• Agee, E. M., and M. L. Hart, 1990: Boundary layer and mesoscale structure over Lake Michigan during a wintertime cold air outbreak. J. Atmos. Sci., 47, 22932316, https://doi.org/10.1175/1520-0469(1990)047<2293:BLAMSO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Angel, J. R., and S. A. Isard, 1998: The frequency and intensity of Great Lake cyclones. J. Climate, 11, 6171, https://doi.org/10.1175/1520-0442(1998)011<0061:TFAIOG>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bailey, M. P., and J. Hallett, 2009: A comprehensive habit diagram for atmospheric ice crystals: Confirmation from the laboratory, AIRS II, and other field studies. J. Atmos. Sci., 66, 28882899, https://doi.org/10.1175/2009JAS2883.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ballentine, R. J., A. J. Stamm, E. E. Chermack, G. P. Byrd, and D. Schleede, 1998: Mesoscale model simulation of the 4–5 January 1995 lake-effect snowstorm. Wea. Forecasting, 13, 893920, https://doi.org/10.1175/1520-0434(1998)013<0893:MMSOTJ>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bard, L., and D. A. R. Kristovich, 2012: Trend reversal in Lake Michigan contribution to snowfall. J. Appl. Meteor. Climatol., 51, 20382046, https://doi.org/10.1175/JAMC-D-12-064.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barthold, F. E., and D. A. R. Kristovich, 2011: Observations of the crosslake cloud and snow evolution in a lake-effect snow event. Mon. Wea. Rev., 139, 23862398, https://doi.org/10.1175/MWR-D-10-05001.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Battaglia, A., E. Rustemeier, A. Tokay, U. Blahak, and C. Simmer, 2010: PARSIVEL snow observations: A critical assessment. J. Atmos. Oceanic Technol., 27, 333344, https://doi.org/10.1175/2009JTECHA1332.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baxter, M. A., C. E. Graves, and J. T. Moore, 2005: A climatology of snow-to-liquid ratio for the contiguous United States. Wea. Forecasting, 20, 729744, https://doi.org/10.1175/WAF856.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blanken, P. D., C. Spence, N. Hedstrom, and J. D. Lenters, 2011: Evaporation from Lake Superior: 1. Physical controls and processes. J. Great Lakes Res., 37, 707716, https://doi.org/10.1016/j.jglr.2011.08.009.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Braham, R. R., and M. J. Dungey, 1984: Quantitative estimates of the effect of Lake Michigan on snowfall. J. Climate Appl. Meteor., 23, 940949, https://doi.org/10.1175/1520-0450(1984)023<0940:QEOTEO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Braham, R. R., and M. J. Dungey, 1995: Lake-effect snowfall over Lake Michigan. J. Appl. Meteor. Climatol., 34, 10091019, https://doi.org/10.1175/1520-0450(1995)034<1009:LESOLM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brandes, E. A., K. Ikeda, G. Zhang, M. Schönhuber, and R. M. Rasmussen, 2007: A statistical and physical description of hydrometeor distributions in Colorado snowstorms using a video disdrometer. J. Appl. Meteor. Climatol., 46, 634650, https://doi.org/10.1175/JAM2489.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Burnett, A. W., M. E. Kirby, H. T. Mullins, and W. P. Patterson, 2003: Increasing Great Lake–effect snowfall during the twentieth century: A regional response to global warming? J. Climate, 16, 35353542, https://doi.org/10.1175/1520-0442(2003)016<3535:IGLSDT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Campbell, L. S., and W. J. Steenburgh, 2017: The OWLeS IOP2b lake-effect snowstorm: Mechanisms contributing to the Tug Hill precipitation maximum. Mon. Wea. Rev., 145, 24612478, https://doi.org/10.1175/MWR-D-16-0461.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Changnon, S. A., Jr., and D. M. A. Jones, 1972: Review of the influences of the Great Lakes on weather. Water Resour. Res., 8, 360371, https://doi.org/10.1029/WR008i002p00360.

