• Andrić, J., M. Kumjian, D. Zrnić, J. Straka, and V. 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.

    • Search Google Scholar
    • Export Citation
  • Baumgardner, D., and Coauthors, 2017: Cloud ice properties: In situ measurement challenges. 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-16-0011.1.

  • 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.

    • Search Google Scholar
    • Export Citation
  • Boe, B. A., and P. J. DeMott, 1999: Comparisons of Lohse wing-tip generators and burn-in-place pyrotechnics in the North Dakota cloud modification project. J. Wea. Modif., 31, 109118.

    • Search Google Scholar
    • Export Citation
  • Cober, S. G., J. W. Strapp, and G. A. Isaac, 1996: An example of supercooled drizzle drops formed through a collision–coalescence process. J. Appl. Meteor., 35, 22502260, https://doi.org/10.1175/1520-0450(1996)035<2250:AEOSDD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • DeMott, P. J., 1995: Quantitative description of ice formation mechanisms of silver iodide-type aerosols. Atmos. Res., 38, 6399, https://doi.org/10.1016/0169-8095(94)00088-U.

    • Search Google Scholar
    • Export Citation
  • DeMott, P. J., W. G. Finnegan, and L. O. Grant, 1983: An application of chemical kinetic theory and methodology to characterize the ice nucleation properties of aerosols used for weather modification. J. Appl. Meteor., 22, 11901203, https://doi.org/10.1175/1520-0450(1983)022<1190:AAOCKT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Deshler, T., and D. W. Reynolds, 1990: The persistence of seeding effects in a winter orographic cloud seeded with silver iodide burned in acetone. J. Appl. Meteor., 29, 477488, https://doi.org/10.1175/1520-0450(1990)029<0477:TPOSEI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Deshler, T., D. W. Reynolds, and A. W. Huggins, 1990: Physical response of winter orographic clouds over the Sierra Nevada to airborne seeding using dry ice or silver iodide. J. Appl. Meteor., 29, 288330, https://doi.org/10.1175/1520-0450(1990)029<0288:PROWOC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Faber, S., J. R. French, and R. Jackson, 2018: Laboratory and in-flight evaluation of measurement uncertainties from a commercial Cloud Droplet Probe (CDP). Atmos. Meas. Tech., 11, 36453659, https://doi.org/10.5194/amt-11-3645-2018.

    • Search Google Scholar
    • Export Citation
  • Field, P. R., and A. J. Heymsfield, 2003: Aggregation and scaling of ice crystal size distributions. J. Atmos. Sci., 60, 544560, https://doi.org/10.1175/1520-0469(2003)060<0544:AASOIC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • French, J. R., and Coauthors, 2018: Precipitation formation from orographic cloud seeding. Proc. Natl. Acad. Sci. USA, 115, 11681173, https://doi.org/10.1073/pnas.1716995115.

    • Search Google Scholar
    • Export Citation
  • Friedrich, K., and Coauthors, 2020: Quantifying snowfall from orographic cloud seeding. Proc. Natl. Acad. Sci. USA, 117, 51905195, https://doi.org/10.1073/pnas.1917204117.

    • Search Google Scholar
    • Export Citation
  • Fukuta, N., and T. Takahashi, 1999: The growth of atmospheric ice crystals: A summary of findings in vertical supercooled cloud tunnel studies. J. Atmos. Sci., 56, 19631979, https://doi.org/10.1175/1520-0469(1999)056<1963:TGOAIC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Geerts, B., Q. Miao, Y. Yang, R. Rasmussen, and D. Breed, 2010: An airborne profiling radar study of the impact of glaciogenic cloud seeding on snowfall from winter orographic clouds. J. Atmos. Sci., 67, 32863302, https://doi.org/10.1175/2010JAS3496.1.

    • Search Google Scholar
    • Export Citation
  • Geerts, B., and Coauthors, 2013: The AgI Seeding Cloud Impact Investigation (ASCII) campaign 2012: Overview and preliminary results. J. Wea. Modif., 45, 2443.

    • Search Google Scholar
    • Export Citation
  • Geresdi, I., R. M. Rasmussen, and W. Grabowski, 2005: Sensitivity of freezing drizzle formation in stably stratified clouds to ice processes. Meteor. Atmos. Phys., 88, 91105, https://doi.org/10.1007/s00703-003-0048-5.

    • Search Google Scholar
    • Export Citation
  • Grazioli, J., G. Lloyd, L. Panziera, C. Hoyle, P. Connoly, J. Henneberger et al., 2015: Polarimetric radar and in situ observations of riming and snowfall microphysics during CLACE, 2014. Atmos. Chem. Phys., 15, 13 78713 802, https://doi.org/10.5194/acp-15-13787-2015.

    • Search Google Scholar
    • Export Citation
  • Griffin, E., T. Schuur, and A. 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.

    • Search Google Scholar
    • Export Citation
  • Haimov, S., and A. Rodi, 2013: Fixed-antenna pointing-angle calibration of airborne Doppler cloud radar. J. Atmos. Oceanic Technol., 30, 23202335, https://doi.org/10.1175/JTECH-D-12-00262.1.

    • Search Google Scholar
    • Export Citation
  • Harimaya, T., and M. Sato, 1989: Measurement of the riming amount on snowflakes. J. Fac. Sci. Hokkaido Univ., 8, 355366.

  • Hobbs, P. V., 1975: The nature of winter clouds and precipitation in the Cascade Mountains and their modification by artificial seeding. Part III: Case studies of the effects of seeding. J. Appl. Meteor., 14, 819858, https://doi.org/10.1175/1520-0450(1975)014<0819:TNOWCA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hobbs, P. V., J. H. Lyons, J. D. Locatelli, K. R. Biswas, L. F. Radke, R. R. Weiss Sr., and A. L. Rangno, 1981: Radar detection of cloud-seeding effects. Science, 213, 12501252, https://doi.org/10.1126/science.213.4513.1250.

    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., P. R. Field, A. J. Illingworth, R. J. Cotton, and T. W. Choularton, 2002: Properties of embedded convection in warm-frontal mixed-phase cloud from aircraft and polarimetric radar. Quart. J. Roy. Meteor. Soc., 128, 451476, https://doi.org/10.1256/003590002321042054.

    • 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.

    • Search Google Scholar
    • Export Citation
  • Knollenberg, R. G., 1981: Technique for probing cloud microstructure. Clouds, Their Formation, Optical Properties, and Effects, P. V. Hobbs and A. Deepak, Eds., Academic Press, 15–91.

  • Korolev, A., J. W. Strapp, G. A. Isaac, and E. Emery, 2013: Improved airborne hot-wire measurements of ice water content in clouds. J. Atmos. Oceanic Technol., 30, 21212131, https://doi.org/10.1175/JTECH-D-13-00007.1.

    • Search Google Scholar
    • Export Citation
  • Lamb, D., and J. Verlinde, 2011: Physics and Chemistry of Clouds. Cambridge University Press, 584 pp.

  • Lance, S., C. A. Brock, D. Rogers, and J. A. Gordon, 2010: Water droplet calibration of the Cloud Droplet Probe (CDP) and in-flight performance in liquid, ice and mixed-phase clouds during ARCPAC. Atmos. Meas. Tech., 3, 16831706, https://doi.org/10.5194/amt-3-1683-2010.

    • Search Google Scholar
    • Export Citation
  • Lawson, R. P., P. Zmarzly, K. Weaver, Q. Mo, D. O’Connor, B. Baker, and H. Jonsson, 2006: The 2D-S (stereo) probe: Design and preliminary tests of a new airborne, high-speed, high-resolution particle imaging probe. J. Atmos. Oceanic Technol., 23, 14621477, https://doi.org/10.1175/JTECH1927.1.

    • Search Google Scholar
    • Export Citation
  • Ludlam, F. H., 1955: Artificial snowfall from mountain clouds. Tellus, 7, 277290, https://doi.org/10.3402/tellusa.v7i3.8908.

  • 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.

    • Search Google Scholar
    • Export Citation
  • Majewski, A., and J. French, 2020: Supercooled drizzle development in response to semi-coherent vertical velocity fluctuations within an orographic layer cloud. Atmos. Chem. Phys., 20, 50355054, https://doi.org/10.5194/acp-20-5035-2020.

    • Search Google Scholar
    • Export Citation
  • Marcolli, C., B. Nagare, A. Welti, and U. Lohmann, 2016: Ice nucleation efficiency of AgI: Review and new insights. Atmos. Chem. Phys., 16, 89158937, https://doi.org/10.5194/acp-16-8915-2016.

    • Search Google Scholar
    • Export Citation
  • Mitchell, D. L., R. Zhang, and R. L. Pitter, 1990: Mass-dimensional relationships for ice particles and the influence of riming on snowfall rates. J. Appl. Meteor., 29, 153163, https://doi.org/10.1175/1520-0450(1990)029<0153:MDRFIP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Moisseev, D., E. Saltikoff, and M. Leskinen, 2009: Using dual-polarization weather radar observations to improve quantitative precipitation estimation in snowfall. Proc. Eighth Int. Symp. on Tropospheric Profiling, Delft, Netherlands, Royal Netherlands Meteorological Institute, S11-O04.

  • Moisseev, D., S. Lautaportti, J. Tyynela, and S. Lim, 2016: Dual-polarization radar signatures in snowstorms: Role of snowflake aggregation. J. Geophys. Res., 121, 12 64412 655, https://doi.org/10.1002/2015JD023884.

    • Search Google Scholar
    • Export Citation
  • Moisseev, D., A. von Lerber, and J. Tiira, 2017: Quantifying the effect of riming on snowfall using ground-based observations. J. Geophys. Res., 122, 40194037, https://doi.org/10.1002/2016JD026272.

    • Search Google Scholar
    • Export Citation
  • Murakami, M., Y. Yamada, T. Matsuo, H. Mizuno, and K. Morikawa, 1992: Microphysical structures of warm-frontal clouds. The 20 June 1987 case study. J. Meteor. Soc. Japan, 70, 877895, https://doi.org/10.2151/jmsj1965.70.5_877.

