across the melting level, gravity waves, boundary layer circulations, and other complex features. Vertical velocities in these features ranged from 1 to 5 m s−1, and many features were on scales of 5 km or less. The purpose of this paper is to introduce the HCR and highlight the remarkable finescale structures revealed within this Northeast U.S. cyclone by the HCR.

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

CORRESPONDING AUTHOR E-MAIL: Robert M. Rauber, r-rauber@illinois.edu

Finescale structures, including cloud-top generating cells, wave motions, and boundary layer circulations, are revealed within a major Northeast snowstorm using the new High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Cloud Radar.

Ground-based scanning radar systems have been used in research and operations for many decades to document mesoscale structures within winter cyclones over the Northeast United States. In research, these data are normally combined with rawinsonde or model analyses to explore the relationship between heavy precipitation bands and the forcing mechanisms that produce them (e.g., Sanders and Bosart 1985; Seltzer et al. 1985; Sanders 1986; Wolfsberg et al. 1986; Emanuel 1988; Reuter and Yau 1990; Geerts and Hobbs 1991; Jurewicz and Evans 2004; Novak et al. 2004, 2008, 2010). Radar data have also been used to investigate microphysical processes within the storms (e.g., Stark et al. 2013; Colle et al. 2014; Griffin et al. 2014; Picca et al. 2014; Ganetis and Colle 2015).

Measurements with vertically pointing radars in Northeast cyclones have an even longer history, dating to the end of the Second World War. Early reports of mesoscale structures within Northeast cyclones were based on data from radars employing wavelengths between 1.25 and 3.0 cm. These studies consistently identified convective generating cells and precipitation fall streaks at the top of otherwise stratiform warm frontal and comma head clouds (Browne 1952; Marshall 1953; Gunn et al. 1954; Wexler 1955; Gunn and Marshall 1955; Plank et al. 1955; Langleben 1956; Douglas et al. 1957; Wexler and Atlas 1959). The cells were found to form above fronts (Douglas et al. 1957), were ∼1 mi (1.6 km) in horizontal extent (Langleben 1956), had updrafts ranging from 0.75 to 3 m s−1 (Wexler and Atlas 1959), produced streamers of precipitation that merged as they fell to produce the stratiform radar echo (Gunn et al. 1954), and, when viewed with scanning radars, were organized by shear into linear bands (Wexler 1955). Subsequent radar measurements by Kreitzberg and Brown (1970) also found evidence for elevated convection and cellular structures.

The first Doppler radar measurements using vertically pointing radar in a Northeast snowstorm were reported by Boucher et al. (1965). They found, in what was thought to be stratiform clouds, updrafts and downdrafts of 2–4 m s−1 and rapidly evolving turbulent structures. They noted that it was “rather surprising to find such mesoscale structure in both the horizontal and vertical winds that accompany supposedly stratiform precipitation” and that the wind “varied strikingly” over distances of 5 km or less (Boucher et al. 1965, p. 597). Similar high-frequency variability in the wind field was subsequently noted by Wexler et al. (1967). Syrett et al. (1995, p. 3404), using a vertically pointing W-band (94 GHz) cloud radar, noted that the structure of “a fairly typical midlatitude cyclone” was “extremely complicated” with large convective cells near cloud top as well as smaller-scale, cloud-top generating cells.

These past investigations, recent microphysical studies using vertically pointing Ku-band and dual-polarization radar in East Coast cyclones (Stark et al. 2013; Colle et al. 2014; Picca et al. 2014; Griffin et al. 2014; Ganetis and Colle 2015), and airborne W-band radar observations of complex structures in continental winter cyclones (Rauber et al. 2014a,b, 2015; Plummer et al. 2014, 2015; Rosenow et al. 2014; Keeler et al. 2016), as well as past observations in cyclones on the U.S. West Coast (e.g., Hobbs and Locatelli 1978; Herzegh and Hobbs 1980; Houze et al. 1981), motivated a new investigation of the structure of Northeast cyclones using airborne W-band radar. Airborne radar measurements have the advantage of being able to document the finescale spatial variability of mesoscale structures (e.g., Rauber et al. 2014b), as opposed to the temporal structure over a single location, as afforded by fixed-site profiling radars.

A unique scientific opportunity developed in late 2014 when the testing phase of the new National Science Foundation (NSF)–National Center for Atmospheric Research (NCAR) High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER; UCAR/NCAR 2015) Cloud Radar (HCR) neared completion at NCAR. As part of the research associated with the Profiling of Winter Storms (PLOWS) experiment (Rauber et al. 2014a) and the field testing of the HCR, a target-of-opportunity single flight of the HIAPER HCR radar was carried out over a cyclone along the Northeast U.S. coast. The “Nor’easter flight” was carried out on 2 February 2015 over a storm that produced over 16 in. of snow in Boston, Massachusetts. The purpose of this article is to illustrate the spatial structure of mesoscale features previously noted in past investigations of Northeast snowstorms with ground-based, vertically pointing radars and to demonstrate the capabilities of the HCR system.

THE HIAPER CLOUD RADAR.

System overview.

The NCAR HIAPER Cloud Radar (UCAR/NCAR 2014) is a W-band (approximately 3-mm wavelength), dual-polarization, Doppler, airborne research radar developed to be housed in a standard, large, underwing aircraft pod as shown in Fig. 1 (Vivekanandan et al. 2015). An important innovation and asset of HCR is the real-time stabilization of the beam that accounts for changes in aircraft attitude during flight to keep the beam pointing in the specified direction. This capability results in the avoidance of many errors and artifacts associated with operating from a moving platform. The HCR is currently deployable on the NCAR Gulfstream V (GV, pronounced G-5) HIAPER aircraft but could potentially be mounted on another aircraft that can accommodate a large pod. The HCR is also deployable on the ground and is housed in half of a standard 6-m shipping container that can also contain the High Spectral Resolution Lidar. The specifications, design, and capabilities of the HCR are described in detail in Vivekanandan et al. (2015); some key specifications of the HCR for nominal operations are listed in Table 1.

Fig. 1.
Fig. 1.

Illustration of the HCR airborne configuration. The large underwing pod is pictured to the left. The radome is the white section that extends in front of the leading edge of the wing. Inside the large pod is the pressure vessel, as illustrated in the upper right. Many of the important components are located in the pressure vessel including the transceiver, modulator, and data system. A single rack is required in the cabin, saving valuable room for research equipment and staff.