    • 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, https://doi.org/10.1175/MWR-D-14-00035.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Conrick, R., H. D. Reeves, and S. Zhong, 2015: The dependence of QPF on the choice of boundary- and surface-layer parameterization for a lake-effect snowstorm. J. Appl. Meteor. Climatol., 54, 11771190, https://doi.org/10.1175/JAMC-D-14-0291.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cooper, S. J., N. B. Wood, and T. S. L’Ecuyer, 2017: A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations. Atmos. Meas. Tech., 10, 25572571, https://doi.org/10.5194/amt-10-2557-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Eichenlaub, V. L., 1970: Lake effect snowfall to the lee of the Great Lakes: Its role in Michigan. Bull. Amer. Meteor. Soc., 51, 403412, https://doi.org/10.1175/1520-0477(1970)051<0403:LESTTL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Field, P., A. Heymsfield, and A. Bansemer, 2007: Snow size distribution parameterization for midlatitude and tropical ice clouds. J. Atmos. Sci., 64, 43464365, https://doi.org/10.1175/2007JAS2344.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gorodetskaya, I. V., N. P. M. Van Lipzig, M. R. Van den Broeke, A. Mangold, W. Boot, and C. H. Reijmer, 2013: Meteorological regimes and accumulation patterns at Utsteinen, Dronning Maud Land, East Antarctica: Analysis of two contrasting years. J. Geophys. Res. Atmos., 118, 17001715, https://doi.org/10.1002/jgrd.50177.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grecu, M., W. S. Olson, S. J. Munchak, S. Ringerud, L. Liao, Z. Haddad, B. L. Kelley, and S. F. McLaughlin, 2016: The GPM combined algorithm. J. Atmos. Oceanic Technol., 33, 22252245, https://doi.org/10.1175/JTECH-D-16-0019.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hamada, A., and Y. N. Takayabu, 2016: Improvements in detection of light precipitation with the Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM DPR). J. Atmos. Oceanic Technol., 33, 653667, https://doi.org/10.1175/JTECH-D-15-0097.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Helmus, J. J., and S. M. Collis, 2016: The Python ARM Radar Toolkit (Py-ART), a library for working with weather radar data in the Python programming language. J. Open Res. Software, 4, e25, https://doi.org/10.5334/jors.119.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Henderson, D. S., C. D. Kummerow, D. A. Marks, and W. Berg, 2017: A regime-based evaluation of TRMM oceanic precipitation biases. J. Atmos. Oceanic Technol., 34, 26132635, https://doi.org/10.1175/JTECH-D-16-0244.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Henne, P. D., F. S. Hu, and D. T. Cleland, 2007: Lake-effect snow as the dominant control of mesic-forest distribution in Michigan, USA. J. Ecol., 95, 517529, https://doi.org/10.1111/j.1365-2745.2007.01220.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., P. Field, and A. Bansemer, 2008: Exponential size distributions for snow. J. Atmos. Sci., 65, 40174031, https://doi.org/10.1175/2008JAS2583.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., C. Schmitt, A. Bansemer, and C. H. Twohy, 2010: Improved representation of ice particle masses based on observations in natural clouds. J. Atmos. Sci., 67, 33033318, https://doi.org/10.1175/2010JAS3507.1.

    • Crossref
    • 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, https://doi.org/10.1175/2010JAMC2505.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holroyd, E. W., 1971: Lake-effect cloud bands as seen from weather satellites. J. Atmos. Sci., 28, 11651170, https://doi.org/10.1175/1520-0469(1971)028<1165:LECBAS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hou, A. Y., and et al. , 2014: The Global Precipitation Measurement Mission. Bull. Amer. Meteor. Soc., 95, 701722, https://doi.org/10.1175/BAMS-D-13-00164.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houze, R. A., Jr., and et al. , 2017: The Olympic Mountains Experiment (OLYMPEX). Bull. Amer. Meteor. Soc., 98, 21672188, https://doi.org/10.1175/BAMS-D-16-0182.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, G.-J., V. Bringi, D. Moisseev, W. 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 environment. Atmos. Res., 153, 3448, https://doi.org/10.1016/j.atmosres.2014.07.013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hudak, D., H. Barker, P. Rodriguez, and D. Donovan, 2006: The Canadian CloudSat validation project. Fourth European Conf. on Radar in Hydrology and Meteorology, Barcelona, Spain, ERAD, P11.6, www.crahi.upc.edu/ERAD2006/proceedingsMask/00165.pdf.

