• Andrić, J., M. R. Kumjian, D. S. Zrnić, J. M. Straka, and V. M. Melnikov, 2013: Polarimetric signatures above the melting layer in winter storms: An observational and modeling study. J. Appl. Meteor. Climatol., 52, 682700, https://doi.org/10.1175/JAMC-D-12-028.1.

    • 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
  • Baker, B., and R. P. Lawson, 2006: Improvement in determination of ice water content from two-dimensional particle imagery. Part I: Image-to-mass relationships. J. Appl. Meteor. Climatol., 45, 12821290, https://doi.org/10.1175/JAM2398.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bechini, R., L. Baldini, and V. Chandrasekar, 2013: Polarimetric radar observations in the ice region of precipitating clouds at C-band and X-band radar frequencies. J. Appl. Meteor. Climatol., 52, 11471169, https://doi.org/10.1175/JAMC-D-12-055.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bell, M. M., M. Dixon, B. Javornik, W.-C. Lee, B. Melli, J. DeHart, and T.-Y. Cha, 2020: nsf-lrose/lrose-cyclone: lrose-cyclone-20200110. Zenodo, https://doi.org/10.5281/zenodo.3604387.

    • Search Google Scholar
    • Export Citation
  • Brandes, E. A., and K. Ikeda, 2004: Freezing-level estimation with polarimetric radar. J. Appl. Meteor., 43, 15411553, https://doi.org/10.1175/JAM2155.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brdar, S., and A. Seifert, 2018: McSnow: A Monte-Carlo particle model for riming and aggregation of ice particles in a multidimensional microphysical phase space. J. Adv. Model. Earth Syst., 10, 187206, https://doi.org/10.1002/2017MS001167.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brown, P. R. A., and P. N. Fancis, 1995: Improved measurements of the ice water content in cirrus using a total-water probe. J. Atmos. Oceanic Technol., 12, 410414, https://doi.org/10.1175/1520-0426(1995)012<0410:IMOTIW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chase, R. J., and Coauthors, 2018: Evaluation of triple-frequency radar retrieval of snowfall properties using coincident airborne in situ observations during OLYMPEX. Geophys. Res. Lett., 45, 57525760, https://doi.org/10.1029/2018GL077997.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cober, S., A. Korolev, and G. Isaac, 2001: Assessing characteristics of the Rosemount Icing Detector under natural icing conditions. 39th Aerospace Sciences Meeting and Exhibit, Reno, NV, American Institute of Aeronautics and Astronautics, AIAA-2001-0397, https://doi.org/10.2514/6.2001-397.

    • Crossref
    • Export Citation
  • Colle, B. A., and Y. Zeng, 2004: Bulk microphysical sensitivities within the MM5 for orographic precipitation. Part I: The Sierra 1986 event. Mon. Wea. Rev., 132, 27802801, https://doi.org/10.1175/MWR2821.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Colle, B. A., M. F. Garvert, J. B. Wolfe, C. F. Mass, and C. P. Woods, 2005: The 13–14 December 2001 IMPROVE-2 event. Part III: Simulated microphysical budgets and sensitivity studies. J. Atmos. Sci., 62, 35353558, https://doi.org/10.1175/JAS3552.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Conrick, R., and C. F. Mass, 2019a: Evaluating simulated microphysics during OLYMPEX using GPM satellite observations. J. Atmos. Sci., 76, 10931105, https://doi.org/10.1175/JAS-D-18-0271.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Conrick, R., and C. F. Mass, 2019b: An evaluation of simulated precipitation characteristics during OLYMPEX. J. Hydrometeor., 20, 11471164, https://doi.org/10.1175/JHM-D-18-0144.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Durran, D. R., and J. B. Klemp, 1982: On the effects of moisture on the Brunt-Väisälä frequency. J. Atmos. Sci., 39, 21522158, https://doi.org/10.1175/1520-0469(1982)039<2152:OTEOMO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Giangrande, S. E., J. M. Krause, and A. V. Ryzhkov, 2008: Automatic designation of the melting layer with a polarimetric prototype of the WSR-88D radar. J. Appl. Meteor. Climatol., 47, 13541364, https://doi.org/10.1175/2007JAMC1634.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gourley, J. J., and C. M. Calvert, 2003: Automated detection of the bright band using WSR-88D data. Wea. Forecasting, 18, 585599, https://doi.org/10.1175/1520-0434(2003)018<0585:ADOTBB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grabowski, W. W., H. Morrison, S.-I. Shima, G. C. Abade, P. Dziekan, and H. Pawlowska, 2019: Modeling of cloud microphysics: Can we do better? Bull. Amer. Meteor. Soc., 100, 655672, https://doi.org/10.1175/BAMS-D-18-0005.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffin, E. M., T. J. Schuur, and A. V. Ryzhkov, 2018: A polarimetric analysis of ice microphysical processes in snow, using quasi-vertical profiles. J. Appl. Meteor. Climatol., 57, 3150, https://doi.org/10.1175/JAMC-D-17-0033.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hallett, J., and S. C. Mossop, 1974: Production of secondary ice particles during the riming process. Nature, 249, 2628, https://doi.org/10.1038/249026a0.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hobbs, P. V., R. C. Easter, and A. B. Fraser, 1973: A theoretical study of the flow of air and fallout of solid precipitation over mountainous terrain: Part II. Microphysics. J. Atmos. Sci., 30, 813823, https://doi.org/10.1175/1520-0469(1973)030<0813:ATSOTF>2.0.CO;2.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holroyd, E. W., 1987: Some techniques and uses of 2D-C habit classification software for snow particles. J. Atmos. Oceanic Technol., 4, 498511, https://doi.org/10.1175/1520-0426(1987)004<0498:STAUOC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houze, R. A., Jr., 2012: Orographic effects on precipitating clouds. Rev. Geophys., 50, RG1001, https://doi.org/10.1029/2011RG000365.