Citation: Bulletin of the American Meteorological Society 98, 2; 10.1175/BAMS-D-15-00180.1

Table 1.

Specifications of HCR in its airborne configuration during nominal operations.

Table 1.

The range resolution, 19.2 m, was achieved by oversampling the 256-ns transmit pulse by a factor of 2. In general, the sensitivity will change with changing pulse length and dwell time. The along-track resolution in Table 1 is defined by the distance the aircraft travels in a single dwell time, combined with the physical beamwidth, and is valid for staring data, for example, nadir or zenith. At aircraft ground speeds varying between 200 and 275 m s−1 (depending on direction of travel relative to the wind), the along-track resolution during the flight described herein ranged between 20 and 200 m, depending on the radial distance from the aircraft.

The HCR reflector is capable of scanning perpendicular to the long axis of the pod at a scan rate up to 30° s−1. Scanning (or staring) perpendicular to the pod is possible over an approximately 230° sector, from about –5° to +225°, without interference from the fuselage or wing where 0° is defined as zenith and 180° is nadir.

Any user-defined scanning sector within those limits can be accomplished. In scanning mode, the along-track resolution at a particular elevation angle is defined by the time interval required for the beam to return to the given angle. By controlling the width of the scanning sector and the scan rate, the along-track resolution at a given ground speed can be determined by the user. For example, scanning from nadir to zenith and back takes about 13 s (allowing for the turnaround time). At 200 m s−1, the along-track sampling interval at a given angle would be about 2.6 km. The angular resolution of HCR depends on the chosen scan rate and dwell times. For the maximum scan rate of 30° s−1 and the typical dwell time of 0.1 s, the angular resolution is 3°, but if the dwell time were reduced to 0.01 s (100-Hz data rate), the resolution would be 0.3°. Currently, the beam stabilization option is not available during active scanning of the HCR reflector.

Many of HCR’s electronics are housed in a pressurized vessel within the pod (Fig. 1), allowing operation at the temperature and pressure extremes possible from sea level to 13.7 km (45,000 ft). The HCR uses only one rack inside the aircraft, thus saving valuable cabin space. Within the pod, a lens antenna illuminates a rotating reflector that allows the HCR to stare or scan perpendicular to the aircraft heading.

HCR measurements.

The most common operating configuration of the HCR is to transmit in vertical (V) polarization and receive both vertical and horizontal (H) polarizations, where H and V are with respect to Earth’s surface. The measurements include the equivalent radar reflectivity factor (Ze, hereafter reflectivity), radial velocity (Vr), velocity spectrum width (SW), and linear depolarization ratio (LDR).

The Ze is proportional to the sum of the backscattered power of all the particles within the volume measured by the radar. In distributed targets such as rain or snow, Ze depends on the number of particles, their size, and the index of refraction. The Vr is a measure of the reflectivity-weighted mean velocity of particles along the direction of the radar beam. In the case of the vertical pointing radar, Vr measures the sum of the vertical wind speed and particle fall speed. The SW is an estimate of the variance of the radial velocities of the different particles within the radar volume. Sources of variance that contribute to SW for HCR include wind shear within the radar volume, different particle fall speeds, turbulence, and the motion of the platform.

The HCR transmitted wave is linearly polarized, and the receiver measures power at polarizations both parallel to (copolar) and normal to (cross polar) the transmitted polarization. The LDR is the ratio of the received cross-polar power to the received copolar power. At vertical incidence, the copolar beam is roughly normal to the aircraft motion, and the cross-polar beam is parallel to the aircraft motion. When the HCR is pointing horizontally, the copolar pulse is vertically polarized. For vertical incidence, elongated particles oriented at 45° to the polarization plane or canted at 45° within the polarization plane will have large LDR values, while the intrinsic LDR of spherical particles would be negative infinity decibels. However, the practical LDR measurement is limited by the cross-polar isolation of the radar system itself. For HCR, the LDR limit is about –29 to –30 dB. Because the cross-polar power is up to about 30 dB (or 1,000 times) weaker than the copolar power, LDR has dramatically reduced sensitivity and thus data coverage, compared to the other measurements. Tumbling, wet, nonspherical particles such as hail, melting aggregates, wet graupel, and other melting particles are identified with large LDR values, whereas light rain and cloud droplets, and some dry ice particles such as low-density aggregates, are associated with low LDR values near the system limit (Vivekanandan et al. 1999). At vertical incidence, dry columnar and irregular ice crystals can have elevated LDR values that fall between the system limit and the LDR measured in the bright band (Matrosov et al. 2001; Reinking et al. 2002). In addition, the in-phase (I) and quadrature (Q) time series data are recorded for HCR operations, enabling Doppler spectral analysis.

Advantages and limitations.

Vertically pointing W-band radars have several advantages and disadvantages. An advantage of the high W-band frequency that is particularly important for airborne applications is that the hardware has small physical dimensions and is lightweight compared to lower-frequency radar systems. These W-band systems also have increased sensitivity to small hydrometeors (Doviak and Zrnić 1993), and the data typically have lower measurement variances than longer-wavelength radars (Doviak and Zrnić 1993; Ellis and Vivekanandan 2011).

However, W-band signals are significantly attenuated through the clear atmosphere due to absorption by oxygen and water vapor (Ellis and Vivekanandan 2010) and by cloud and precipitation particles (Hogan et al. 2005; Ellis and Vivekanandan 2011; Lhermitte 1987). Liquid cloud droplets, drizzle, rain, and wet ice particles strongly attenuate at the W band. For example the attenuation through liquid is over 4 dB km−1 (g m−3)−1 at W band and is only 0.005 dB km−1 (g m−3)−1 for S band [10-cm wavelength; used by the National Weather Service Weather Surveillance Radar-1988 Doppler (WSR-88D) network]. Wet ice particles such as melting aggregates can cause severe attenuation that is difficult to correct. Even dry aggregates can noticeably attenuate the W-band signal (Li et al. 2000; Matrosov and Battaglia 2009). Interestingly, simulations by Matrosov and Battaglia (2009) found that the snow attenuation was nearly canceled out by the effects of multiple scattering. Attenuation impacts Ze by reducing the values with range and complicating their interpretation. The Vr and SW are only affected if the attenuation results in low signal-to-noise ratio (SNR) or reduction of the signal below the detection limit. Low SNR leads to increased measurement variance of Vr and SW.