    • Search Google Scholar
    • Export Citation
  • Peters, G., B. Fischer, and T. Andersson, 2002: Rain observations with a vertically looking Micro Rain Radar (MRR). Boreal Environ. Res., 7, 353362.

    • Search Google Scholar
    • Export Citation
  • Pokharel, B., B. Geerts, X. Jing, K. Friedrich, J. Aikins, D. Breed, R. Rasmussen, and A. Huggins, 2014: The impact of ground-based glaciogenic seeding on clouds and precipitation over mountains: A multi-sensor case study of shallow precipitating orographic cumuli. Atmos. Res., 147–148, 162182, https://doi.org/10.1016/j.atmosres.2014.05.014.

    • Search Google Scholar
    • Export Citation
  • Pokharel, B., B. Geerts, X. Jing, K. Friedrich, K. Ikeda, and R. Rasmussen, 2017: A multi-sensor study of the impact of ground-based glaciogenic seeding on clouds and precipitation over mountains in Wyoming. Part II: Seeding impact analysis. Atmos. Res., 183, 4257, https://doi.org/10.1016/j.atmosres.2016.08.018.

    • Search Google Scholar
    • Export Citation
  • Politovich, M. K., 1989: Aircraft icing caused by large supercooled droplets. J. Appl. Meteor., 28, 856868, https://doi.org/10.1175/1520-0450(1989)028<0856:AICBLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Pruppacher, H. R., and J. D. Klett, 1997: Microphysics of Clouds and Precipitation. 2nd ed. Kluwer Academic, 954 pp.

  • Rangno, A. L., and P. V. Hobbs, 1991: Ice particle concentrations and precipitation development in small polar maritime cumuliform clouds. Quart. J. Roy. Meteor. Soc., 117, 207241, https://doi.org/10.1002/qj.49711749710.

    • Search Google Scholar
    • Export Citation
  • Rasmussen, R. M., B. C. Bernstein, M. Murakami, G. Stossmeister, and B. Stankov, 1995: The 1990 Valentine’s Day Arctic outbreak. Part I: Mesoscale and microscale structure and evolution of a Colorado Front Range shallow upslope cloud. J. Appl. Meteor., 34, 14811511, https://doi.org/10.1175/1520-0450-34.7.1481.

    • Search Google Scholar
    • Export Citation
  • Rauber, R. M., and Coauthors, 2019: Wintertime orographic cloud seeding—A review. J. Appl. Meteor. Climatol., 58, 21172140, https://doi.org/10.1175/JAMC-D-18-0341.1.

    • Search Google Scholar
    • Export Citation
  • Reinking, R. F., 1979: The onset and early growth of snow crystals by accretion of droplets. J. Atmos. Sci., 36, 870881, https://doi.org/10.1175/1520-0469(1979)036<0870:TOAEGO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rodi, A., 2011: King of the air: The evolution and capabilities of Wyoming’s observation aircraft. Meteor. Technol. Int., 2011 (5), 4447, http://viewer.zmags.com/publication/852ec8f8#/852ec8f8/46.

    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., and D. S. Zrnic, 1998: Discrimination between rain and snow with a polarimetric radar. J. Appl. Meteor., 37, 12281240, https://doi.org/10.1175/1520-0450(1998)037<1228:DBRASW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Schneebeli, M., N. Dawes, M. Lehning, and A. Berne, 2013: High-resolution vertical profiles of X-Band polarimetric radar observables during snowfall in the Swiss Alps. J. Appl. Meteor. Climatol., 52, 378394, https://doi.org/10.1175/JAMC-D-12-015.1.

    • 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.

    • Search Google Scholar
    • Export Citation
  • Takahashi, T., T. Endoh, G. Wakaham, and N. Fukuta, 1991: Vapor diffusional growth of freefalling snow crystals between −3 and −23°C. J. Meteor. Soc. Japan, 69, 1530, https://doi.org/10.2151/jmsj1965.69.1_15.

    • Search Google Scholar
    • Export Citation
  • Tessendorf, S. A., B. Boe, B. Geerts, M. J. Manton, S. Parkinson, and R. Rasmussen, 2019: A transformational approach to winter orographic weather modification research: The SNOWIE Project. Bull. Amer. Meteor. Soc., 96, 21952198, https://doi.org/10.1175/BAMS-D-15-00146.1.

    • Search Google Scholar
    • Export Citation
  • Wang, Z., and Coauthors, 2012: Single aircraft integration of remote sensing and in situ sampling for the study of cloud microphysics and dynamics. Bull. Amer. Meteor. Soc., 93, 653668, https://doi.org/10.1175/BAMS-D-11-00044.1.

    • Search Google Scholar
    • Export Citation
  • Williams, E. D., and Coauthors, 2015: Measurements of differential reflectivity in snowstorms and warm season stratiform systems. J. Appl. Meteor. Climatol., 54, 573595, https://doi.org/10.1175/JAMC-D-14-0020.1.

    • Search Google Scholar
    • Export Citation
  • Wurman, J., 2001: The DOW mobile multiple-Doppler network. Preprints, 30th Int. Conf. on Radar Meteorology, Munich, Germany, Amer. Meteor. Soc., 95–97.

  • Xue, L., and Coauthors, 2013: Implementation of a silver iodide cloud seeding parameterization in WRF. Part I: Model description and idealized 2D sensitivity tests. J. Appl. Meteor. Climatol., 52, 14331457, https://doi.org/10.1175/JAMC-D-12-0148.1.

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

    Schematic of cloud-seeding operations and related research questions.

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    Fig. 2.

    Topographic map showing the flight tracks for the seeding aircraft (solid lines) and the UWKA aircraft (dashed lines) on 19 (red lines), 20 (blue lines), and 30 Jan 2017 (green line). The range of cruising altitudes (MSL) is indicated for each aircraft and day; leg notation is indicated for 19 Jan; winds at the cruising altitude of the seeding aircraft are indicated (half barb is 2.5 m s−1, and full barb is 5 m s−1). Locations of the ground-based radar at PJ and SB and the sounding at Crouch are shown as diamond and circle symbols, respectively. The distance from the PJ radar along the UWKA track is indicated. The 50-km radius around each radar is highlighted as a gray area. Mountain ranges discussed in the text are highlighted.

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    Fig. 3.

    Vertical profile of (a) temperature, (b) equivalent potential temperature, (c) wind speed, and (d) wind direction from the sounding at Crouch closest to the seeding line observations at 1600 UTC 19 Jan (red lines), 0000 UTC 20 Jan (blue lines), and 1600 UTC 31 Jan (green lines). The horizontal gray dashed line represents the height of PJ. The range of cloud-top heights as the seeding lines pass through the ROD are indicated by unfilled boxes in (a); the range of UWKA flights is indicated by filled boxes (color coded by day) associated with the cloud-top range.

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    Fig. 4.

    Location of flares (upper plot) and 10-min averaged liquid water content (lower plot) measured by the seeding aircraft for each seeding flight leg on (a) 19, (b) 20, and (c) 31 Jan. The direction of the flight leg is indicated by gray arrows in the upper panels. Circles and lines respectively indicate the locations of the EJ and BIP flares. Data were averaged over 10 min in the lower panels. Numbers in parentheses indicate the mean temperature during the seeding flight leg.

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    Fig. 5.

    Combined maximum Ze between the surface and 1 km AGL from the PJ and SB DOW radars on 19 Jan at (a) 1710, (b) 1719, (c) 1729, and (d) 1746 UTC. Radar locations are indicated by the star symbols, and the maximum range of 50 km is indicated with a circle centered around each radar. UWKA legs 6–8 are highlighted as a red dashed line; the position of the UWKA aircraft at the radar times is highlighted by an aircraft symbol. Seeding aircraft legs are indicated as black dashed lines. Seeding lines A′ and B′ associated with legs A and B are highlighted.

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    Fig. 6.

    Evolution of Ze from the WCR during UWKA legs 4–10 on 19 Jan. Times given indicate the beginning and end of each leg, and arrows indicate flight direction for that leg. In all cases, wind is from left to right. A clear signal from seeding line A is detected in all seven legs. Seeding line B is detectable in the last five legs. Thick, solid lines contour regions of enhanced reflectivity caused by seeding. Dashed lines show similar regions of increased reflectivity from seeding that are interspersed with areas of natural reflectivity enhancement. The white belt is the WCR blind zone centered at flight level.

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    Fig. 7.

    (a) Hydrometeor size distributions measured by the in situ probes on the UWKA in line A′ during UWKA legs 4–10 on 19 Jan sampled between 1640 and 1816 UTC. (b) Particle images from the 2DS from seeding-line passage are shown. The frame size is 1.6 mm from top to bottom as indicated in the top frame; the labels on the right indicate the UWKA leg number and the duration between the release of the seeding material and sampling by the UWKA. (c) Vertical profiles of Ze from the WCR in seeding line A for each of the UWKA legs shown in Fig. 5. Each box is 8 km wide and 4 km tall [leg number and time are on the bottom, as in (b)]. The gray bar indicates that portion of the UWKA track that was in the seeding line for each of the seven passes and used for the size distribution in (a). Maximum LWC observed at flight level within the seeded line is indicated on the top.

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    Fig. 8.

    As in Fig. 7, but for line B′ on 19 Jan.

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    Fig. 9.

    RHI composite between 1654 and 1742 UTC along the flight track at 39° azimuthal direction on 19 Jan showing dual-polarization variables for (a) line A′ and (b) line B′ with Kdp on the top plot, Zdr in the middle plot, and Ze in the lower plot. Terrain is indicated in dark-gray shading The cone of silence and the area below the lowest radar beam are indicated in light-gray shading. PJ is shown as a star symbol, and the North Folk Range is highlighted. Temperatures were derived from the nearest sounding at 1600 UTC at Crouch (location shown in Fig. 2). Radar times are indicated in the top plot; minutes after seeding are in the middle plot. Red shading indicates the altitude range of the UWKA flight tracks.