  • Houze, R. A., Jr., and S. Medina, 2005: Turbulence as a mechanism for orographic precipitation enhancement. J. Atmos. Sci., 62, 35993623, https://doi.org/10.1175/JAS3555.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houze, R. A., Jr., and Coauthors, 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
  • Jensen, A. A., and J. Y. Harrington, 2015: Modeling ice crystal aspect ratio evolution during riming: A single-particle growth model. J. Atmos. Sci., 72, 25692590, https://doi.org/10.1175/JAS-D-14-0297.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johnson, D. B., 1987: On the relative efficiency of coalescence and riming. J. Atmos. Sci., 44, 16711680, https://doi.org/10.1175/1520-0469(1987)044<1671:OTREOC>2.0.CO;2.

    • 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, https://doi.org/10.1175/2010JAMC2558.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • King, W. D., D. A. Parkin, and R. J. Handsworth, 1978: A hot-wire liquid water device having fully calculable response characteristics. J. Appl. Meteor., 17, 18091813, https://doi.org/10.1175/1520-0450(1978)017<1809:AHWLWD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kingsmill, D. E., P. J. Neiman, F. M. Ralph, and A. B. White, 2006: Synoptic and topographic variability of Northern California precipitation characteristics in landfalling winter storms observed during CALJET. Mon. Wea. Rev., 134, 20722094, https://doi.org/10.1175/MWR3166.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Korolev, A., and T. Leisner, 2020: Review of experimental studies of secondary ice production. Atmos. Chem. Phys., 20, 11 76711 797, https://doi.org/10.5194/acp-20-11767-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Korolev, A., J. W. Strapp, and G. A. Isaac, 1998: Evaluation of the accuracy of PMS optical array probes. J. Atmos. Oceanic Technol., 15, 708720, https://doi.org/10.1175/1520-0426(1998)015<0708:EOTAOP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumjian, M. R., and K. A. Lombardo, 2017: Insights into the evolving microphysical and kinematic structure of northeastern U.S. winter storms from dual-polarization Doppler radar. Mon. Wea. Rev., 145, 10331061, https://doi.org/10.1175/MWR-D-15-0451.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marwitz, J. D., 1983: The kinematics of orographic airflow during Sierra storms. J. Atmos. Sci., 40, 12181227, https://doi.org/10.1175/1520-0469(1983)040<1218:TKOOAD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marwitz, J. D., 1987: Deep orographic storms over the Sierra Nevada. Part I: Thermodynamic and kinematic structure. J. Atmos. Sci., 44, 159173, https://doi.org/10.1175/1520-0469(1987)044<0159:DOSOTS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Massmann, A. K., J. R. Minder, R. D. Garreaud, D. E. Kingsmill, R. A. Valenzuela, A. Montecinos, S. L. Fults, and J. R. Snider, 2017: The Chilean coastal orographic precipitation experiment: Observing the influence of microphysical rain regimes on coastal orographic precipitation. J. Hydrometeor., 18, 27232743, https://doi.org/10.1175/JHM-D-17-0005.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McFarquhar, G. M., J. A. Finlon, D. M. Stechman, W. Wu, R. C. Jackson, and M. Freer, 2018: University of Illinois/Oklahoma Optical Array Probe (OAP) processing software. Zenodo, https://doi.org/10.5281/ZENODO.1285969.