Another complication using the Ze measurements at W band is the fact that precipitation-sized particles violate the Rayleigh scattering assumption. These non-Rayleigh effects mean that the Ze values of particles of particular sizes are not unique, making quantitative interpretation of Ze difficult.

The movement of the radar during flight impacts the Doppler measurements and requires correction of the measured Vr for platform motion. To measure the motion of the pod, which commonly differs from the fuselage, the HCR has its own inertial navigation system (INS) located just fore of the reflector. Correcting the radar pointing angle for platform motion is critical to obtain accurate Vr measurements. For the staring mode, the HCR has real-time stabilization that updates the reflector position during flight at a rate of 20 Hz, keeping the beam very near the desired pointing angle. The stabilization of the reflector is accomplished by using the INS data to directly control the reflector’s scanning motors to compensate for the pod motion. The result is that the desired pointing angle is maintained during flight to within about 0.1°. This is particularly important for vertical measurements (nadir or zenith) to reduce Vr errors caused by horizontal winds at nonflight levels being projected into the radial direction of off-nadir (zenith) beams (Vivekanandan et al. 2015). For example, at an off-nadir pointing offset of 0.1°, a 30 m s−1 horizontal wind will result in a maximum of 0.05 m s−1 radial velocity error. Without stabilization, these errors can be large and are correctable only if the vertical profile of the horizontal wind is known accurately, which is typically not possible. For example, a 2° off-nadir offset could result in radial velocity errors over 1 m s−1, with a 30 m s−1 horizontal wind. The final data are also corrected using the measured pointing angles and navigation data following Lee et al. (1994) to correct for any residual pointing angle offsets that can result even with the reflector stabilization. The Vr can be measured within about ±0.1 m s−1 (Vivekanandan et al. 2015). The specifications, design, and capabilities of the HCR are described in more detail in Vivekanandan et al. (2015). It should be noted that at vertical incidence, such as during the Nor’easter flight, the corrected Vr is a measurement of the combined vertical wind and particle fall speed. Estimates of either one of those quantities alone cannot be done without assumptions about the other.

Another impact of the motion of the radar platform is spectral broadening due to the finite radar beamwidth (Nathanson 1969; Chu 2002). At the air speeds achieved during the Nor’easter flight, the spectral broadening varied from about 0.6 to 0.8 m s−1. This is evidenced in the SW measured at the ocean or land surface. This results in the measured SW having higher values than what resulted from turbulence, shear, and differential fall speed of hydrometeors alone.

Finally, there are complications interpreting vertically pointing radar data. The data are two-dimensional “curtains” through a three-dimensional field and the shapes of features may be difficult to correctly interpret. Horizontal advection, or wind drift, of the observed particles across the curtain means that their source or destination region will not be observed by HCR (Mittermaier et al. 2004; Szyrmer and Zawadzki 2014; Oue et al. 2015).

HCR during the Nor’easter flight.

For the 2 February flight, the HCR was configured with the beam pointed at nadir, while the GV was flying at 12,800 m (42,000 ft). The sensitivity achievable at 1-km range was –43 dBZ. Despite the strong attenuation in wet snow and rain, Earth’s surface was always detected, and radial velocities were recovered through the depth of the storm throughout the flight.

THE 2 FEBRUARY 2015 NORTHEAST SNOWSTORM.

Extratropical cyclones along the U.S. East Coast typically either develop directly along the eastern seaboard and move northeastward or form when a preexisting cyclone moving toward the East Coast from the central United States undergoes secondary development (Kocin and Uccellini 2004). The cyclone sampled during the GV flight was the latter type. The storm initially developed over central Kansas at 0600 UTC 1 February 2015. The center of the cyclone passed directly south of Chicago at 2100 UTC 1 February, produced 49 cm (19.3 in.) of snow at O’Hare International Airport (the fifth largest snowfall event in the airport’s history), and reached western Pennsylvania by 1200 UTC 2 February. Secondary development of low pressure along the East Coast began between 1200 and 1500 UTC 2 February. Figure 2 shows a radar composite, frontal positions, and the sea level pressure field at 1500 UTC over the Northeast United States at the time when secondary development was underway. The surface low pressure center intensified 10 hPa between 1500 UTC 2 February and 0000 UTC 3 February as the cyclone moved out over the Atlantic south of the New England coastline, a deepening rate of approximately 1.1 hPa h−1. The cyclone produced heavy snowfall across New England and the Great Lakes region during its approach toward the East Coast and intensification period over the western Atlantic (Fig. 3). The heaviest snow occurred in Vermont and New Hampshire, where as much as 61 cm (24 in.) fell. Boston recorded 41 cm (16 in.) during the storm. The storm alone contributed about 15% of the record 2.81 m (110.6 in.) of snow officially recorded in Boston during the 2014/15 winter.

Fig. 2.
Fig. 2.

Composite radar analysis of the 2 Feb 2015 cyclone at 1500 UTC. The thin white lines are sea level pressure (hPa), the dashed yellow line is the 0°C surface isotherm, and the solid yellow line is the flight track of the GV aircraft. The red line denotes the track of the low pressure center during the flight, with positions and minimum sea level pressures noted at 1800 and 2100 UTC 2 Feb, and 0000 UTC 3 Feb.

Citation: Bulletin of the American Meteorological Society 98, 2; 10.1175/BAMS-D-15-00180.1

Fig. 3.
Fig. 3.

Total snowfall distribution (in.) associated with the 2 Feb 2015 storm [image (with changes) courtesy of www.weather.com, used with permission].

Citation: Bulletin of the American Meteorological Society 98, 2; 10.1175/BAMS-D-15-00180.1

Based on forecasts, the decision was made to ferry the GV from its base in Boulder, Colorado, to Raleigh, North Carolina, on 31 January. The research flight commenced from Raleigh at 1247 UTC, arriving at the first waypoint over the northern tip of Delaware Bay at an altitude of 12,800 m (42,000 ft) at 1326 UTC. This altitude was chosen so that the aircraft would be in the stratosphere above the storm to minimize turbulence and also be above commercial air traffic, which was expected to be congested with the snowstorm complicating departures and arrivals at the major airports on the East Coast. From this first waypoint over Delaware, the aircraft flew in a straight-line path (Fig. 2) to Bangor, Maine, the second waypoint, arriving at 1418 UTC. The GV flew five additional legs between the two waypoints, completing the last leg at 1940 UTC, before returning to Raleigh. Each leg of the flight crossed the rain–snow line. The position of the rain–snow line, estimated from surface reports, migrated northward during the flight, due both to the northeastward movement of the cyclone and changes in insolation from the morning to early afternoon.