    • Search Google Scholar
    • Export Citation
  • Keighton, S., and et al. , 2009: A collaborative approach to study northwest flow snow in the southern Appalachians. Bull. Amer. Meteor. Soc., 90, 979992, https://doi.org/10.1175/2009BAMS2591.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kelly, R. D., 1982: A single Doppler radar study of horizontal-roll convection in a lake-effect snow storm. J. Atmos. Sci., 39, 15211531, https://doi.org/10.1175/1520-0469(1982)039<1521:ASDRSO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kelly, R. D., 1984: Horizontal roll and boundary-layer interrelationships observed over Lake Michigan. J. Atmos. Sci., 41, 18161826, https://doi.org/10.1175/1520-0469(1984)041<1816:HRABLI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kelly, R. D., 1986: Mesoscale frequencies and seasonal snowfalls for different types of Lake Michigan snow storms. J. Climate Appl. Meteor., 25, 308312, https://doi.org/10.1175/1520-0450(1986)025<0308:MFASSF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klugmann, D., K. Heinsohn, and H. J. Kirtzel, 1996: A low cost 24 GHz FM-CW Doppler radar rain profiler. Contrib. Atmos. Phys., 61, 247253.

    • Search Google Scholar
    • Export Citation
  • Kneifel, S., M. S. Kulie, and R. Bennartz, 2011a: A triple-frequency approach to retrieve microphysical snowfall parameters. J. Geophys. Res., 116, D11203, https://doi.org/10.1029/2010JD015430.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kneifel, S., M. Maahn, G. Peters, and C. Simmer, 2011b: Observation of snowfall with a low-power FM-CW K-band radar (Micro Rain Radar). Meteor. Atmos. Phys., 113, 7587, https://doi.org/10.1007/s00703-011-0142-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kneifel, S., A. von Lerber, J. Tiira, D. Moisseev, P. Kollias, and J. Leinonen, 2015: Observed relations between snowfall microphysics and triple-frequency radar measurements. J. Geophys. Res. Atmos., 120, 60346055, https://doi.org/10.1002/2015JD023156.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kolka, R. K., C. P. Giardina, J. D. McClure, A. Mayer, and M. F. Jurgensen, 2010: Partitioning hydrologic contributions to an ‘old-growth’ riparian area in the Huron Mountains of Michigan, USA. Ecohydrology, 3, 315324, https://doi.org/10.1002/eco.112.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kristovich, D. A. R., 1993: Mean circulations of boundary-layer rolls in lake-effect snow storms. Bound.-Layer Meteor., 63, 293315, https://doi.org/10.1007/BF00710463.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kristovich, D. A. R., and R. A. Steve, 1995: A satellite study of cloud-band frequencies over the Great Lakes. J. Appl. Meteor., 34, 20832090, https://doi.org/10.1175/1520-0450(1995)034<2083:ASSOCB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kristovich, D. A. R., and N. F. Laird, 1998: Observations of widespread lake-effect cloudiness: Influences of lake surface temperature and upwind conditions. Wea. Forecasting, 13, 811821, https://doi.org/10.1175/1520-0434(1998)013<0811:OOWLEC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kristovich, D. A. R., and et al. , 2000: The Lake-Induced Convection Experiment and the snowband Dynamics Project. Bull. Amer. Meteor. Soc., 81, 519542, https://doi.org/10.1175/1520-0477(2000)081<0519:TLCEAT>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kristovich, D. A. R., N. F. Laird, and M. R. Hjelmfelt, 2003: Convective evolution across Lake Michigan during a WIDESPREAD Lake-effect snow event. Mon. Wea. Rev., 131, 643655, https://doi.org/10.1175/1520-0493(2003)131<0643:CEALMD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kristovich, D. A. R., and et al. , 2017: The Ontario Winter Lake-effect Systems field campaign: Scientific and educational adventures to further our knowledge and prediction of lake-effect storms. Bull. Amer. Meteor. Soc., 98, 315332, https://doi.org/10.1175/BAMS-D-15-00034.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kristovich, D. A. R., L. Bard, L. Stoecker, and B. Geerts, 2018: Influence of Lake Erie on a Lake Ontario lake-effect snowstorm. J. Appl. Meteor. Climatol., 57, 2019–2033, https://doi.org/10.1175/JAMC-D-17-0349.1.