    • Search Google Scholar
    • Export Citation
  • McMurdie, L. A., A. K. Rowe, R. A. Houze Jr., S. R. Brodzik, J. P. Zagrodnik, and T. M. Schuldt, 2018: Terrain-enhanced precipitation processes above the melting layer: Results from OLYMPEX. J. Geophys. Res. Atmos., 123, 12 19412 209, https://doi.org/10.1029/2018JD029161.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Medina, S., B. F. Smull, R. A. Houze Jr., and M. Steiner, 2005: Cross-barrier flow during orographic precipitation events: Results from MAP and IMPROVE. J. Atmos. Sci., 62, 35803598, https://doi.org/10.1175/JAS3554.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Medina, S., E. Sukovich, and R. A. Houze Jr., 2007: Vertical structures of precipitation in cyclones crossing the Oregon Cascades. Mon. Wea. Rev., 135, 35653586, https://doi.org/10.1175/MWR3470.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343360, https://doi.org/10.1175/BAMS-87-3-343.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Minder, J. R., D. R. Durran, and G. H. Roe, 2011: Mesoscale controls on the mountainside snow line. J. Atmos. Sci., 68, 21072127, https://doi.org/10.1175/JAS-D-10-05006.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moisseev, D., E. Saltikoff, and M. Leskinen, 2009: Dual-polarization weather radar observations of snow growth processes. 34th Conf. on Radar Meteorology, Williamsburg, VA, Amer. Meteor. Soc., 13b.2, https://ams.confex.com/ams/pdfpapers/156123.pdf.

  • Petersen, W. A., A. Tokay, P. N. Gatlin, and M. T. Wingo, 2017a: GPM ground validation Autonomous Parsivel Unit (APU) OLYMPEX. Subsets used: APU03, APU06, APU08. NASA Global Hydrology Resource Center DAAC, accessed 28 March 2018, https://doi.org/10.5067/GPMGV/OLYMPEX/APU/DATA301.

    • Crossref
    • Export Citation
  • Petersen, W. A., D. B. Wolff, J. Wang, and A. Tokay, 2017b: GPM ground validation Met One Rain Gauge Pairs OLYMPEX. Subsets used: Fishery site, Prairie Creek site, Wynoochee site. NASA Global Hydrology Resource Center DAAC, accessed 23 April 2018, https://doi.org/10.5067/GPMGV/OLYMPEX/GAUGES/DATA201.

    • Crossref
    • Export Citation
  • Petersen, W. A., R. A. Houze, and L. A. McMurdie, 2018: GPM ground validation OLYMPEX field campaign data collection. NASA EOSDIS Global Hydrology Resource Center Distributed Active Archive Center, accessed 26 September 2016, https://doi.org/10.5067/GPMGV/OLYMPEX/DATA101.

    • Crossref
    • Export Citation
  • Petty, G. W., and W. Huang, 2011: The modified gamma size distribution applied to inhomogeneous and nonspherical particles: Key relationships and conversions. J. Atmos. Sci., 68, 14601473, https://doi.org/10.1175/2011JAS3645.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pippitt, J. L., D. B. Wolff, W. A. Petersen, and D. A. Marks, 2015: Data and operational processing for NASA’s GPM ground validation program. 37th Conf. on Radar Meteorology, Norman, OK, Amer. Meteor. Soc., 111, https://ams.confex.com/ams/37RADAR/webprogram/Paper275627.html.

  • Poellot, M. R., A. J. Heymsfield, and A. Bansemer, 2017: GPM ground validation UND citation cloud microphysics OLYMPEX. NASA Global Hydrology Resource Center DAAC, accessed 4 November 2019, https://doi.org/10.5067/GPMGV/OLYMPEX/MULTIPLE/DATA201.

    • Crossref
    • Export Citation
  • Roe, G. H., 2005: Orographic precipitation. Annu. Rev. Earth Planet. Sci., 33, 645671, https://doi.org/10.1146/annurev.earth.33.092203.122541.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rutledge, S. A., K. Young, H. Voemel, D. Hudak, and P. Rodriguez, 2018: GPM ground validation upper air radiosonde OLYMPEX. NASA Global Hydrology Resource Center DAAC, accessed 5 July 2016, https://doi.org/10.5067/GPMGV/OLYMPEX/RADIOSONDES/DATA101.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sánchez-Diezma, R., I. Zawadzki, and D. Sempere-Torres, 2000: Identification of the bright band through the analysis of volumetric radar data. J. Geophys. Res., 105, 22252236, https://doi.org/10.1029/1999JD900310.