MESOSCALE STRUCTURES OBSERVED BY THE HCR.

The aircraft flew six 840-km-long straight legs back and forth between northern Delaware and Bangor, Maine, during the storm. The HCR data shown herein are from one leg flown between 1418 and 1533 UTC. Figures 4a and 4b show cross sections of equivalent potential temperature along that flight leg. The cross sections were developed from a simulation of the storm with the Weather Research and Forecasting (WRF) Model1 and are 9-h forecasts valid at the center time of the cross sections. A short-term forecast was used, rather than an analysis, so that features such as the unstable boundary layer over the Atlantic between 520 and 780 km would have time to fully develop. Superimposed on Fig. 4a is the wind component normal to the cross section, with hot (cold) colors denoting flow into (out of) the cross section. Figure 4b shows the parallel wind component with hot colors denoting flow from right to left and cold colors the opposite direction. On these cross sections, a warm front slopes upward from the surface over Delaware to 4 km over Bangor. The 0°C isotherm folds southward along the frontal surface over a distance of 160 km. Within this folded region, ice pellets and/or freezing rain were possible. Strong wind shear occurred across the frontal zone. Two areas of conditional instability were present aloft: one at 4.0–6.0-km altitude between x = 120 and 260 km and the second at 3.7–4.8-km altitude between x = 410 and 500 km. The dendritic growth layer, indicated by the –16°C contour, was between 5.0 and 4.2 km, slowly sloping downward toward the colder air. The HCR cross sections that follow are at the locations of the vertical gray bars and will be presented as progressing from the cold to the warm side of the storm (Fig. 4). The height of the gray bars corresponds to the height of the HCR cross sections, all of which extend to just above the highest cloud top at their respective locations.

Fig. 4.
Fig. 4.

(a) Cross section along flight track between 1418 and 1533 UTC from the WRF simulation showing equivalent potential temperature (K, black lines) and wind component normal to cross section [m s−1, hot (cold) colors into (out of) cross section]. (b) As in (a), but for wind component parallel to cross section. Key temperatures (°C) are denoted with red lines. The GV flight track is denoted at the top of the cross section. Vertical gray bars denote the locations of HCR cross sections in Figs. 611.

Citation: Bulletin of the American Meteorological Society 98, 2; 10.1175/BAMS-D-15-00180.1

The HCR data in the figures that follow are displayed in vertical cross section for 1 min of flight, a distance of 12 km. The location of each cross section is shown on a 0.5° reflectivity scan from the nearest WSR-88D (Fig. 5). The cross sections each show Ze, Vr, SW, and LDR. The vertical radial velocity Vr includes the vertical air motion plus the reflectivity-weighted terminal velocity of the ensemble of particles within the pulse volume. For the purpose of interpretation, a rough estimate of the terminal velocity of the larger ice particles, which contribute most to the reflectivity, is about 1 m s−1, while a rough estimate of the terminal fall speed of raindrops below the brightband is about 4 m s−1. Positive radial velocities on the figures denote particle motion away from the radar (downward).

Fig. 5.
Fig. 5.

WSR-88D 0.5° scans showing the radar reflectivity factor from (a) Bangor (KGYX) at 1434 UTC; (b) Boston (KBOX) at 1448 UTC; (c) Upton, NY (KOKX), at 1457 UTC; (d) KOKX at 1503 UTC, (e) Mount Holly, NJ (KDIX), at 1515 UTC; and (f) KDIX at 1529 UTC 2 Feb 2015. Locations of cross sections in Figs. 611 are shown in the small circles in (a)–(f), respectively.

Citation: Bulletin of the American Meteorological Society 98, 2; 10.1175/BAMS-D-15-00180.1

Figure 6 shows HCR data collected at 1434 UTC, well north of the rain–snow line. The data were collected over the ocean (Fig. 5a) at a location where the top of the frontal zone was located at 3 km (Fig. 4), and the clouds extended to 8.5-km altitude. The cloud top was characterized by undulations in the reflectivity field and organized fluctuations in the vertical radial velocity field characteristic of wave motions. The waves extended over a depth of 2.5 km. The ice particles at cloud top would have smaller terminal velocities, so the vertical radial velocities at the cloud top in this figure are closer to actual values of vertical air motion. The vertical oscillations within the waves are on the order of 2 m s−1. The remaining cloud was stratiform. However, a shallow turbulent layer was present at 3 km, indicated by finescale fluctuations in the Vr field and a band of high values of SW. This layer occurred along the frontal boundary and was likely associated with wind shear across the front (Fig. 4). Organized circulations were also present in the unstable boundary layer over the Atlantic extending upward to the base of the stable layer at 1.3-km altitude. The LDR signal was near the noise level, suggesting that particles were dry, low-density aggregate snowflakes.

Fig. 6.
Fig. 6.

(a) Equivalent radar reflectivity factor, (b) vertical radial velocity, (c) spectral width, and (d) linear depolarization ratio measured by the HCR during a 1-min period beginning at 1434 UTC 2 Feb 2015. The location of the cross section is indicated on Figs. 4 and 5.

Citation: Bulletin of the American Meteorological Society 98, 2; 10.1175/BAMS-D-15-00180.1

Contrast these data with Fig. 7, which features data collected at 1448 UTC onshore over northeast Massachusetts (Fig. 5b). Again, these data were collected north of the rain–snow line. There were two cloud layers at this location: a 1-km-deep layer between 5- and 6-km altitude and a second layer extending from 4 km to the surface. The top of the upper layer is marked by small, cellular features, with a plume of ice particles descending to the lower layer on the right side of the cross section near t = 55 s. The most remarkable features of this cross section, however, are the apparent waves present between 0.5- and 3.0-km altitude. Accounting for terminal fall velocities of snow, the vertical velocity oscillations are on the order of 2 m s−1 within the waves. The wave structure is also apparent in the Ze and SW fields. There is a general increase in Ze at the mean level of the waves near 1.5 km. This level is also marked by high values of SW, indicating a spread in total particle fall velocity and/or an increase in turbulence. The layer where these waves were occurring encompassed the warm frontal zone (Fig. 4). An increase in LDR occurred near the base of the waves at 1 km. Above this layer, LDR was below the noise level, again suggesting dry, low-density aggregate snowflakes. The increase in Ze and LDR below ∼1 km suggests an evolution in particle habit, although what these changes might be is speculative.