    • Crossref
    • 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, https://doi.org/10.1175/2009JAMC2193.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kulie, M. S., and L. Milani, 2018: Seasonal variability of shallow cumuliform snowfall: A CloudSat perspective. Quart. J. Roy. Meteor. Soc., 144, 329343, https://doi.org/10.1002/qj.3222.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kulie, M. S., M. J. Hiley, R. Bennartz, S. Kneifel, and S. Tanelli, 2014: Triple-frequency radar reflectivity signatures of snow: Observations and comparisons with theoretical ice particle scattering models. J. Appl. Meteor. Climatol., 53, 10801098, https://doi.org/10.1175/JAMC-D-13-066.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kulie, M. S., L. Milani, N. B. Wood, S. A. Tushaus, R. Bennartz, and T. S. L’Ecuyer, 2016: A shallow cumuliform snowfall census using spaceborne radar. J. Hydrometeor., 17, 12611279, https://doi.org/10.1175/JHM-D-15-0123.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kummerow, C. D., D. L. Randel, M. Kulie, N. Wang, R. Ferraro, S. Joseph Munchak, and V. Petkovic, 2015: The evolution of the Goddard profiling algorithm to a fully parametric scheme. J. Atmos. Oceanic Technol., 32, 22652280, https://doi.org/10.1175/JTECH-D-15-0039.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kunkel, K. E., L. Ensor, M. Palecki, D. Easterling, D. Robinson, K. G. Hubbard, and K. Redmond, 2009: A new look at lake-effect snowfall trends in the Laurentian Great Lakes using a temporally homogeneous data set. J. Great Lakes Res., 35, 2329, https://doi.org/10.1016/j.jglr.2008.11.003.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Laird, N. F., N. Metz, L. Gaudet, C. Grasmick, L. Higgins, C. Loeser, and D. Zelinsky, 2017: Climatology of cold season lake-effect cloud bands for the North American Great Lakes. Int. J. Climatol., 37, 21112121, https://doi.org/10.1002/joc.4838.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lang, C. E., J. M. McDonald, L. Gaudet, D. Doeblin, E. A. Jones, and N. F. Laird, 2018: The influence of a lake-to-lake connection from Lake Huron on the lake-effect snowfall in the vicinity of Lake Ontario. J. Appl. Meteor. Climatol., 57, 14231439, https://doi.org/10.1175/JAMC-D-17-0225.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Leathers, D. J., and A. W. Ellis, 1996: Synoptic mechanisms associated with snowfall increases to the lee of Lakes Erie and Ontario. Int. J. Climatol., 16, 11171135, https://doi.org/10.1002/(SICI)1097-0088(199610)16:10<1117::AID-JOC80>3.0.CO;2-4.

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

    • Search Google Scholar
    • Export Citation
  • Liao, L., R. Meneghini, A. Tokay, and L. F. Bliven, 2016: Retrieval of snow properties for Ku- and Ka-band dual-frequency radar. J. Appl. Meteor. Climatol., 55, 18451858, https://doi.org/10.1175/JAMC-D-15-0355.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, G., 2008a: A database of microwave single-scattering properties for nonspherical ice particles. Bull. Amer. Meteor. Soc., 89, 15631570, https://doi.org/10.1175/2008BAMS2486.1.

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

    • Search Google Scholar
    • Export Citation
  • Maahn, M., and P. Kollias, 2012: Improved Micro Rain Radar snow measurements using Doppler spectra post-processing. Atmos. Meas. Tech., 5, 26612673, https://doi.org/10.5194/amt-5-2661-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maahn, M., C. Burgard, S. Crewell, I. V. Gorodetskaya, S. Kneifel, S. Lhermitte, K. Van Tricht, and N. P. van Lipzig, 2014: How does the spaceborne radar blind zone affect derived surface snowfall statistics in polar regions? J. Geophys. Res. Atmos., 119, 13 60413 620, https://doi.org/10.1002/2014JD022079.