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    Fig. 10.

    Similar to Fig. 6, but for the evolution of near-vertical Doppler radial velocity from the WCR during UWKA legs 6–8 on 19 Jan. Blue shades indicate upward motion, and red shades indicate downward motion. Note that the color scale has been shifted by 1 m s−1 to account for an expected nominal terminal fall velocity of the main scatterers. In this context blue and red regions respectively indicate areas of upward-moving and downward-moving air. Black lines contour regions of enhanced reflectivity caused by seeding.

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    Fig. 11.

    (a) PPI of Ze at 2.8 km MSL on 19 Jan. Each plot is 50 km × 100 km. Mean dual-polarization variables are analyzed for line A′ indicated within the black box. Color bars for Ze and terrain are shown in Fig. 4. Vertical profiles of mean (b) Ze, (c) Zdr, (d) Kdp, and (e) ρhv as a function of time (color coded). Horizontal lines indicate −10° and −15°C temperatures from the 1600 UTC sounding at Crouch. Red shading indicates the altitude range of the UWKA flight tracks.

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    Fig. 12.

    As in Fig. 5, but Ze from PJ radar for 20 Jan at (a) 0047, (b) 0116, (c) 0143, and (d) 0211 UTC.

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    Fig. 13.

    As in Fig. 6, but showing UWKA legs 6–10 on 20 Jan. Since the UWKA passed through the northwest end of the seeding lines, pairs of lines show up as a single intersect and are therefore labeled as pairs.

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    Fig. 14.

    Vertical profile of Ze (color coded) and Doppler velocity (black lines; m s−1) observed by the MRR at PJ on 20 Jan between 0045 and 0200 UTC. Seeding lines C′–H′ are labeled. Blue shading indicates the altitude range of the UWKA flight tracks.

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    Fig. 15.

    Hydrometeor size distributions measured by in situ probes on the UWKA in (a) lines C′D′, (b) lines E′F′, and (c) lines G′H′ corresponding to UWKA legs 7–10 on 20 Jan (cf. Fig. 7). Vertical profiles of Ze from the WCR for (d) lines C′D′, (e) lines E′F′, and (f) lines G′H′ shown in (a)–(c). Each box is 9 km wide and 5 km tall. The gray bar indicates that portion of the UWKA leg from which the size distributions were constructed. The labels below each image indicate the UWKA leg number and the duration of the gray bar. Labels above indicate the maximum LWC observed within the gray bar.

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    Fig. 16.

    As in Fig. 11, but (a) PPI of Ze at 2.8 km MSL for four radar times on 20 Jan. ROD is divided into four 8 km × 60 km boxes (boxes 1–4) indicating the analysis area. Each panel is 50 km × 60 km. Vertical profiles of (b) area with Ze > 15 dBZ, (c) Ze¯, (d) Kdp¯, and (e) Zdr¯ as a function of time (color coded). Horizontal lines indicate −5°, −10°, and −15°C temperatures from the 0000 UTC sounding at Crouch. Gray shading indicates height levels that might be partially affected by radar beam blockage. Blue shading indicates the altitude range of the UWKA flight tracks.

  • View in gallery
    Fig. 17.

    As in Fig. 11, but for Ze observed by the SB DOW radar on 31 Jan at (a) 2110, (b) 2122, (c) 2134, and (d) 2146 UTC.

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    Fig. 18.

    (a) Vertical west–east cross section of Ze from the UWKA flight legs 6–9. Times and flight direction are indicated. Terrain is shown in black. (b) West–east RHI scan along flight track on 31 Jan observed by the PJ DOW radar at 2114, 2124, 2130, and 2142 UTC. UWKA flight legs 6–9 and the position of the aircraft are indicated as a red line and red aircraft symbol. Lines A′ and B′ indicate the BIP flares, and lines A″ and B″ are the EJ flares. Dark-gray shading indicates topography; lighter-gray shading indicates approximated radar coverage.

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    Fig. 19.

    As in Fig. 11, but showing (a) PPI of Ze at 2.8 km at six radar times on 31 Jan. Each plot is 50 km × 95 km. Vertical profiles of mean (b) Ze, (c) Zdr, (d) Kdp, and (e) hv over all seeding lines. Horizontal lines indicate −10° and −15°C temperatures from the closest sounding at 1600 UTC sounding at Crouch. Green shading indicates the altitude range of the UWKA flight tracks.

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    Fig. 20.

    A conceptual illustration of the seeding lines and snowfall with (a) weak horizontal winds (19 and 20 Jan) and (b) strong horizontal winds on 31 Jan (modified Fig. 1 in French et al. 2018). The top plots show temporal evolution of the seeding lines, with yellow–orange–red colors indicating locations and relative magnitude of Ze as a vertical cross section along the UWKA flight track. The bottom plots show a plain view of the distribution of total accumulated liquid equivalent snowfall with intensities increasing from yellow to orange to red colors [modified from Friedrich et al. (2020)]. Observations are limited to the maximum radar range; accumulations most likely occurred farther downwind and beyond the radar range. Yellow dots show locations of ground-based radars, the solid and dashed lines represent a typical flight track for the seeding or Wyoming King Air aircraft, respectively.

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Microphysical Characteristics and Evolution of Seeded Orographic Clouds

Katja FriedrichaDepartment of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado

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Jeffrey R. FrenchbDepartment of Atmospheric Science, University of Wyoming, Laramie, Wyoming

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Sarah A. TessendorfcResearch Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Melinda HattbDepartment of Atmospheric Science, University of Wyoming, Laramie, Wyoming

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Courtney WeekscResearch Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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

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Bart GeertsbDepartment of Atmospheric Science, University of Wyoming, Laramie, Wyoming

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Lulin XuecResearch Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Roy M. RasmussencResearch Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Derek R. BlestrudeIdaho Power Company, Boise, Idaho

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Melvin L. KunkeleIdaho Power Company, Boise, Idaho

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Nicholas DawsoneIdaho Power Company, Boise, Idaho

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Shaun ParkinsoneIdaho Power Company, Boise, Idaho

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Free access

Abstract

The spatial distribution and magnitude of snowfall resulting from cloud seeding with silver iodide (AgI) is closely linked to atmospheric conditions, seeding operations, and dynamical, thermodynamical, and microphysical processes. Here, microphysical processes leading to ice and snow production are analyzed in orographic clouds for three cloud-seeding events, each with light or no natural precipitation and well-defined, traceable seeding lines. Airborne and ground-based radar observations are linked to in situ cloud and precipitation measurements to determine the spatiotemporal evolution of ice initiation, particle growth, and snow fallout in seeded clouds. These processes and surface snow amounts are explored as particle plumes evolve from varying amounts of AgI released, and within changing environmental conditions, including changes in liquid water content (LWC) along and downwind of the seeding track, wind speed, and shear. More AgI did not necessarily produce more liquid equivalent snowfall (LESnow). The greatest amount of LESnow, largest area covered by snowfall, and highest peak snowfall produced through seeding occurred on the day with the largest and most widespread occurrence of supercooled drizzle, highest wind shear, and greater LWC along and downwind of the seeding track. The day with the least supercooled drizzle and the lowest LWC downwind of the seeding track produced the smallest amount of LESnow through seeding. The stronger the wind was, the farther away the snowfall occurred from the seeding track.

© 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: Katja Friedrich, katja.friedrich@colorado.edu

Abstract

The spatial distribution and magnitude of snowfall resulting from cloud seeding with silver iodide (AgI) is closely linked to atmospheric conditions, seeding operations, and dynamical, thermodynamical, and microphysical processes. Here, microphysical processes leading to ice and snow production are analyzed in orographic clouds for three cloud-seeding events, each with light or no natural precipitation and well-defined, traceable seeding lines. Airborne and ground-based radar observations are linked to in situ cloud and precipitation measurements to determine the spatiotemporal evolution of ice initiation, particle growth, and snow fallout in seeded clouds. These processes and surface snow amounts are explored as particle plumes evolve from varying amounts of AgI released, and within changing environmental conditions, including changes in liquid water content (LWC) along and downwind of the seeding track, wind speed, and shear. More AgI did not necessarily produce more liquid equivalent snowfall (LESnow). The greatest amount of LESnow, largest area covered by snowfall, and highest peak snowfall produced through seeding occurred on the day with the largest and most widespread occurrence of supercooled drizzle, highest wind shear, and greater LWC along and downwind of the seeding track. The day with the least supercooled drizzle and the lowest LWC downwind of the seeding track produced the smallest amount of LESnow through seeding. The stronger the wind was, the farther away the snowfall occurred from the seeding track.

© 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: Katja Friedrich, katja.friedrich@colorado.edu

1. Introduction

Mountain snowpack is a natural reservoir recharged annually by winter snowfall. Seeding of orographic clouds to increase snowpack and water supplies for agricultural, energy, and municipal applications has been pursued for nearly 70 years (Rauber et al. 2019). During cloud seeding, silver iodide (AgI) aerosols are injected into clouds of supercooled liquid water (SLW) converting droplets into ice particles, which subsequently fall out as snow (Ludlam 1955). Advances in physical analyses of cloud-seeding operations have recently resulted in increasingly robust evaluations of cloud-seeding components under varying atmospheric conditions (e.g., Geerts et al. 2010, 2013; Pokharel et al. 2014, 2017; French et al. 2018; Tessendorf et al. 2019; Friedrich et al. 2020). In orographic cloud systems, SLW forms within updrafts generated through orographic lift, convection, and dynamical processes such as gravity waves, cloud-top generating cells, or turbulence (see review by Rauber et al. 2019). Low ice particle concentrations (<0.1 L−1) and warm cloud tops (>−15°C) enhance the likelihood that SLW will be present (e.g., Politovich 1989; Rangno and Hobbs 1991; Murakami et al. 1992; Rasmussen et al. 1995; Cober et al. 1996; Geresdi et al. 2005). Targeting areas of enhanced SLW and low natural ice crystal concentrations by introducing artificial ice nucleating particles increases the likelihood that ice crystals may form and precipitate as snow.