Fig. 7.
Fig. 7.

As in Fig. 6, but for a 1-min period beginning at 1448 UTC 2 Feb 2015.

Citation: Bulletin of the American Meteorological Society 98, 2; 10.1175/BAMS-D-15-00180.1

The data in Fig. 8 were collected at 1457 UTC over northeast Connecticut, about 100 km southwest of the previous location (Figs. 4, 5c). The clouds at this location were 7 km deep. The cloud top was characterized by narrow updrafts and downdrafts, some exceeding 2 m s−1. The billowed reflectivity pattern, together with the lack of fall streaks emanating from the updrafts, suggests that shear near cloud top was mixing particles within the cloud-top layer. A layer of higher Ze was present between 4 and 5 km. This layer corresponds to dendritic growth zone temperatures (–16° to –13°C). Enhancements of reflectivity in this zone and toward the ground have been noted at S and X band (Kennedy and Rutledge 2011; Ryzhkov et al. 2016; Schrom and Kumjian 2016). An increase in LDR was observed within and below this zone. Since updrafts were negligible at these altitudes, particles within this zone would likely be dry. The increase in LDR may indicate that particles within this layer were nonspherical and wobbling in and out of the plane of polarization as they fell. The location of this cross section was near the northern limit of the 0°C isotherm aloft (Fig. 4). Periodic enhancements in LDR at 1.2 km and “LDR fall streaks” below 1.2 km, together with increases in Vr in some regions below 1.2 km, were characteristic of a rain–snow mix of precipitation.

Fig. 8.
Fig. 8.

As in Fig. 6, but for a 1-min period beginning at 1457 UTC 2 Feb 2015.

Citation: Bulletin of the American Meteorological Society 98, 2; 10.1175/BAMS-D-15-00180.1

Figure 9 shows the data from 1 min of flight beginning at 1503 UTC over southern Connecticut (Figs. 4, 5d). Cloud-top generating cells were ubiquitous in this region. Vertical air velocities at the tops of these cells (accounting for ice particle terminal velocities) were on the order of 1–2 m s−1, consistent with past measurements (e.g., Rosenow et al. 2014; Kumjian et al. 2014). The reflectivity plumes descending from these cells are marked by larger downward radial velocity, suggesting that the particles produced by these cells are larger and have greater terminal velocities. The plumes also appear in the SW field, suggesting that the ice particles within the plumes have a broader range of terminal velocities than outside the plumes. Enhanced turbulence within the plumes could also contribute to the elevated SW. The reduced sensitivity and coverage of LDR is evident in Fig. 9d, where only the brightband was above the noise level. This suggests that dry aggregates were present above and spherical raindrops were below the melting level. Note the small region of upward radial velocities present at 2.5 km at t = 20 s from the left side of the cross section. This feature is coincident with a wave on the bright band indicated by the wavelike oscillation and enhancement of the LDR field below the feature. The upward motion in the cross section is fairly smooth in the Doppler velocity field, suggesting a coherent structure. Further, the spectral width here is rather low, suggesting a lack of significant turbulence or variability in fall speeds. Below the melting layer, the larger Ze, larger fall speeds, and enhanced spectrum width are all consistent with heavier rainfall with larger drops present. The LDR rising above the noise below the bright band in this region is consistent with larger, and potential wobblier, raindrops.

Fig. 9.
Fig. 9.

As in Fig. 6, but for a 1-min period beginning at 1503 UTC 2 Feb 2015.

Citation: Bulletin of the American Meteorological Society 98, 2; 10.1175/BAMS-D-15-00180.1

Figure 10 shows a cross section at 1515 UTC, coinciding with the area of conditional instability between 4 and 6 km near x = 210 km on Fig. 4. This location was marked by wavelike oscillations in Vr extending over a depth of 4 km. Accounting for the fall velocity of the ice particles, the vertical velocities in the updrafts and downdrafts were on the order of 3–5 m s−1. Substantial variability in SW was present in the lower half of the wave layer between 5 and 6 km. Fall streaks emanated from the base of the wave layer and merged above the bright band. The fall streaks were marked by an increase in LDR. Based on the Ze and Vr fields, uniform rain fell below the bright band, where attenuation of the W-band signal was clearly visible.

Fig. 10.
Fig. 10.

As in Fig. 6, but for a 1-min period beginning at 1515 UTC 2 Feb 2015.

Citation: Bulletin of the American Meteorological Society 98, 2; 10.1175/BAMS-D-15-00180.1

The final example (Fig. 11) was collected south of the rain–snow line at the surface warm front along the Pennsylvania–New Jersey border just northeast of Delaware. This location was near the cyclone dry slot boundary (Fig. 5f). The clouds at this location were layered. An apparent cirrus layer was located at 6-km altitude. This layer was cellular, with upward vertical velocities approaching 1.0–1.5 m s−1 in the cells and small plumes of ice particles descending from the cells. For the most part, these particles sublimated into the drier air below as they fell, but some near t = 45 s survived to enter the second layer. Particles in the second layer between 3 and 4.5 km exhibit a range of vertical radial velocities. It is unclear if this represents differences in terminal velocities of particles or differences in vertical air motion within the layer. The lowest layer contains weak generating cells at its top near 3 km. Plumes of ice particles can be seen descending toward the melting layer, where they lose their identity. The melting layer is clear in the LDR signal. Otherwise, the LDR signal was below noise level, suggesting dry, low-density snowflakes above and spherical raindrops below the melting level. The rain intensity, based on the horizontal distribution of reflectivity, varied over short distances across this region.

Fig. 11.
Fig. 11.

As in Fig. 6, but for a 1-min period beginning at 1529 UTC 2 Feb 2015.

Citation: Bulletin of the American Meteorological Society 98, 2; 10.1175/BAMS-D-15-00180.1

SUMMARY.