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

    • Crossref
    • 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, https://doi.org/10.1175/2009JTECHA1238.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., M. Maahn, and G. de Boer, 2019: Observational and modeling study of ice hydrometeor radar dual-wavelength ratios. J. Appl. Meteor. Climatol., 58, 2005–2017, https://doi.org/10.1175/JAMC-D-19-0018.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McFarquhar, G. M., and et al. , 2017: Processing of ice cloud in situ data collected by bulk water, scattering, and imaging probes: Fundamentals, uncertainties, and efforts toward consistency. Ice Formation and Evolution in Clouds and Precipitation: Measurement and Modeling Challenges, Meteor. Monogr., No. 58, Amer. Meteor. Soc., https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0007.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McMillen, J. D., and W. J. Steenburgh, 2015: Impact of microphysics parameterizations on simulations of the 27 October 2010 Great Salt Lake–effect snowstorm. Wea. Forecasting, 30, 136152, https://doi.org/10.1175/WAF-D-14-00060.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meng, H., J. Dong, R. Ferraro, B. Yan, L. Zhao, C. Kongoli, N.-Y. Wang, and B. Zavodsky, 2017: A 1DVAR-based snowfall rate retrieval algorithm for passive microwave radiometers. J. Geophys. Res. Atmos., 122, 65206540, https://doi.org/10.1002/2016JD026325.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Minder, J. R., T. W. Letcher, L. S. Campbell, P. G. Veals, and W. J. Steenburgh, 2015: The evolution of lake-effect convection during landfall and orographic uplift as observed by profiling radars. Mon. Wea. Rev., 143, 44224442, https://doi.org/10.1175/MWR-D-15-0117.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Newman, A. J., P. A. Kucera, and L. F. Bliven, 2009: Presenting the Snowflake Video Imager (SVI). J. Atmos. Oceanic Technol., 26, 167179, https://doi.org/10.1175/2008JTECHA1148.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Niziol, T. A., W. R. Snyder, and J. S. Waldstreicher, 1995: Winter weather forecasting throughout the eastern United States. Part IV: Lake effect snow. Wea. Forecasting, 10, 6177, https://doi.org/10.1175/1520-0434(1995)010<0061:WWFTTE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Norton, D. C., and S. J. Bolsenga, 1993: Spatiotemporal trends in lake effect and continental snowfall in the Laurentian Great Lakes, 1951–1980. J. Climate, 6, 1943–1956, https://doi.org/10.1175/1520-0442(1993)006<1943:STILEA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Notaro, M., K. Holman, A. Zarrin, E. Fluck, S. Vavrus, and V. Bennington, 2013: Influence of the Laurentian Great Lakes on regional climate. J. Climate, 26, 789804, https://doi.org/10.1175/JCLI-D-12-00140.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Notaro, M., D. Lorenz, C. Hoving, and M. Schummer, 2014: Twenty-first-century projections of snowfall and winter severity across central-eastern North America. J. Climate, 27, 65266550, https://doi.org/10.1175/JCLI-D-13-00520.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Olson, W. S., and et al. , 2016: The microwave radiative properties of falling snow derived from nonspherical ice particle models. Part II: Initial testing using radar, radiometer and in situ observations. J. Appl. Meteor. Climatol., 55, 709722, https://doi.org/10.1175/JAMC-D-15-0131.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Owens, N. D., R. M. Rauber, B. F. Jewett, and G. M. McFarquhar, 2017: The contribution of lake enhancement to extreme snowfall within the Chicago–Milwaukee urban corridor during the 2011 Groundhog Day blizzard. Mon. Wea. Rev., 145, 24052420, https://doi.org/10.1175/MWR-D-17-0025.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pettersen, C., R. Bennartz, A. J. Merrelli, M. D. Shupe, D. D. Turner, and V. P. Walden, 2018: Precipitation regimes over central Greenland inferred from 5 years of ICECAPS observations. Atmos. Chem. Phys., 18, 47154735, https://doi.org/10.5194/acp-18-4715-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pettersen, C., M. S. Kulie, L. F. Bliven, A. J. Merrelli, W. A. Petersen, T. J. Wagner, D. B. Wolff, and N. B. Wood, 2020a: A composite analysis of snowfall modes from four winter seasons in Marquette, Michigan. J. Appl. Meteor. Climatol., 59, 103124, https://doi.org/10.1175/JAMC-D-19-0099.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pettersen, C., and et al. , 2020b: Introducing the Precipitation Imaging Package: Assessment of microphysical and bulk characteristics of snow. Atmosphere, 11, 785, https://doi.org/10.3390/atmos11080785.