Several studies have observed the airborne seeding-induced ice nucleation process by measuring an increase in in-cloud ice particle concentrations, changes in particle-size spectra, and depletion of smaller and growth of larger particles (Hobbs 1975; Hobbs et al. 1981; Deshler et al. 1990; Deshler and Reynolds 1990; French et al. 2018). However, quantifying ice and snow production, and comparing the results from seeding experiments remains challenging because of variations in the amount and type of seeding agent used, thermodynamic structure of the clouds, and atmospheric conditions during seeding. For example, Deshler and Reynolds (1990) observed an ice particle concentration of 50–100 L−1 and rimed particles 5–10 min after airborne cloud seeding over California’s central Sierra Nevada using a combination of dry ice and AgI. By contrast, French et al. (2018) reported an ice particle concentration of only 1–5 L−1 with diameters > 300 μm 30 min after airborne seeding using AgI over Idaho’s Payette Mountains. Once ice nucleation occurs, ice particles undergo depositional, dendritic growth at temperatures between −10° and −15°C (Takahashi et al. 1991; Fukuta and Takahashi 1999; Kennedy and Rutledge 2011; Andrić et al. 2013; Bechini et al. 2013; Schrom et al. 2015; Williams et al. 2015; Moisseev et al. 2016; Griffin et al. 2018) as well as aggregation and riming (Reinking 1979; Mitchell et al. 1990; Harimaya and Sato 1989; Moisseev et al. 2017; Grazioli et al. 2015).

Although these studies have provided evidence of microphysical changes associated with cloud seeding, in this study ice initiation and snow production are quantified and linked to environmental conditions, seeding procedures, and microphysical processes. The goal of this paper is to quantify ice and snow production, and associated microphysical processes due to cloud seeding, and show how these processes are linked to environmental conditions, terrain, and AgI amount for three cloud-seeding events discussed previously in French et al. (2018), Tessendorf et al. (2019), and Friedrich et al. (2020). We attempt to answer the following questions (Fig. 1): How much SLW is depleted and ice produced in seeded clouds? How long does it take to produce ice after AgI injection into clouds? How fast does ice grow into precipitating snow? How are ice initiation, particle growth, and snowfall out related to the amount of AgI released and environmental conditions?

Fig. 1.
Fig. 1.

Schematic of cloud-seeding operations and related research questions.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

2. SNOWIE campaign

Data for these events were collected on 19, 20, and 31 January 2017 during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE). On those days, the seeding aircraft released burn-in-place (BIP) and/or ejectable (EJ) flares of AgI perpendicular to the mean wind direction and upwind of two X-band ground-based radars located on mountaintops at Packer John (PJ) and Snowbank (SB; Fig. 2, Table 1). Flight legs of the seeding aircraft will be referred to using capital letters, for example, leg A. The University of Wyoming King Air (UWKA) research aircraft flew tracks prior to, during, and after cloud seeding along the direction of the mean wind perpendicular to the seeding aircraft legs, passing over PJ (Fig. 2). Flight legs of the UKWA will be referred to using numbers (e.g., leg 1). The PJ and SB radars conducted vertical cross section and volume scans (Table 2). Airborne in situ and cloud radar observations are used to quantify supercooled liquid and natural ice particle concentrations prior to injecting AgI into the clouds, and ice nucleation resulting from cloud seeding. Dual-polarization radar observations from the PJ and SB radars are used to study microphysical processes. A detailed overview of the experimental design, instrument specifications, and deployed strategies is given in appendix A and Tessendorf et al. (2019).

Fig. 2.
Fig. 2.

Topographic map showing the flight tracks for the seeding aircraft (solid lines) and the UWKA aircraft (dashed lines) on 19 (red lines), 20 (blue lines), and 30 Jan 2017 (green line). The range of cruising altitudes (MSL) is indicated for each aircraft and day; leg notation is indicated for 19 Jan; winds at the cruising altitude of the seeding aircraft are indicated (half barb is 2.5 m s−1, and full barb is 5 m s−1). Locations of the ground-based radar at PJ and SB and the sounding at Crouch are shown as diamond and circle symbols, respectively. The distance from the PJ radar along the UWKA track is indicated. The 50-km radius around each radar is highlighted as a gray area. Mountain ranges discussed in the text are highlighted.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

Table 1.

Number of BIP and EJ flares, amount of AgI released, mean LWC along each seeding leg, and percentage of the flight leg conducted in clouds. The BIP flares burn for about 4.5 min and release 16.2 g of AgI per flare, and the EJ flares burn for about 35 s and release 2.2 g of AgI per flare. The BIP flares produce a horizontal line of AgI of ~35 km along flight level, and the EJ flares produce a vertical line of AgI of ~820 m below flight level, resulting in a concentration of about 0.5 g km−1 of BIP-AgI flares along the flight track or 2.7 g km−1 of EJ-AgI flares below the flight track. The seeding aircraft, flying at a speed of about 130 m s−1, released BIP and EJ flares as shown in Fig. 3.

Table 1.
Table 2.

Scan strategy for PJ and SB radars for the cases discussed here including 360° azimuthal or PPI scans and vertical cross sections or RHI scans upwind and downwind from the radar. The RHI scans along the UWKA flight track and PPI scans used for this analysis are highlighted in boldface type. Both radars conducted Zdr calibration scans at 89° elevation angle every 12 min.

Table 2.

3. Ice initiation and snow growth on 19 January

a. Natural cloud characteristics and atmospheric conditions

During this event, a slightly conditionally unstable atmosphere was observed between 4 and 4.5 km at temperatures T between −12° and −18°C (Figs. 3a–b, blue lines, all heights above mean sea level, unless otherwise indicated). Southwesterly flow < 20 m s−1 was observed between the surface and 4 km veering to southerly flow between 5.5 and 7 km where winds increased from 20 to 38 m s−1 (Fig. 3c). Enhanced wind shear of >0.02 s−1 occurred between the surface and 2 km and between 4 and 4.5 km. Prior to seeding, cloud top was > 8 km MSL. This deeper cloud split into two layers, with seeding occurring in the lower cloud layer, which had a top between 4 and 4.5 km. During seeding, the cloud top of the lower layer descended to about 3 km as shallower clouds moved in from the west. Within the shallower cloud layer, tops varied as much as 1 km along a single flight leg. Clouds in which seeding lines were observed had −13° < T < −15°C with cloud top at 4–5 km.

Fig. 3.
Fig. 3.

Vertical profile of (a) temperature, (b) equivalent potential temperature, (c) wind speed, and (d) wind direction from the sounding at Crouch closest to the seeding line observations at 1600 UTC 19 Jan (red lines), 0000 UTC 20 Jan (blue lines), and 1600 UTC 31 Jan (green lines). The horizontal gray dashed line represents the height of PJ. The range of cloud-top heights as the seeding lines pass through the ROD are indicated by unfilled boxes in (a); the range of UWKA flights is indicated by filled boxes (color coded by day) associated with the cloud-top range.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

The UWKA flew repeated legs in-cloud within 1 km of cloud top at −11° < T < −14°C. Natural cloud conditions were determined prior to seeding, and during and after seeding outside the seeding lines. Clouds were dominated by SLW, with leg-averaged, LWCs ranging from 0.1 to 0.2 g m−3 and maxima ranging between 0.3 and 0.4 g m−3. Cloud droplet concentrations were < 30 cm−3. Supercooled drizzle with 50 < D < 100 μm was observed in isolated pockets, similar to natural conditions in other cases from SNOWIE (Tessendorf et al. 2019; Majewski and French 2020). Natural ice particle concentrations were < 1 L−1 and often < 0.1 L−1. The only significant concentrations of ice observed at flight level were within seeding lines and over the highest terrain more than 40 km downstream of PJ.

b. Seeding operations and evolution of the seeding lines

The seeding aircraft flew six legs (legs A–F) between 1620 and 1737 UTC (Fig. 2). The reflectivity plumes and microphysical signatures developing from those six legs will be referred to as lines A′–F′. Legs A and B were flown at cloud top (4.1 km) with a mean temperature T¯ = −14°C (Fig. 4a). Legs C–F were flown at 4.4 km MSL at T¯ = −16°C (Fig. 4a). Legs B–F were flown on a track downwind from A (Fig. 2). Leg A commenced at 1620 UTC. The LWC ranged from 0 to 0.4 g m−3 with LWC¯ = 0.11–0.17 g m−3 along legs A and B, with lower amounts (LWC¯ = 0.08–0.09 g m−3) along legs C and D, mostly confined to the southeastern end of the track (Fig. 4a, Table 1). Negligible SLW (LWC¯ < 0.008 g m−3) was observed during legs E and F. Both BIP and EJ flares were deployed during all legs (Table 1, Fig. 4a).

Fig. 4.
Fig. 4.

Location of flares (upper plot) and 10-min averaged liquid water content (lower plot) measured by the seeding aircraft for each seeding flight leg on (a) 19, (b) 20, and (c) 31 Jan. The direction of the flight leg is indicated by gray arrows in the upper panels. Circles and lines respectively indicate the locations of the EJ and BIP flares. Data were averaged over 10 min in the lower panels. Numbers in parentheses indicate the mean temperature during the seeding flight leg.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

A line of enhanced reflectivity (Ze > 15 dBZe, with surroundings from −30 to +10 dBZe) was first observed at 1647 UTC by the PJ Doppler on Wheels (DOW) radar on the southern edge of the radar observational domain (ROD). Calculations of transport time of the seeding material by the mean wind showed that this line originated at A (and hence will be referred to as A′) where EJs and BIPs were deployed 28 min earlier (Table 1). Line A′ continued to move northeastward with the mean wind, passing over PJ at 1710 UTC (Fig. 5, and Movie S1 in the online supplemental material). A second line of enhanced reflectivity (Ze > 15 dBZe with surroundings from less than −30 to +10 dBZe), associated with leg B, was later observed on the southeastern side of the ROD at 1705 UTC, 15 min after the southern portion of B was flown (Fig. 5a). Recall that the seeding aircraft moved its flight track eastward after A (Fig. 2). As a result, A′ and B′ appeared as two parallel lines of enhanced reflectivity with A′ upwind of B′. By the time A′ and B′ propagated through the ROD by 1812 UTC, and moved over higher terrain, the lines had widened and near surface Ze within the lines enhanced to >25 dBZe. Snowfall on the ground was first observed at 1715 UTC and continued through 1812 UTC (Fig. 3 in Friedrich et al. 2020).