This paper presented examples of the finescale structural features present within a major Northeast United States snowstorm as viewed with the new HIAPER Cloud Radar aboard the NCAR GV aircraft. The HCR provided high-quality, high-resolution, dual-polarimetric Doppler radar data with beam-pointing angle stabilization throughout the flight. The data presented in this paper represent only 6 min of flight time. Overall, the GV collected data with the HCR for more than 6 h. In overviewing the entire dataset, we found the structural variability to be significant minute by minute along the flight path. The cross sections shown in the previous sections are by no means unusual or unique within this dataset. Within the full dataset, we found evidence for elevated convection, cloud-top generating cells, wave motions (in the boundary layer, at cloud midlevels, and at cloud top), boundary layer circulations, and complex circulations across the melting level. Although some regions of the flight did appear stratiform, even within those regions there were often layers of turbulence and or zones where local fluctuations in vertical radial velocity occurred on the order of 1–2 m s−1.

Boucher et al. (1965), when reporting the first vertically pointing Doppler radar measurements in winter storms over the Northeast United States, noted surprising finescale structure in both the horizontal and vertical winds in what they thought was stratiform precipitation. The observations from the HCR add clarity as to the nature of the structural features first observed by Boucher et al. but raise many questions about the forcing for these finescale circulations and their impact on the distribution of precipitation. Determining the forcing for these features requires additional analyses beyond the scope of this paper. More detailed analyses of these mesoscale features as well as modeling studies are underway, and results will be reported in future articles.

ACKNOWLEDGMENTS.

The authors thank the staff at the National Center for Atmospheric Research Earth Observing Laboratory, particularly the Remote Sensing Facility and the Research Aviation Facility staff for their efforts with the GV aircraft. We also thank Dr. Matt Kumjian and two anonymous reviewers for their comments, which helped improve this paper. The composite radar analyses appearing in Fig. 2 were provided by the Iowa Environmental Mesonet maintained by the Iowa State University Department of Agronomy. This work was funded under National Science Foundation Grant AGS-1247404 to the University of Illinois. The authors thank the NSF for making the GV and HCR available for this target of opportunity in support of the PLOWS research program.

REFERENCES

  • Boucher, R. J., R. Wexler, D. Atlas, and R. M. Lhermitte, 1965: Mesoscale wind structure revealed by Doppler radar. J. Appl. Meteor., 4, 590597, doi:10.1175/1520-0450(1965)004<0590:MWSRBD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Browne, I. C., 1952: Precipitation streaks as a cause of radar upper bands. Quart. J. Roy. Meteor. Soc., 78, 590595, doi:10.1002/qj.49707833809.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, F., and J. Dudhia, 2001: Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569585, doi:10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chu, Y., 2002: Beam broadening effect on oblique MST radar Doppler spectrum. J. Atmos. Oceanic Technol., 19, 19551967, doi:10.1175/1520-0426(2002)019<1955:BBEOOM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Colle, B. A., D. Stark, and S. E. Yuter, 2014: Surface microphysical observations within East Coast winter storms on Long Island, New York. Mon. Wea. Rev., 142, 31263146, doi:10.1175/MWR-D-14-00035.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Douglas, R. H., K. L. S. Gunn, and J. S. Marshall, 1957: Pattern in the vertical of snow generation. J. Meteor., 14, 95114, doi:10.1175/1520-0469(1957)014<0095:PITVOS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doviak, R. J., and D. S. Zrnić, 1993: Doppler Radar and Weather Observations. 2nd ed. Academic Press, 562 pp.

  • Ellis, S. M., and J. Vivekanandan, 2010: Water vapor estimates using simultaneous dual-wavelength radar observations. Radio Sci., 45, RS5002, doi:10.1029/2009RS004280.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ellis, S. M., and J. Vivekanandan, 2011: Liquid water content estimates using simultaneous S and Ka band radar measurements. Radio Sci., 46, RS2021, doi:10.1029/2010RS004361.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1988: Observational evidence of slantwise convective adjustment. Mon. Wea. Rev., 116, 18051816, doi:10.1175/1520-0493(1988)116<1805:OEOSCA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ganetis, S. A., and B. A. Colle, 2015: The thermodynamic and microphysical evolution of an intense snowband during the Northeast U.S. blizzard of 8–9 February 2013. Mon. Wea. Rev., 143, 41044125, doi:10.1175/MWR-D-14-00407.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Geerts, B., and P. V. Hobbs, 1991: Organization and structure of clouds and precipitation on the mid-Atlantic coast of the United States. Part IV: Retrieval of the thermodynamic and microphysical structures of a frontal rainband from Doppler radar data. J. Atmos. Sci., 48, 12871305, doi:10.1175/1520-0469(1991)048<1287:OASOCA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffin, E. M., T. J. Schuur, A. V. Ryzhkov, H. D. Reeves, and J. C. Picca, 2014: A polarimetric and microphysical investigation of the Northeast blizzard of 8–9 February 2013. Wea. Forecasting, 29, 12711294, doi:10.1175/WAF-D-14-00056.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gunn, K. L. S., M. P. Langleben, A. S. Dennis, and B. A. Power, 1954: Radar evidence of a generating level for snow. J. Meteor., 11, 2026, doi:10.1175/1520-0469(1954)011<0020:REOAGL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gunn, R. E. S., and J. S. Marshall, 1955: The effect of wind shear on falling precipitation. J. Meteor., 12, 339349, doi:10.1175/1520-0469(1955)012<0339:TEOWSO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Herzegh, P. H., and P. V. Hobbs, 1980: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. II: Warm-frontal clouds. J. Atmos. Sci., 37, 597611, doi:10.1175/1520-0469(1980)037<0597:TMAMSA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hobbs, P. V., and J. D. Locatelli, 1978: Rainbands, precipitation cores and generating cells in a cyclonic storm. J. Atmos. Sci., 35, 230241, doi:10.1175/1520-0469(1978)035<0230:RPCAGC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., N. Gaussiat, and A. J. Illingworth, 2005: Stratocumulus liquid water content from dual-wavelength radar. J. Atmos. Oceanic Technol., 22, 12071218, doi:10.1175/JTECH1768.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341, doi:10.1175/MWR3199.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houze, R. A., Jr., S. A. Rutledge, T. J. Matejka, and P. V. Hobbs, 1981: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. III: Air motions and precipitation growth in a warm frontal rainband. J. Atmos. Sci., 38, 639649, doi:10.1175/1520-0469(1981)038<0639:TMAMSA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Iacono, M., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, doi:10.1029/2008JD009944.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiménez, P. A., J. Dudhia, J. F. González-Rouco, J. Navarro, J. P. Montávez, and E. García-Bustamante, 2012: A revised scheme for the WRF surface layer formulation. Mon. Wea. Rev., 140, 898918, doi:10.1175/MWR-D-11-00056.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jurewicz, M. L., Sr., and M. S. Evans, 2004: A comparison of two banded, heavy snowstorms with very different synoptic settings. Wea. Forecasting, 19, 10111028, doi:10.1175/WAF-823.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Keeler, J. M., B. F. Jewett, R. M. Rauber, G. M. McFarquhar, R. M. Rasmussen, L. Xue, C. Liu, and G. Thompson, 2016: Dynamics of cloud-top generating cells in winter cyclones. Part I: Idealized simulations in the context of field observations. J. Atmos. Sci., 73, 15071527, doi:10.1175/JAS-D-15-0126.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kennedy, P. C., and S. A. Rutledge, 2011: S-band dual-polarization radar observations of winter storms. J. Appl. Meteor. Climatol., 50, 844858, doi:10.1175/2010JAMC2558.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kocin, P. J., and L. W. Uccellini, 2004: Overview. Vol. 1, Northeast Snowstorms, Meteor. Monogr., No. 54, Amer. Meteor. Soc., 289 pp.