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Petterssen, S., and P. A. Calabrese, 1959: On some weather influences due to warming of the air by the Great Lakes in winter. J. Meteor., 16, 646652, https://doi.org/10.1175/1520-0469(1959)016<0646:OSWIDT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reeves, H. D., and D. T. Dawson, 2013: The dependence of QPF on the choice of microphysical parameterization for lake-effect snowstorms. J. Appl. Meteor. Climatol., 52, 363377, https://doi.org/10.1175/JAMC-D-12-019.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ringerud, S., M. S. Kulie, D. L. Randel, G. S. Skofronick-Jackson, and C. D. Kummerow, 2019: Effects of ice particle representation on passive microwave precipitation retrieval in a Bayesian scheme. IEEE Trans. Geosci. Remote Sens., 57, 36193632, https://doi.org/10.1109/TGRS.2018.2886063.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rodriguez, Y., D. A. R. Kristovich, and M. R. Hjelmfelt, 2007: Lake-to-lake cloud bands: Frequencies and locations. Mon. Wea. Rev., 135, 42024213, https://doi.org/10.1175/2007MWR1960.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., and D. S. Zrnić, 2019: Polarimetric measurements of precipitation. Radar Polarimetry for Weather Observations, Springer Atmospheric Sciences, 373433.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schirle, C. E., S. J. Cooper, M. A. Wolff, C. Pettersen, N. B. Wood, T. S. L’Ecuyer, T. Ilmo, and K. Nygård, 2019: Estimation of snowfall properties at a mountainous site in Norway using combined radar and in situ microphysical observations. J. Appl. Meteor. Climatol., 58, 13371352, https://doi.org/10.1175/JAMC-D-18-0281.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schmidlin, T. W., 1993: Impacts on severe winter weather during December 1989 in the Lake Erie snowbelt. J. Climate, 6, 759767, https://doi.org/10.1175/1520-0442(1993)006<0759:IOSWWD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schmidlin, T. W., and J. Kosarik, 1999: A record Ohio snowfall during 9–14 November 1996. Bull. Amer. Meteor. Soc., 80, 11071116, https://doi.org/10.1175/1520-0477(1999)080<1107:AROSDN>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schroeder, J. J., D. A. Kristovich, and M. R. Hjelmfelt, 2006: Boundary layer and microphysical influences of natural cloud seeding on a lake-effect snowstorm. Mon. Wea. Rev., 134, 18421858, https://doi.org/10.1175/MWR3151.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Scott, R. W., and F. A. Huff, 1996: Impacts on the Great Lakes on regional climate conditions. J. Great Lakes Res., 22, 845863, https://doi.org/10.1016/S0380-1330(96)71006-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Skofronick-Jackson, G., and et al. , 2015: Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEX): For measurement’s sake, let it snow. Bull. Amer. Meteor. Soc., 96, 17191741, https://doi.org/10.1175/BAMS-D-13-00262.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Skofronick-Jackson, G., and et al. , 2017: The Global Precipitation Measurement (GPM) mission for science and society. Bull. Amer. Meteor. Soc., 98, 16791695, https://doi.org/10.1175/BAMS-D-15-00306.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Skofronick-Jackson, G., M. Kulie, L. Milani, S. J. Munchak, N. B. Wood, and V. Levizzani, 2019: Satellite estimation of falling snow: A Global Precipitation Measurement (GPM) Core Observatory perspective. J. Appl. Meteor. Climatol., 58, 14291448, https://doi.org/10.1175/JAMC-D-18-0124.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sousounis, P. J., and J. M. Fritsch, 1994: Lake-aggregate mesoscale disturbances. Part II: A case study of the effects on regional and synoptic-scale weather systems. Bull. Amer. Meteor. Soc., 75, 17931812, https://doi.org/10.1175/1520-0477(1994)075<1793:LAMDPI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Souverijns, N., A. Gossart, S. Lhermitte, I. V. Gorodetskaya, S. Kneifel, M. Maahn, F. L. Bliven, and N. P. M. van Lipzig, 2017: Estimating radar reflectivity—Snowfall rate relationships and their uncertainties over Antarctica by combining disdrometer and radar observations. Atmos. Res., 196, 211223, https://doi.org/10.1016/j.atmosres.2017.06.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Spence, C., P. D. Blanken, N. Hedstrom, V. Fortin, and H. Wilson, 2011: Evaporation from Lake Superior: 2: Spatial distribution and variability. J. Great Lakes Res., 37, 717724, https://doi.org/10.1016/j.jglr.2011.08.013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Spence, C., P. D. Blanken, J. D. Lenters, and N. Hedstrom, 2013: The importance of spring and autumn atmospheric conditions for the evaporation regime of Lake Superior. J. Hydrometeor., 14, 16471658, https://doi.org/10.1175/JHM-D-12-0170.1.