Fig. 5.
Fig. 5.

Combined maximum Ze between the surface and 1 km AGL from the PJ and SB DOW radars on 19 Jan at (a) 1710, (b) 1719, (c) 1729, and (d) 1746 UTC. Radar locations are indicated by the star symbols, and the maximum range of 50 km is indicated with a circle centered around each radar. UWKA legs 6–8 are highlighted as a red dashed line; the position of the UWKA aircraft at the radar times is highlighted by an aircraft symbol. Seeding aircraft legs are indicated as black dashed lines. Seeding lines A′ and B′ associated with legs A and B are highlighted.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

The UWKA WCR first detected A′ at 1650 UTC, ~12 km upwind of PJ on UKWA leg 4. At this time, the ice particle plume associated with A′ had a maximum Ze of 5 dBZe as compared with Ze < −10 dBZe in surrounding regions. Line A′ was 1–2 km wide and located at 4–5 km MSL (Fig. 6). Over the next 30 min, A′ grew to 3–5 km wide in the upper portion of the cloud and Ze increased to 10 dBZe. The plume of Ze associated with A′ extended from cloud top to the surface by 1719 UTC, 8 km downwind of PJ (Fig. 6, leg 6). As precipitation descended to the ground, wind shear caused the near-surface portion of the Ze plume to lag the upper-level portion so that A′ appeared tilted (Fig. 6, legs 7–8). During UWKA legs 6–10, near-surface Ze increased from 5 to 15 dBZe as A′ passed over higher terrain. Line B′ was observed by the WCR for the first time at 1717 UTC, 15 km downwind of PJ between 3.5 and 4.5 km MSL (Fig. 6, leg 6). Similar to A′, snow began to fall out during the next 30 min. Within B′, Ze reached a maximum 15 dBZe as it propagated over higher terrain. In both A′ and B′, Ze at 3–4.5 km remained between 5 and 15 dBZe for up to 80 min after the seeding material was released, indicating continued particle nucleation and growth in the upper portion of the cloud. Both lines became tilted once the precipitation plume descended below ~3 km as a result of wind shear between the surface and higher altitudes.

Fig. 6.
Fig. 6.

Evolution of Ze from the WCR during UWKA legs 4–10 on 19 Jan. Times given indicate the beginning and end of each leg, and arrows indicate flight direction for that leg. In all cases, wind is from left to right. A clear signal from seeding line A is detected in all seven legs. Seeding line B is detectable in the last five legs. Thick, solid lines contour regions of enhanced reflectivity caused by seeding. Dashed lines show similar regions of increased reflectivity from seeding that are interspersed with areas of natural reflectivity enhancement. The white belt is the WCR blind zone centered at flight level.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

Continuous lines of enhanced reflectivity were not identified from seeding legs C–F. These lines would have been expected to form upwind of A′. Cross sections from the WCR for UWKA legs 6–10 showed a significant decrease in cloud top, from 4.5 km during the time of legs A–B to <3 km when legs C–F were flown. Seeding material from flares released during legs C–F at 4.4 km would not have reached the cloud top and, therefore, no lines developed.

c. Ice initiation and particle growth

During legs 4–10, the UWKA made repeated passes through A′ and B′, 0.5 to 1 km below cloud top with −11° < T <−14°C, near or below the level at which the AgI was released (Fig. 6). Seven and five passes were respectively made through A′ and B′, ranging from 5 to 95 min after the seeding occurred. On leg 4, 20 min after seeding occurred, the UWKA was 1 km below cloud top at T = −11°C and the WCR detected A′ above flight level with Ze ~ 5 dBZe. The Ze at flight level was −15 dBZe, indicating the precipitation in A′ had not yet descended to flight level (Fig. 7c, leg 4). The cloud at flight level consisted of liquid cloud droplets of 20–30 μm in diameter D and was nearly devoid of ice particles (Figs. 7a,b; leg 4). The LWC was between 0.01 and 0.05 g m−3 directly beneath the seeding line and as high as 0.08 g m−3 a few kilometers downwind. During leg 5, 10 min later at the same level, measurements within A′ showed that the seeding line had descended through the flight level and reflectivity had increased to 10 dBZe (Fig. 7c, leg 5). Consequently, the concentration of cloud droplets (D < 50 μm) had been depleted and the concentration of larger, ice particles (D > 100 μm) had increased by two orders of magnitude (Figs. 7a,b; legs 4–5). The observed LWCs within A′ at this time were < 0.01 g m−3 and ice water contents (IWC) were > 0.10 g m−3. A marked and rapid transition from liquid dominated to ice dominated cloud in A′ had occurred at this level in just 10 min. Few pristine ice crystals were observed just after this transition during leg 5 and most of the ice appeared to be irregularly shaped, suggesting some amount of riming had occurred (Fig. 7b, leg 5). Another five passes through A′ were made over the ensuing 60 min in legs 6–10, and in all cases the observed LWC remained < 0.01 g m−3 (Fig. 7c, legs 6–10) and the concentration of hydrometeors D < 50 μm remained < 1 cm−3. However, the concentration of larger ice particles continued to exceed, by two orders of magnitude, the concentration observed during the earliest pass and in regions just upwind and downwind of A′. By 50 min after seeding, two-dimensional stereo probe (2DS) images confirmed the presence of dendritic crystals within A′ (Fig. 7b, leg 6). Dendritic crystals were observed in all subsequent legs within A′, interspersed with irregular shaped ice (Fig. 7b, legs 7–10).

Fig. 7.
Fig. 7.

(a) Hydrometeor size distributions measured by the in situ probes on the UWKA in line A′ during UWKA legs 4–10 on 19 Jan sampled between 1640 and 1816 UTC. (b) Particle images from the 2DS from seeding-line passage are shown. The frame size is 1.6 mm from top to bottom as indicated in the top frame; the labels on the right indicate the UWKA leg number and the duration between the release of the seeding material and sampling by the UWKA. (c) Vertical profiles of Ze from the WCR in seeding line A for each of the UWKA legs shown in Fig. 5. Each box is 8 km wide and 4 km tall [leg number and time are on the bottom, as in (b)]. The gray bar indicates that portion of the UWKA track that was in the seeding line for each of the seven passes and used for the size distribution in (a). Maximum LWC observed at flight level within the seeded line is indicated on the top.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

Observations within B′ suggest a similar microphysical evolution (Fig. 8). During UWKA legs 4–5, at 5 and 15 min after seeding, no reflectivity signature was detected by the WCR (Fig. 8c, legs 4–5). For these legs, we estimated the expected location of B′ (had it been detected) using the AgI release time, location along B, and assumed that B is being advected with the mean wind at flight level. During leg 4, the UWKA measured LWC in this region was 0.03 g m−3. A significantly smaller amount of LWC was observed in leg 5 and likely resulted from a local lowering of the cloud top. LWCs just a few kilometers on either side of this were between 0.03 and 0.08 g m−3 (not shown). During both legs 4–5, the clouds at flight level were nearly devoid of ice and dominated by relatively small supercooled liquid droplets (Fig. 8b, legs 4–5). B′ was detected by the WCR with a reflectivity of 5 dBZe during leg 6, 30 min after seeding (Fig. 8c, leg 6). LWC within B′ at flight level was 0.01 g m−3, particle images revealed some rimed ice, and particle size distributions showed a decrease in concentration of cloud droplets and an increase in larger hydrometeors (Figs. 8a–c, leg 6). Of the four remaining legs 7–10, only during leg 9 was the LWC > 0.01 g m−3 within B’ (Fig. 8c, legs 7, 8, and 10). During this leg, 75 min after seeding, cloud LWCs up to 0.03 g m−3 were observed, over higher terrain, nearly 60 km downwind of where the AgI was released. These higher LWCs were collocated in regions of ice hydrometeors concentrations of 2–3 L−1 (Fig. 8a, leg 9) resulting in particle images that appear more irregular and hence more rimed than was observed throughout much of A′. For observations in both A′ and B′, total ice concentrations with D > 100 μm never exceeded 21 L−1. Also, once ice was initiated within the A′ and B′, size distributions for ice hydrometeors with D > 1 mm (Figs. 7a and 8a) were remarkably consistent across all penetrations. Crystals of this size likely resulted from aggregation of smaller, dendritic ice crystals leading to the development of an exponential size distribution of these larger particles (Field and Heymsfield 2003)

Fig. 8.
Fig. 8.

As in Fig. 7, but for line B′ on 19 Jan.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

d. Snow growth and fallout

As the seeding lines passed through the ROD, ice crystals and snow continued to grow, generating snowfall on the ground (Fig. 9). Between the first detection of A′ by the PJ radar at 1654 UTC (15 min after seeding) and the time A′ passed over PJ at 1706 UTC (36 min after seeding), Ze and Zdr increased from 3 to 7 dBZe and 0.6 to 1.8 dB, respectively (Fig. 9a). Between 25 and 40 min after seeding, the values of Ze < 10 dBZe and 1 < Zdr < 1.5 dB near cloud top (3–4 km; −8° < T < −12°C) suggest that snow most likely grew through water vapor deposition (Ryzhkov and Zrnic 1998; Moisseev et al. 2009; Kennedy and Rutledge 2011; Bechini et al. 2013; Schneebeli et al. 2013). Within 40 min after seeding, weak up- and downdrafts (1–2 m s−1) were observed within A′ by the WCR (Fig. 10, UWKA leg 6). A change in dual-polarization variables started 48 min after seeding (1718 UTC) and lasting for 15–20 min (Fig. 9). Near cloud top (3–4.5 km MSL), pockets of enhanced Kdp (>1° km−1) and Zdr (0.6–1.2 dB) with updrafts up to 1.5 m s−1 were present. The updrafts near cloud top (Fig. 10, leg 8) may be associated with additional orographic lift that A′ experienced moving up the North Folk Range between 1724 and 1748 UTC after passing PJ (Fig. 9).