    • 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, https://doi.org/10.1175/JAMC-D-15-0338.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schrom, R. S., M. R. Kumjian, and Y. Lu, 2015: Polarimetric radar signatures of dendritic growth zones within Colorado winter storms. J. Appl. Meteor. Climatol., 54, 23652388, https://doi.org/10.1175/JAMC-D-15-0004.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, R. B., 1979: The influence of mountains on the atmosphere. Advances in Geophysics, Vol. 21, Academic Press, 87–230, https://doi.org/10.1016/S0065-2687(08)60262-9.

    • Crossref
    • Export Citation
  • Viviroli, D., H. H. Dürr, B. Messerli, M. Meybeck, and R. Weingartner, 2007: Mountains of the world, water towers for humanity: Typology, mapping, and global significance. Water Resour. Res., 43, W07447, https://doi.org/10.1029/2006WR005653.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • White, A. B., D. J. Gottas, E. T. Strem, F. M. Ralph, and P. J. Neiman, 2002: An automated brightband height detection algorithm for use with Doppler radar spectral moments. J. Atmos. Oceanic Technol., 19, 687697, https://doi.org/10.1175/1520-0426(2002)019<0687:AABHDA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • White, A. B., P. J. Neiman, F. M. Ralph, D. E. Kingsmill, and P. O. Persson, 2003: Coastal orographic rainfall processes observed by radar during the California Land-Falling Jets Experiment. J. Hydrometeor., 4, 264282, https://doi.org/10.1175/1525-7541(2003)4<264:CORPOB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wolff, D. B., D. A. Marks, and W. A. Petersen, 2015: General application of the relative calibration adjustment (RCA) technique for monitoring and correcting radar reflectivity calibration. J. Atmos. Oceanic Technol., 32, 496506, https://doi.org/10.1175/JTECH-D-13-00185.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wolff, D. B., D. A. Marks, W. A. Petersen and J. L. Pippitt, 2017: GPM ground validation NASA S-band dual polarimetric (NPOL) Doppler radar OLYMPEX. NASA Global Hydrology Resource Center DAAC, accessed 8 December 2016, https://doi.org/10.5067/GPMGV/OLYMPEX/NPOL/DATA301.

    • Crossref
    • Export Citation
  • Zagrodnik, J. P., L. A. McMurdie, and R. A. Houze Jr., 2018: Stratiform precipitation processes in cyclones passing over a coastal mountain range. J. Atmos. Sci., 75, 9831004, https://doi.org/10.1175/JAS-D-17-0168.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zagrodnik, J. P., L. A. McMurdie, R. A. Houze Jr., and S. Tanelli, 2019: Vertical structure and microphysical characteristics of frontal systems passing over a three-dimensional coastal mountain range. J. Atmos. Sci., 76, 15211546, https://doi.org/10.1175/JAS-D-18-0279.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zagrodnik, J. P., L. A. McMurdie, and R. Conrick, 2021: Microphysical enhancement processes within stratiform precipitation on the barrier and sub-barrier scale of the Olympic Mountains. Mon. Wea. Rev., 149, 503520, https://doi.org/10.1175/MWR-D-20-0164.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 816 711 1
Full Text Views 173 126 17
PDF Downloads 165 115 9

Orographically Modified Ice-Phase Precipitation Processes during the Olympic Mountains Experiment (OLYMPEX)

Andrew DeLaFranceaDepartment of Atmospheric Sciences, University of Washington, Seattle, Washington

Search for other papers by Andrew DeLaFrance in
Current site
Google Scholar
PubMed
Close
https://orcid.org/0000-0002-5292-7698
,
Lynn McMurdieaDepartment of Atmospheric Sciences, University of Washington, Seattle, Washington

Search for other papers by Lynn McMurdie in
Current site
Google Scholar
PubMed
Close
, and
Angela RowebDepartment of Atmospheric and Oceanic Sciences, University of Wisconsin–Madison, Madison, Wisconsin