    • 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, https://doi.org/10.1175/MWR-D-12-00276.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., and et al. , 2008: CloudSat mission: Performance and early science after the first year of operation. J. Geophys. Res., 113, D00A18, https://doi.org/10.1029/2008JD009982.

    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., D. Winker, J. Pelon, C. Trepte, D. Vane, C. Yuhas, T. L’Ecuyer, and M. Lebsock, 2018: CloudSat and CALIPSO within the A-Train: Ten years of actively observing the Earth system. Bull. Amer. Meteor. Soc., 99, 569581, https://doi.org/10.1175/BAMS-D-16-0324.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Suriano, Z. J., 2019: Changing intrasynoptic type characteristics and interannual frequencies of circulation patterns conducive to lake-effect snowfall. J. Appl. Meteor. Climatol., 58, 23132328, https://doi.org/10.1175/JAMC-D-19-0069.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Suriano, Z. J., and D. J. Leathers, 2017a: Synoptic climatology of lake effect snowfall conditions in the eastern Great Lakes region. Int. J. Climatol., 37, 43774389, https://doi.org/10.1002/joc.5093.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Suriano, Z. J., and D. J. Leathers, 2017b: Synoptically classified lake-effect snowfall trends to the lee of Lakes Erie and Ontario. Climate Res., 74, 113, https://doi.org/10.3354/cr01480.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thomas, B. C., and J. E. Martin, 2007: A synoptic climatology and composite analysis of the Alberta clipper. Wea. Forecasting, 22, 315333, https://doi.org/10.1175/WAF982.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tiira, J., D. N. Moisseev, A. von Lerber, D. Ori, A. Tokay, L. F. Bliven, and W. Petersen, 2016: Ensemble mean density and its connection to other microphysical properties of falling snow as observed in southern Finland. Atmos. Meas. Tech., 9, 48254841, https://doi.org/10.5194/amt-9-4825-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Veals, P. G., and W. J. Steenburgh, 2015: Climatological characteristics and orographic enhancement of lake-effect precipitation east of Lake Ontario and over the Tug Hill Plateau. Mon. Wea. Rev., 143, 35913609, https://doi.org/10.1175/MWR-D-15-0009.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Veals, P. G., W. J. Steenburgh, and L. S. Campbell, 2018: Factors affecting the inland and orographic enhancement of lake-effect precipitation over the Tug Hill Plateau. Mon. Wea. Rev., 146, 17451762, https://doi.org/10.1175/MWR-D-17-0385.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Villani, J. P., M. L. Jurewicz Sr., and K. Reinhold, 2017: Forecasting the inland extent of lake effect snow bands downwind of Lake Ontario. J. Oper. Meteor., 5, 5370, https://doi.org/10.15191/nwajom.2017.0505.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • von Lerber, A., D. Moisseev, L. F. Bliven, W. Petersen, A. Harri, and V. Chandrasekar, 2017: Microphysical properties of snow and their link to Ze –S relations during BAECC 2014. J. Appl. Meteor. Climatol., 56, 15611582, https://doi.org/10.1175/JAMC-D-16-0379.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • von Lerber, A., D. Moisseev, D. A. Marks, W. Petersen, A. M. Harri, and V. Chandrasekar, 2018: Validation of GMI snowfall observations by using a combination of weather radar and surface measurements. J. Appl. Meteor. Climatol., 57, 797820, https://doi.org/10.1175/JAMC-D-17-0176.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Welsh, D., B. Geerts, X. Jing, P. T. Bergmaier, J. R. Minder, W. J. Steenburgh, and L. S. Campbell, 2016: Understanding heavy lake-effect snowfall: The vertical structure of radar reflectivity in a deep snowband over and downwind of Lake Ontario. Mon. Wea. Rev., 144, 42214244, https://doi.org/10.1175/MWR-D-16-0057.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • West, T. K., W. J. Steenburgh, and G. G. Mace, 2019: Characteristics of sea-effect clouds and precipitation over the Sea of Japan region as observed by A-Train satellites. J. Geophys. Res. Atmos., 124, 13221335, https://doi.org/10.1029/2018JD029586.