Fig. 9.
Fig. 9.

RHI composite between 1654 and 1742 UTC along the flight track at 39° azimuthal direction on 19 Jan showing dual-polarization variables for (a) line A′ and (b) line B′ with Kdp on the top plot, Zdr in the middle plot, and Ze in the lower plot. Terrain is indicated in dark-gray shading The cone of silence and the area below the lowest radar beam are indicated in light-gray shading. PJ is shown as a star symbol, and the North Folk Range is highlighted. Temperatures were derived from the nearest sounding at 1600 UTC at Crouch (location shown in Fig. 2). Radar times are indicated in the top plot; minutes after seeding are in the middle plot. Red shading indicates the altitude range of the UWKA flight tracks.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

Fig. 10.
Fig. 10.

Similar to Fig. 6, but for the evolution of near-vertical Doppler radial velocity from the WCR during UWKA legs 6–8 on 19 Jan. Blue shades indicate upward motion, and red shades indicate downward motion. Note that the color scale has been shifted by 1 m s−1 to account for an expected nominal terminal fall velocity of the main scatterers. In this context blue and red regions respectively indicate areas of upward-moving and downward-moving air. Black lines contour regions of enhanced reflectivity caused by seeding.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

The dendritic growth layer (DGL) can be identified from dual-polarization observations as an enhancement in Zdr and Kdp, reduced ρhv, and a strong vertical gradient in Ze (e.g., Hogan et al. 2002; Kennedy and Rutledge 2011; Lamb and Verlinde 2011; Andrić et al. 2013; Bechini et al. 2013). These changes occur because dendrites enable rapid aggregational snow growth as the crystal branches more readily interlock (Pruppacher and Klett 1997). The enhancement in Kdp and Zdr near cloud top occurred within −10° < T < −15°C where vigorous growth of dendritic ice particles is expected (Takahashi et al. 1991; Fukuta and Takahashi 1999). Enhanced dendritic growth near cloud top, starting at about 36–48 min after seeding, was also supported by images of particles from the 2DS that showed more dendritic crystals during leg 6 (50 min after seeding) than during leg 5 (30 min after seeding; Fig. 7b). In fact, this enhancement of Kdp (>1° km−1) and Zdr (0.6–1.2 dB) around 3.8 km or −13°C was observed along the length of A′ as the line encountered higher terrain between 1724 and 1748 UTC 54–78 min after seeding (not shown). Zdr and Kdp ranged mainly between −7 and 0 dB and between 0° and 0.5° km−1, respectively, between 1654 and 1712 UTC, while positive Zdr and Kdp up to 1.5 dB and 1.6° km−1 were observed after 1718 UTC. Within the DGL, steady weak updrafts up to 1.5 m s−1 were observed (Fig. 10, leg 7). These updrafts were likely associated with additional orographic lift that A′ experienced as it passed the peak of the North Folk Range at 1730–1742 UTC (Figs. 9a and 10, legs 7–8). As the clouds associated with A′ passed through the ROD, reflectivities remained between 0 and 9 dBZe at cloud top (3–4 km MSL). While no information of AgI concentration downwind of PJ is available, it is hypothesized that ice initiation continuously occurred as unactivated residual AgI was transported farther downward and updrafts, associated with higher terrain, provided SLW during local orographic ascent. As precipitation descended to the ground, wind shear caused the near-surface portion of A′ to lag the upper-level portion so that A′ appeared tilted (Fig. 9a). The snow associated with A′ reached the ground within 42–48 min after seeding with Ze > 10 dBZe, Kdp < 0.5° km−1, and downward Vr of 3 m s−1 below 2 km MSL (Fig. 10). These values suggest heavily rimed particles.

Similar evolution and microphysical processes were observed within B′ (Fig. 9b). Line B′ was first observed at 1706 UTC (~20 min after cloud seeding) at 4–4.5 km MSL downwind of PJ, but still upwind of the North Fork Range (Fig. 2). As B′ passed over the upwind side of the North Fork Range, Ze and Zdr increased from 1 to 10 dBZe and from 0.3 to 1.8 dB, respectively. Passage of the line through the DGL was first observed in the dual-polarization variables at 1730 UTC between 3.5 and 4.5 km MSL with Kdp > 0.8° km−1 and Zdr > 1 dB in the upper part of the cloud (around 3.8 km or −13°C). Within the DGL, steady weak updrafts (<1 m s−1), associated with orographic lift similar to A′, were observed (Fig. 10, leg 8) between 1730 and 1742 UTC. Similar to A′, Ze remained between 0 and 9 dBZe at cloud top as B′ passed through the ROD suggesting, together with the steady updraft shown in Fig. 10, continuous ice initiation. The snow associated with B′ reached the ground about 36 min after seeding with Ze > 5 dBZe, Kdp < 0.5° km−1, and Vr of 1 m s−1 (Fig. 10) close to the surface (1–2 km AGL).

To further quantify these changes in microphysical processes, we conducted a quantitative analysis by calculating the mean values of dual-polarization parameters at each height and time step associated with A′ (Fig. 11). Within the DGL (~3.3–4.1 km MSL), Zdr¯ steadily decreased from −0.2 to 0.6 dB at 4.1 km MSL (T = −15°C) to −0.4–0 dB at 3.3 km MSL between 1705 to 1806 UTC. The Kdp¯ decreased only slightly within the DGL between 1705 and 1806 UTC from 0.5° to 0.6° km−1 at 4.1 km to 0.4°–0.6° km−1 at 3.3 km. A peak in Kdp¯ of 0.6° km−1 at 4 km MSL was observed between 1741–1753 UTC. Ze¯ increased below the DGL toward the surface to 10–15 dBZe most likely the result of aggregation and riming as snow fell toward the surface. A change toward more aggregated and rimed particles at the surface is seen in decreasing ρhv¯ changing from 0.99 at 1705 UTC to 0.98 between 1734 and 1806 UTC but increased slightly afterward. The enhanced snow growth, most likely related to riming, aggregation, and rapid dendritic growth above the higher terrain between 1718 and 1748 UTC, resulted in higher accumulated snowfall over the North Folk Range and Salmon River Mountains relative to the other areas downwind of PJ between 1705 and 1718 UTC (Fig. 3 in Friedrich et al. 2020).

Fig. 11.
Fig. 11.

(a) PPI of Ze at 2.8 km MSL on 19 Jan. Each plot is 50 km × 100 km. Mean dual-polarization variables are analyzed for line A′ indicated within the black box. Color bars for Ze and terrain are shown in Fig. 4. Vertical profiles of mean (b) Ze, (c) Zdr, (d) Kdp, and (e) ρhv as a function of time (color coded). Horizontal lines indicate −10° and −15°C temperatures from the 1600 UTC sounding at Crouch. Red shading indicates the altitude range of the UWKA flight tracks.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

4. Ice initiation and snow growth on 20 January

a. Natural cloud characteristics and atmospheric conditions

At cloud top (3.5–4 km), a neutral to slightly conditionally unstable atmosphere with −17° < T < −13°C was observed (Figs. 3a,b). Predominantly southwesterly flow of <10 m s−1 occurred up to 2.5 km changing to westerly flow between 2.5 and 6 km (Fig. 3c). Layers of wind shear > 0.02 s−1 were observed between 2 and 5 km MSL. The clouds formed principally over the higher terrain and did not extend far upwind of the mountain.

The UWKA flew a total of 10 legs, with seven flown in cloud. The presence of extensive pockets of supercooled drizzle with D > 100 μm, resulted in moderate icing conditions requiring that the UWKA fly three legs above cloud top. All in-cloud legs were within 1 km of cloud top at −11° < T < −14°C. Leg-averaged, in-cloud LWCs ranged from 0.1 to 0.2 g m−3 with maximum LWC along a leg ranging from 0.45 to 0.6 g m−3. Concentrations of cloud droplets were less than 30 cm−3. Observed natural ice concentrations were generally less than 0.1 L−1 except in isolated pockets over higher terrain, where concentrations at flight level were between 1 and 5 L−1.

b. Seeding operations and evolution of the seeding lines

The seeding aircraft flew eight legs (legs A–H) on a constant flight track between 0003 and 0129 UTC at an altitude of 4.1 km for legs A, F, and G, and 3.8 km for legs B–E and H (Fig. 2). LWC¯ between 0.04 and 0.28 g m−3 and T¯ = −14°C were observed along nearly the entire seeding aircraft flight track during seeding legs D, E, and H (Fig. 4b, Table 1). While legs A, B, F, and G were flown mainly (89%–100% of the flight leg) above the cloud to avoid heavy icing, with T¯ from −14° to −15°C, 59%–82% of legs C–D were also flown in cloud at T = −14°C, albeit with lower LWC values (0.11 < LWC¯ < 0.18 g m−3). As a result, only EJ flares were released during legs A, F, and G. BIP and EJ flares were used in legs B–E and H (Table 1, Fig. 4b).