    • Crossref
    • Export Citation
  • Kreitzberg, C. W., and H. A. Brown, 1970: Mesoscale weather systems within an occlusion. J. Appl. Meteor., 9, 417432, doi:10.1175/1520-0450(1970)009<0417:MWSWAO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumjian, M. R., S. Rutledge, R. Rasmussen, P. Kennedy, and M. Dixon, 2014: High-resolution polarimetric radar observations of snow-generating cells. J. Appl. Meteor. Climatol., 53, 16361658, doi:10.1175/JAMC-D-13-0312.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Langleben, M. P., 1956: The plan pattern of snow echoes at the generating level. J. Meteor., 13, 554560, doi:10.1175/1520-0469(1956)013<0554:TPPOSE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, W. C., P. Dodge, F. D. Marks, and P. H. Hildebrand, 1994: Mapping of airborne Doppler radar data. J. Atmos. Oceanic Technol., 11, 572578, doi:10.1175/1520-0426(1994)011<0572:MOADRD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lhermitte, R., 1987: A 94-GHz Doppler radar for cloud observations. J. Atmos. Oceanic Technol., 4, 3648, doi:10.1175/1520-0426(1987)004<0036:AGDRFC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, L., and Coauthors, 2000: Ice cloud extinction retrieval using ground-based and airborne millimeter-wave cloud radar measurements. Proc. 10th ARM Science Team Meeting, San Antonio, TX, Atmospheric Radiation Measurement Program, 1–6. [Available online at www.arm.gov/publications/proceedings/conf10/extended_abs/li_l.pdf.]

  • Marshall, J. S., 1953: Precipitation trajectories and patterns. J. Meteor., 10, 2529, doi:10.1175/1520-0469(1953)010<0025:PTAP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, D., R. F. Reinking, R. A. Kropfli, B. E. Martner, and B. W. Bartram, 2001: On the use of radar depolarization ratios for estimating shapes of ice hydrometeors in winter clouds. J. Appl. Meteor., 40, 479490, doi:10.1175/1520-0450(2001)040<0479:OTUORD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., and A. Battaglia, 2009: Influence of multiple scattering on CloudSat measurements in snow: A model study. Geophys. Res. Lett., 36, L12806, doi:10.1029/2009GL038704.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mittermaier, M. P., R. J. Hogan, and A. J. Illingworth, 2004: Using mesoscale model winds for correcting wind-drift errors in radar estimates of surface rainfall. Quart. J. Roy. Meteor. Soc., 130, 21052123, doi:10.1256/qj.03.156.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nathanson, F., 1969: Radar Design Principles. McGraw-Hill, 626 pp.