Search for other papers by Angela Rowe in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Over mountainous terrain, windward enhancement of stratiform precipitation results from a combination of warm-rain and ice-phase processes. In this study, ice-phase precipitation processes are investigated within frontal systems during the Olympic Mountains Experiment (OLYMPEX). An enhanced layer of radar reflectivity (ZH) above the melting level bright band (i.e., a secondary ZH maximum) is observed over both the windward slopes of the Olympic Mountains and the upstream ocean, with a higher frequency of occurrence and higher ZH values over the windward slopes indicating an orographic enhancement of ice-phase precipitation processes. Aircraft-based in situ observations are evaluated for the 1–2 and 3 December 2015 orographically enhanced precipitation events. Above the secondary ZH maximum, the hydrometeors are primarily horizontally oriented dendritic and branched crystals. Within the secondary ZH maximum, there are high concentrations of large (>~2-mm diameter) dendrites, plates, and aggregates thereof, with a significant degree of riming. In both events, aggregation and riming appear to be enhanced within a turbulent layer near sheared flow at the top of a low-level jet impinging on the terrain and forced to rise above the melting level. Based on windward ground sites at low, mid-, and high elevations, secondary ZH maxima periods during all of OLYMPEX are associated with increased rain rates and larger mass-weighted mean drop diameters compared to periods without a secondary ZH maximum. This result suggests that precipitation originating from secondary ZH maxima layers may contribute to enhanced windward precipitation accumulations through the formation of large, dense particles that accelerate fallout.

Significance Statement

Precipitation processes are modified within winter storms passing over the Olympic Mountains, often resulting in increased rain and snow on the windward slopes. This study evaluates precipitation characteristics and inferred growth processes related to radar reflectivity maxima within ice layers of clouds, providing insights into ice-phase contributions to windward precipitation. Ground- and aircraft-based measurements indicate that rapid ice growth may occur when branched and platelike crystals are aggregated within turbulent regions that are prevalent over the windward slopes. Large aggregate particles gain mass by collection of supercooled liquid water, which may increase precipitation fallout. While ground measurements suggest that ice-phase growth contributes to windward accumulations, some uncertainty about the processes that occur between the ice layer and the ground remain.

© 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: Andrew DeLaFrance, adelaf@uw.edu

This article is included in the The Olympic Mountains Experiment (OLYMPEX) Special Collection.

Abstract

Over mountainous terrain, windward enhancement of stratiform precipitation results from a combination of warm-rain and ice-phase processes. In this study, ice-phase precipitation processes are investigated within frontal systems during the Olympic Mountains Experiment (OLYMPEX). An enhanced layer of radar reflectivity (ZH) above the melting level bright band (i.e., a secondary ZH maximum) is observed over both the windward slopes of the Olympic Mountains and the upstream ocean, with a higher frequency of occurrence and higher ZH values over the windward slopes indicating an orographic enhancement of ice-phase precipitation processes. Aircraft-based in situ observations are evaluated for the 1–2 and 3 December 2015 orographically enhanced precipitation events. Above the secondary ZH maximum, the hydrometeors are primarily horizontally oriented dendritic and branched crystals. Within the secondary ZH maximum, there are high concentrations of large (>~2-mm diameter) dendrites, plates, and aggregates thereof, with a significant degree of riming. In both events, aggregation and riming appear to be enhanced within a turbulent layer near sheared flow at the top of a low-level jet impinging on the terrain and forced to rise above the melting level. Based on windward ground sites at low, mid-, and high elevations, secondary ZH maxima periods during all of OLYMPEX are associated with increased rain rates and larger mass-weighted mean drop diameters compared to periods without a secondary ZH maximum. This result suggests that precipitation originating from secondary ZH maxima layers may contribute to enhanced windward precipitation accumulations through the formation of large, dense particles that accelerate fallout.

Significance Statement

Precipitation processes are modified within winter storms passing over the Olympic Mountains, often resulting in increased rain and snow on the windward slopes. This study evaluates precipitation characteristics and inferred growth processes related to radar reflectivity maxima within ice layers of clouds, providing insights into ice-phase contributions to windward precipitation. Ground- and aircraft-based measurements indicate that rapid ice growth may occur when branched and platelike crystals are aggregated within turbulent regions that are prevalent over the windward slopes. Large aggregate particles gain mass by collection of supercooled liquid water, which may increase precipitation fallout. While ground measurements suggest that ice-phase growth contributes to windward accumulations, some uncertainty about the processes that occur between the ice layer and the ground remain.

© 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: Andrew DeLaFrance, adelaf@uw.edu

This article is included in the The Olympic Mountains Experiment (OLYMPEX) Special Collection.

Save