Reflectivity plumes from all eight seeding legs appeared as a zigzag seeding signature pattern of lines A′–H′ (Fig. 12, Movie S2 in the online supplemental material). Background (natural) reflectivity values ranged between −30 and −10 dBZe throughout the event. Lines A′ and B′ initially consisted of circular areas or “dots” of Ze > 10 dBZe with background values from −30 to −5 dBZe and were first observed by the PJ DOW radar between 0030 and 0045 UTC ~5 km downwind of A–B at 2.6 km MSL (supplemental Movie S2). The Ze dots were associated with ice particles forming from individual EJ flares deployed during A and the beginning of B (Fig. 4b). Their 3–4 km spacing matched the average 3-km distance between flare drops. As A′ and B′ moved downwind, C′, D′, and E′ appeared between 0045 and 0124 UTC as semicontinuous lines, a result of continuous ejection of AgI through both BIP and EJ flares. Lines F′ and G′ later appeared as Ze dots between 0124 and 0143 UTC, the result of using only EJ flares along F and G. Line H′, the final line, appeared between 0142 and 0152 UTC. As the lines propagated through the ROD, they broadened quickly and merged with other lines because of the low wind speed (<10 m s−1) and shear up to 0.02–0.03 s−1 between the surface and 4 km MSL. Precipitation accumulated mainly over the higher terrain and within the ROD (Fig. 3 in Friedrich et al. 2020).

Fig. 12.
Fig. 12.

As in Fig. 5, but Ze from PJ radar for 20 Jan at (a) 0047, (b) 0116, (c) 0143, and (d) 0211 UTC.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

The UWKA flew along the NW edge of seeding lines A′–H′ and intersected the lines on their northernmost extent (Fig. 12) within a region of natural (background) Ze between −15 and −10 dBZe (Fig. 13). Because lines A′–H′ were arranged in a zigzag pattern, the UWKA intersections appeared as line pairs. Line pair A′B′ was first detected by the WCR at 0032 UTC during UWKA leg 6, 3 km upwind of PJ and 21 min after seeding (Fig. 13). At this time, pair A′B′ was confined to between 3 and 4 km MSL and was 1.5 km wide with a maximum Ze of 0 dBZe. Line pair A′B′ generated Ze plumes that extended to the surface within 18 min (Fig. 13, leg 7) and precipitated out (Fig. 13, leg 8) 35 min after pair A′B′ was first detected by the WCR. Line pair C′D′ was detected by the WCR at 0047 UTC (Fig. 13, leg 7), 15 min after the seeding aircraft turned from seeding leg C to leg D. By 0108 UTC, Ze plumes reached the surface. By leg 9, pair C′D′ was 8 km wide at 3.5 km MSL and contained Ze of 10 dBZe from cloud top to the surface. Pair C′D′ was still detectable during the UWKA’s last leg (Fig. 13, leg 10), but the maximum Ze had decreased to 5 dBZe and the width at 3.5 km narrowed to 2.5 km. Line pair E′F′ was not detected by the WCR during leg 8 but was clearly visible on leg 9, with Ze plumes reaching the surface 20 min later on leg 10. Similarly, line pair G′H′ was detected during UWKA leg 9 at 0126 UTC, just 5 min after the seeding aircraft turned from legs G and H. The Ze at this time was from −10 to −5 dBZe at 3.5 km MSL, only 5 dB greater than the natural cloud. Twenty-three minutes later (Fig. 13, leg 10), Ze within pair G′H′ had increased to 5 dBZe and extended from cloud top to 2 km MSL.

Fig. 13.
Fig. 13.

As in Fig. 6, but showing UWKA legs 6–10 on 20 Jan. Since the UWKA passed through the northwest end of the seeding lines, pairs of lines show up as a single intersect and are therefore labeled as pairs.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

Line pairs A′B′, C′D′, E′F′, and G′H′ were detected by the WCR 30, 15, 30, and 5 min after seeding occurred, respectively. For pairs A′B′ and E′F′, previous UWKA legs at 2 and 12 min after seeding, respectively, failed to detect a line. In all cases, lines were initially 1–2 km wide, and rapidly grew in width, with pairs C′D′ and E′F achieving maximum width of 6–8 km 50–55 min after seeding. For pairs C′D′, E′F′, and G′H′, the seeding lines were discernible during the last leg flown by the UWKA (Fig. 13, leg 10) from 0145 to 0149 UTC. Note also that the seeding lines drifted east of the UWKA flight track, since the UWKA flight track was not oriented directly along the mean wind (Fig. 2).

On the basis of the seeding aircraft track and the ambient winds, all seeding lines should have passed over PJ. The PJ MRR observed three distinct groups of seeding lines (Fig. 14). The first group between 0100 and 0114 UTC was related to pair C′D′. Pairs E′F′ and G′H′ passed over the MRR between 0128 and 0131 UTC and 0154 and 0159 UTC, respectively. A maximum Ze of 10 dBZe and Vr = −1 m s−1 were observed. As indicated by both the MRR and WCR measurements, none of the snow generated by seeding reached the surface at PJ but rather fell to the surface downwind.

Fig. 14.
Fig. 14.

Vertical profile of Ze (color coded) and Doppler velocity (black lines; m s−1) observed by the MRR at PJ on 20 Jan between 0045 and 0200 UTC. Seeding lines C′–H′ are labeled. Blue shading indicates the altitude range of the UWKA flight tracks.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

c. Ice initiation and particle growth

The UWKA flew 5 legs (legs 6–10) in which seeding lines were detected. Due to moderate icing conditions encountered on this day, only legs 7, 9, and 10 were in-cloud while legs 6 and 8 were above cloud. During the three in-cloud legs, three passes were made through line pair C′D′, two passes were made each through line pair E′F′ and line pair G′H′, and only one pass was made through line pair A′B′. Passes through the seeding lines were made 5–75 min after seeding occurred and within 500 m of cloud top at the T = −12°C level. Observed LWCs within the seeding lines ranged from < 0.01 to 0.143 g m−3 in pair C′D′ (Fig. 15d), 0.01 to 0.047 g m−3 in E′F′ (Fig. 15e), and 0.016 to 0.034 g m−3 in line pair G′H′ (Fig. 15f). For all particle size distributions measured at flight level within the seeding lines and 30 min or more after seeding, a distinctive “tail” of larger (ice) particles, D > 100 μm, was evident with mean concentrations of 1–4 L−1 (Figs. 15a–c). In only two cases, in pair G′H′ at 5 min after seeding and in pair C′D′ at 15 min after seeding (Fig. 15a, leg 7; Fig. 15c, leg 9), was the tail absent; note that during leg 7 in pair C′D′, 15 min after seeding, the UWKA passed underneath the level of the seeding line. The next in situ observation of pair C′D′ was not made until 60 min after seeding during leg 9, by which time particles several mm in diameter were observed (Fig. 15a, leg 9). In all cases, once ice formed, concentrations of ice particles with D > 100 μm never exceeded 26 L−1 at flight level. The Ze at cloud top began to decrease with time, as the snow precipitated out of the cloud, despite the clouds appearing to contain significant amounts of available SLW.

Fig. 15.
Fig. 15.

Hydrometeor size distributions measured by in situ probes on the UWKA in (a) lines C′D′, (b) lines E′F′, and (c) lines G′H′ corresponding to UWKA legs 7–10 on 20 Jan (cf. Fig. 7). Vertical profiles of Ze from the WCR for (d) lines C′D′, (e) lines E′F′, and (f) lines G′H′ shown in (a)–(c). Each box is 9 km wide and 5 km tall. The gray bar indicates that portion of the UWKA leg from which the size distributions were constructed. The labels below each image indicate the UWKA leg number and the duration of the gray bar. Labels above indicate the maximum LWC observed within the gray bar.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

d. Snow growth and fallout

We were unable to analyze each seeding line separately in the PJ radar data as the eight seeding lines propagated slowly toward the northeast and started to merge quickly, in particular along the northern and southern turning points of the seeding aircraft (Fig. 16a). Instead, we divided the area that the seeding lines moved through into four northwest–southeast-oriented, 8-km-wide, and 60-km-long boxes with box 1 (box 4) representing the earlier (later) stage of the seeding lines’ evolution. Widespread snowfall over more than 2000 km2, indicated by the area with Ze > 15 dBZe in Fig. 16b, was primarily observed in box 2 and box 3 between 2 and 3.5 km MSL between 0120 and 0215 UTC. The largest area of snowfall (>3000 km2) was observed at 0123 UTC in box 2 mainly associated with line pair C′D′ about 30–60 min after seeding (Fig. 16b). The largest area in box 2 (>3000 km2) was observed around 2.4–2.7 km MSL and was slightly higher, between 2.5 and 3 km MSL, in box 3 (Fig. 16b). The decrease in area below 2.5 km MSL across all boxes was mainly related to complete and/or partial beam blockage of the radar beam, which was more severe with distance from the radar (particularly by box 4) and, therefore, might not represent realistic snowfall conditions.

Fig. 16.
Fig. 16.

As in Fig. 11, but (a) PPI of Ze at 2.8 km MSL for four radar times on 20 Jan. ROD is divided into four 8 km × 60 km boxes (boxes 1–4) indicating the analysis area. Each panel is 50 km × 60 km. Vertical profiles of (b) area with Ze > 15 dBZ, (c) Ze¯, (d) Kdp¯, and (e) Zdr¯ as a function of time (color coded). Horizontal lines indicate −5°, −10°, and −15°C temperatures from the 0000 UTC sounding at Crouch. Gray shading indicates height levels that might be partially affected by radar beam blockage. Blue shading indicates the altitude range of the UWKA flight tracks.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

The magnitude of mean dual-polarization parameters (Ze¯, Kdp¯,and Zdr¯) indicate snow growth with time (Figs. 16c–e). Ze¯ increased from ~10 dBZe at 4 km to ~15 dBZe at 2.5 km during the time of maximum snowfall (0100–0230 UTC). In addition,Ze¯ increased starting at 0034 UTC and peaked at around 15 dBZe at and around 2.5 km between 0123 and 0151 UTC. Similar to Ze¯, Kdp¯ showed very little temporal and vertical change. During the main snowfall, Kdp¯ ranged between 0.3° and 0.5° km−1 with temporal variations of ±0.1. A slight increase in Kdp¯ within box 2 and box 3 occurred around 3.5 km MSL where T = −13°C. This might be an indication of dendritic growth. Between 0100 and 0230 UTC, Zdr¯ remained slightly higher (0.5–1 dB) within the DGL (2.5–4 km MSL) relative to the surface. This indication of dendritic growth was consistently observed in box 2 and box 3 and sporadically in box 1 and box 4. As dendritic growth can lead to rapid snow formation and fallout, the question still remains as to why the seeding lines precipitated out so much faster and farther upwind in comparison with 19 January. This will be explored in section 6.