  • Novak, D. R., L. F. Bosart, D. Keyser, and J. S. Waldstreicher, 2004: An observational study of cold season-banded precipitation in Northeast U.S. cyclones. Wea. Forecasting, 19, 9931010, doi:10.1175/815.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Novak, D. R., L. F. Bosart, and S. E. Yuter, 2008: High-resolution observations and model simulations of the life cycle of an intense mesoscale snowband over the northeastern United States. Mon. Wea. Rev., 136, 14331456, doi:10.1175/2007MWR2233.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Novak, D. R., L. F. Bosart, and A. R. Aiyyer, 2010: Evolution of mesoscale precipitation band environments within the comma head of Northeast U.S. cyclones. Mon. Wea. Rev., 138, 23542374, doi:10.1175/2010MWR3219.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oue, M., M. Kumjian, Y. Lu, J. Verlinde, K. Aydin, and E. E. Clothiaux, 2015: Linear depolarization ratios of columnar ice crystals in a deep precipitating system over the Arctic observed by zenith-pointing Ka-band Doppler radar. J. Appl. Meteor. Climatol., 54, 10601068, doi:10.1175/JAMC-D-15-0012.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Picca, J. C., D. M. Schultz, B. A. Colle, S. Ganetis, D. R. Novak, and M. J. Sienkiewicz, 2014: The value of dual-polarization radar in diagnosing the complex microphysical evolution of an intense snowband. Bull. Amer. Meteor. Soc., 95, 18251834, doi:10.1175/BAMS-D-13-00258.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Plank, V. G., D. Atlas, and W. H. Paulsen, 1955: The nature and detectability of clouds and precipitation as determined by 1.25-centimeter radar. J. Meteor., 12, 358378, doi:10.1175/1520-0469(1955)012<0358:TNADOC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Plummer, D. M., G. M. McFarquhar, R. M. Rauber, B. F. Jewett, and D. C. Leon, 2014: Structure and statistical analysis of the microphysical properties of generating cells in the comma head region of continental winter cyclones. J. Atmos. Sci., 71, 41814203, doi:10.1175/JAS-D-14-0100.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Plummer, D. M., G. M. McFarquhar, R. M. Rauber, B. F. Jewett, and D. C. Leon, 2015: Microphysical properties of convectively generated fall streaks in the comma-head region of continental winter cyclones. J. Atmos. Sci., 72, 24652483, doi:10.1175/JAS-D-14-0354.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rauber, R. M., and Coauthors, 2014a: Stability and charging characteristics of the comma head region of continental winter cyclones. J. Atmos. Sci., 71, 15591582, doi:10.1175/JAS-D-13-0253.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rauber, R. M., M. K. Macomber, D. M. Plummer, A. A. Rosenow, G. M. McFarquhar, B. F. Jewett, D. Leon, and J. M. Keeler, 2014b: Finescale radar and airmass structure of the comma head of a continental winter cyclone: The role of three airstreams. Mon. Wea. Rev., 142, 42074229, doi:10.1175/MWR-D-14-00057.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rauber, R. M., and Coauthors, 2015: The role of cloud-top generating cells and boundary-layer circulations in the finescale radar structure of a winter cyclone over the Great Lakes. Mon. Wea. Rev., 143, 22912318, doi:10.1175/MWR-D-14-00350.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reinking, R. F., S. Y. Matrosov, L. Kropfli, and B. W. Bartram, 2002: Evaluation of a slant quasi-linear radar polarization state for distinguishing drizzle droplets, pristine ice crystals, and less regular ice particles. J. Atmos. Oceanic Technol., 19, 296321, doi:10.1175/1520-0426-19.3.296.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reuter, G. W., and M. K. Yau, 1990: Observations of slantwise convective instability in winter cyclones. Mon. Wea. Rev., 118, 447458, doi:10.1175/1520-0493(1990)118<0447:OOSCII>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rosenow, A. A., D. M. Plummer, R. M. Rauber, G. M. McFarquhar, B. F. Jewett, and D. Leon, 2014: Vertical velocity and physical structure of generating cells and convection in the comma head region of continental winter cyclones. J. Atmos. Sci., 71, 15381558, doi:10.1175/JAS-D-13-0249.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A., P. Zhang, H. Reeves, M. Kumjian, T. Schallener, S. Trömel, and C. Simmer, 2016: Quasi-vertical profiles—A new way to look at polarimetric radar data. J. Atmos. Oceanic Technol., 33, 551562, doi:10.1175/JTECH-D-15-0020.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sanders, F., 1986: Frontogenesis and symmetric stability in a major New England snowstorm. Mon. Wea. Rev., 114, 18471862, doi:10.1175/1520-0493(1986)114<1847:FASSIA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sanders, F., and L. F. Bosart, 1985: Mesoscale structure in the megalopolitan snowstorm, 11–12 February 1983. Part II: Doppler radar study of the New England snowband. J. Atmos. Sci., 42, 13981407, doi:10.1175/1520-0469(1985)042<1398:MSITMS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schrom, R. S., and M. R. Kumjian, 2016: Connecting microphysical processes in Colorado winter storms with vertical profiles of radar observations. J. Appl. Meteor. Climatol., 55, 17711787, doi:10.1175/JAMC-D-15-0338.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seltzer, M. A., R. E. Passarelli, and K. A. Emanuel, 1985: The possible role of symmetric instability in the formation of precipitation bands. J. Atmos. Sci., 42, 22072219, doi:10.1175/1520-0469(1985)042<2207:TPROSI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stark, D., B. A. Colle, and S. E. Yuter, 2013: Observed microphysical evolution for two East Coast winter storms and the associated snow bands. Mon. Wea. Rev., 141, 20372057, doi:10.1175/MWR-D-12-00276.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Syrett, W. J., B. A. Albrecht, and E. E. Clothiaux, 1995: Vertical cloud structure in a midlatitude cyclone from a 94-GHz radar. Mon. Wea. Rev., 123, 33933407, doi:10.1175/1520-0493(1995)123<3393:VCSIAM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Szyrmer, W., and I. Zawadzki, 2014: Snow studies. Part IV: Ensemble retrieval of snow microphysics from dual-wavelength vertically pointing radars. J. Atmos. Sci., 71, 11581170, doi:10.1175/JAS-D-12-0285.1.

    • Crossref
    • 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, 50955115, doi:10.1175/2008MWR2387.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • UCAR/NCAR, 2014: HIAPER cloud radar (HCR). Earth Observing Laboratory, 2014-present, accessed 15 March 2016, doi:10.5065/D6BP00TP.

    • Crossref
    • Export Citation
  • UCAR/NCAR, 2015: HIAPER Gulfstream GV. Earth Observing Laboratory, 2005-present, accessed 15 March 2016, doi:10.5065/D6DR2SJP.

    • Crossref
    • Export Citation
  • Vivekanandan, J., D. S. Zrnić, S. M. Ellis, R. Oye, 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
  • Vivekanandan, J., and Coauthors, 2015: A wing pod-based millimeter wavelength airborne cloud radar. Geosci. Instrum. Methods Data Syst., 4, 161176, doi:10.5194/gi-4-161-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wexler, R., 1955: Radar analysis of precipitation streamers observed 25 February 1954. J. Atmos. Sci., 12, 391393, doi:10.1175/1520-0469(1955)012<0391:RAOPSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wexler, R., and D. Atlas, 1959: Precipitation generating cells. J. Meteor., 16, 327332, doi:10.1175/1520-0469(1959)016<0327:PGC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wexler, R., A. C. Chmela, and G. M. Armstrong, 1967: Wind field observations by Doppler radar in a New England snowstorm. Mon. Wea. Rev., 95, 929935, doi:10.1175/1520-0493(1967)095<0929:WFOBDR>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wolfsberg, D. G., K. A. Emanuel, and R. E. Passarelli, 1986: Band formation in a New England winter storm. Mon. Wea. Rev., 114, 15521569, doi:10.1175/1520-0493(1986)114<1552:BFIANE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
1

The WRF Model simulation initial and boundary condition grids were taken from the National Centers for Environmental Prediction–North American Mesoscale Forecast System (run from 0600 UTC 2 February). One 9-km domain was employed, with 90 vertical levels. Treatment of physical processes used the following parameterizations: surface layer based on Monin–Obukhov similarity theory (Jiménez et al. 2012); Unified Noah land surface scheme (Chen and Dudhia 2001); Yonsei University (YSU; Hong et al. 2006) planetary boundary layer; Rapid Radiative Transfer Model for GCMs (RRTMG) shortwave and longwave radiation (Iacono et al. 2008); and Thompson microphysics (Thompson et al. 2008).

Save