    • Crossref
    • 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, https://doi.org/10.1175/JAMC-D-11-0112.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wood, N. B., and T. S. L’Ecuyer, 2021: What millimeter-wavelength radar reflectivity reveals about snowfall: An information-centric analysis. Atmos. Meas. Tech., 14, 869888, https://doi.org/10.5194/amt-14-869-2021.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wood, N. B., T. S. L’Ecuyer, F. L. Bliven, and G. L. Stephens, 2013: Characterization of video disdrometer uncertainties and impacts on estimates of snowfall rate and radar reflectivity. Atmos. Meas. Tech., 6, 36353648, https://doi.org/10.5194/amt-6-3635-2013.

    • Crossref
    • 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, https://doi.org/10.1175/JAMC-D-14-0137.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Woods, C. P., M. T. Stoelinga, and J. D. Locatelli, 2008: Size spectra of snow particles measured in wintertime precipitation in the Pacific Northwest. J. Atmos. Sci., 65, 189205, https://doi.org/10.1175/2007JAS2243.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, J., and et al. , 2016: Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimation: Initial operating capabilities. Bull. Amer. Meteor. Soc., 97, 621638, https://doi.org/10.1175/BAMS-D-14-00174.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Snowfall in the Northern Great Lakes: Lessons Learned from a Multisensor Observatory

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  • 1 NOAA/NESDIS/STAR/Advanced Satellite Products Branch, Madison, Wisconsin
  • | 2 Space Science and Engineering Center, University of Wisconsin–Madison, Madison, Wisconsin
  • | 3 NOAA/National Weather Service, Wakefield, Virginia
  • | 4 NOAA/National Weather Service, Indianapolis, Indiana
  • | 5 NOAA/National Weather Service, Chicago, Illinois
  • | 6 NOAA/National Weather Service, Marquette, Michigan
  • | 7 University of Wisconsin–Madison, Madison, Wisconsin
  • | 8 Michigan Technological University, Houghton, Michigan
  • | 9 Department of Geography, University of Colorado Boulder, Boulder, Colorado
  • | 10 Leipzig University, Leipzig, Germany
  • | 11 Environment and Climate Change Canada, Saskatoon, Saskatchewan, Canada
  • | 12 University of Cologne, Cologne, Germany
  • | 13 National Center for Atmospheric Research, Boulder, Colorado
  • | 14 NASA Goddard Space Flight Center, Greenbelt, Maryland
  • | 15 NASA Wallops Flight Facility, Wallops Island, Virginia
  • | 16 NASA Marshall Space Flight Center, Huntsville, Alabama
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Abstract

A multisensor snowfall observational suite has been deployed at the Marquette, Michigan, National Weather Service Weather Forecast Office (KMQT) since 2014. Micro Rain Radar (MRR; profiling radar), Precipitation Imaging Package (PIP; snow particle imager), and ancillary ground-based meteorological observations illustrate the unique capabilities of these combined instruments to document radar and concomitant microphysical properties associated with northern Great Lakes snowfall regimes. Lake-effect, lake-orographic, and transition event case studies are presented that illustrate the variety of snowfall events that occur at KMQT. Case studies and multiyear analyses reveal the ubiquity of snowfall produced by shallow events. These shallow snowfall features and their distinctive microphysical fingerprints are often difficult to discern with conventional remote sensing instruments, thus highlighting the scientific and potential operational value of MRR and PIP observations. The importance of near-surface lake-orographic snowfall enhancement processes in extreme snowfall events and regime-dependent snow particle microphysical variability controlled by regime and environmental factors are also highlighted.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Mark S. Kulie, mark.kulie@noaa.gov

Abstract

A multisensor snowfall observational suite has been deployed at the Marquette, Michigan, National Weather Service Weather Forecast Office (KMQT) since 2014. Micro Rain Radar (MRR; profiling radar), Precipitation Imaging Package (PIP; snow particle imager), and ancillary ground-based meteorological observations illustrate the unique capabilities of these combined instruments to document radar and concomitant microphysical properties associated with northern Great Lakes snowfall regimes. Lake-effect, lake-orographic, and transition event case studies are presented that illustrate the variety of snowfall events that occur at KMQT. Case studies and multiyear analyses reveal the ubiquity of snowfall produced by shallow events. These shallow snowfall features and their distinctive microphysical fingerprints are often difficult to discern with conventional remote sensing instruments, thus highlighting the scientific and potential operational value of MRR and PIP observations. The importance of near-surface lake-orographic snowfall enhancement processes in extreme snowfall events and regime-dependent snow particle microphysical variability controlled by regime and environmental factors are also highlighted.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Mark S. Kulie, mark.kulie@noaa.gov

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