5. Ice initiation and snow growth on 31 January

a. Natural cloud characteristics and atmospheric conditions

Below 2.5 km, a stable boundary layer was observed with westerly winds > 8 m s−1 and T of about 0°C (Figs. 3a,b). Above this stable layer, westerly winds increased from 8 to 40 m s−1 at 5.5 km and above (Fig. 3c). Wind shear layers (>0.03 s−1) occurred between the surface and 5.5 km MSL. The atmosphere was stable with T decreasing from −5°C at 2.5 km to −35°C at 8 km.

Cloud tops with −13° < T < −15°C were steady, between 4.8 and 5.2 km through the entire event, rarely varying more than a 100 m over a flight leg. The UWKA never penetrated more than 150 m below cloud top. Early legs identified severe icing conditions, with widespread presence of supercooled drops with D > 100 μm and some observations of supercooled drops exceeding 150 μm in diameter. The limited in situ observations on this day reveal near-cloud-top LWCs up to 0.4 g m−3 with droplet concentrations ranging from 20 to 30 cm−3.

b. Seeding operations and evolution of the seeding lines

Because of severe icing and strong winds, the seeding aircraft only flew two legs (legs A–B) deploying BIP and EJ flares continuously (Fig. 4c; Table 2) on a constant flight track between 2040 and 2105 UTC at 4.9 km MSL. Both legs were flown mainly in cloud (> 95%; Table 1) with westerly winds at about 30 m s−1 and T¯ = −13°C. LWC was < 0.5 g m−3 with LWC¯ ranging between 0.23 and 0.24 g m−3 (Fig. 4c).

Two parallel lines, A′ and A″, with Ze > 15 dBZe (in a background of < 10 dBZe) separated by about 5 km emerged from the first seeding leg (line A) at 2105 UTC, as observed by the DOW radars (Fig. 17 and Table 1; also see Movie S3 in the online supplemental material). Line A′, farther downwind, had a more continuous pattern, consistent with the burning of BIP flares. Line A″, upwind of A′, consisting of distinct comma-shaped areas of Ze, related to individual EJ flares, which dropped to lower altitudes into a weaker wind regime below the seeding aircraft flight level. The AgI from these EJ flares was vertically distributed over a depth of about 820 m below flight level, while BIP flares burned as a horizontal line at flight level. Considering shear of >0.03 s−1 between 4.8 and 4.9 km MSL, AgI from BIP and EJ flares were advected at a different wind speed causing the separation into two parallel lines. Line A′ (associated with BIPs) broadened rapidly from 3–5 to >10 km wide between 2114 and 2124 UTC (Fig. 18). Line A″ (associated with EJs) also broadened from <1 km to about 5 km wide but remained much narrower than A′. Wind shear caused the upper part of A′ and A″ to propagate faster than the lower part creating forward tilted seeding lines. Line A′ reached the surface with Ze > 15 dBZe at about 2114 UTC and continued to snow out mostly on the east side of the ROD (Friedrich et al. 2020). Areas with Ze > 20 dBZe at the surface were still observed as A′ moved out of the ROD (Figs. 17d, 18b). Snowfall with Ze > 20 dBZe associated with A″ started to reach the surface at 2124 UTC.

Fig. 17.
Fig. 17.

As in Fig. 11, but for Ze observed by the SB DOW radar on 31 Jan at (a) 2110, (b) 2122, (c) 2134, and (d) 2146 UTC.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

Fig. 18.
Fig. 18.

(a) Vertical west–east cross section of Ze from the UWKA flight legs 6–9. Times and flight direction are indicated. Terrain is shown in black. (b) West–east RHI scan along flight track on 31 Jan observed by the PJ DOW radar at 2114, 2124, 2130, and 2142 UTC. UWKA flight legs 6–9 and the position of the aircraft are indicated as a red line and red aircraft symbol. Lines A′ and B′ indicate the BIP flares, and lines A″ and B″ are the EJ flares. Dark-gray shading indicates topography; lighter-gray shading indicates approximated radar coverage.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

The same pattern of two parallel lines of Ze > 15 dBZe in a background of <10 dBZe emerged after seeding leg B. The northern part of B′ and B″ was first observed at 2122 UTC, with B′ quickly merging with A″ at 2129 UTC (Fig. 17c). At 2134 UTC, most of the lines had merged or had left the ROD.

c. Snow growth and fallout

The first seeding lines were observed about 30 min after seeding. Initially, echoes associated with EJ flares were smaller in size and occurred downwind of the BIP flares (Fig. 19a). Since both EJ and BIP flares merged within 10–15 min of radar detection and quickly moved out of the ROD, we analyzed spatiotemporal dual-polarization variables combined within both seeding legs. Dual-polarization variables indicated a rapid increase in snowfall and increase in the size of the seeding lines over 36 min. Below 3.5 km MSL, Ze¯ increased with time from ~7 dBZe at 2110 UTC up to 15 dBZe at 2134 UTC (Fig. 19b). Over the same time, Ze¯ between 4 and 4.5 km MSL increased from ~7 to 13 dBZe. Note that at and after 2134 UTC parts of the seeding lines already moved out of the ROD causing Ze¯ to decrease after 2134 UTC (Fig. 19b). An increase in Ze¯ with decreasing height was primarily observed after 2129 UTC indicating a rapid increase in particle diameter. Note that the increase in Ze¯ with decreasing height in line A′ was already observed at 2114 UTC and later occurred persistently in all seeding lines (Fig. 18b). Little change in Zdr¯ with decreasing height was observed between 2117 and 2134 UTC; except for a slight increase in Zdr¯ of 0.3 dB with decreasing height at 2110 UTC (Fig. 19c). However, a peak in Zdr¯ was observed at 2141–2146 UTC at about 4.3 km (−13°C) with an increase in Ze¯ below 4 km indicating the possibility of dendritic growth. While Kdp¯ also remained relatively constant with decreasing height, a slight increase in Kdp¯ was observed at 2110 and 2146 UTC in the DGL (Fig. 19d). ρhv¯ profiles showed higher values at earlier (2110 UTC) and later times (2141–2146 UTC; Fig. 19e). All profiles showed a decrease of ρhv¯ with decreasing height indicating a broadening of different hydrometeor types and shapes.

Fig. 19.
Fig. 19.

As in Fig. 11, but showing (a) PPI of Ze at 2.8 km at six radar times on 31 Jan. Each plot is 50 km × 95 km. Vertical profiles of mean (b) Ze, (c) Zdr, (d) Kdp, and (e) hv over all seeding lines. Horizontal lines indicate −10° and −15°C temperatures from the closest sounding at 1600 UTC sounding at Crouch. Green shading indicates the altitude range of the UWKA flight tracks.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

6. Influence of environmental conditions and seeding methods on snow amount and distribution

Friedrich et al. (2020) used a selection of reflectivity–snowfall relationships, precipitation gauge analysis, and the reflectivity fields discussed here to estimate total liquid equivalent snowfall (LESnow) for the three days. For more information on accuracy and range of snowfall estimates, we refer the reader to Friedrich et al. (2020). The largest amount of LESnow within the ROD was observed on 31 January with 339 540 m3 over 2410 km2 following 19 min of seeding (Friedrich et al. 2020; Table 3). The second largest LESnow, 241 260 m3 over 1838 km2 was on 20 January following 82 min of seeding. The smallest amount, 123 220 m3 over 2327 km2, occurred on 19 January with 26 min of seeding (Friedrich et al. 2020). Snowfall on 19 January was distributed over the ROD with accumulations of 0.05–0.14 mm. On 20 January snowfall mainly accumulated over an area 80% of the size of that on 19 January with accumulations of 0.05–1.5 mm (Fig. 3 in Friedrich et al. 2020). Snow accumulation on 31 January ranged between 0.05 and 0.25 mm. Seeding rates and amounts and environmental conditions must be responsible for how much (and whether) AgI is activated, how AgI and subsequent snowfall is transported and dispersed, and how it ultimately is distributed as snowfall on the mountains. Here, we consider what factors might have been responsible for the differences in total accumulation and spatial distribution in these three cases.

Table 3.

Summary of measurements during the three events discussed here.

Table 3.

The three cases discussed here had similar cloud-top temperatures ranging from −13° to −15°C, natural ice particle concentrations of 1–5 L−1, and cloud droplet concentrations < 30 cm−3 (Table 3). Differences were in the amount of AgI released, cloud-top altitude, LWC along and downwind of the seeding aircraft track, wind speed, and shear.

a. Impact of AgI amounts

Ice nucleation efficiency of AgI has been explored in experimental and theoretical studies (e.g., DeMott et al. 1983; DeMott 1995; Boe and DeMott 1999; Xue et al. 2013; Marcolli et al. 2016). Ice nucleus (IN) size and concentration has been identified as controlling ice formation, together with temperature, water vapor saturation, and cloud droplet, which will be discussed in the following sections. Particle size distribution generated by burning AgI flares depends on updraft strength with larger-sized particles occurring during weaker updrafts (DeMott et al. 1983). Since IN size and number concentration observations are not available, we chose to use the total AgI mass as a proxy ice nuclei production acknowledging that the same mass of AgI can lead to different size and number concentration under varying environmental conditions. Ultimately, the ice particle concentrations observed serves as a direct measure of how many ice nuclei actually activated within the seeding plumes.

A total of 445 g of AgI from EJ and BIP flares was released on 20 January from eight seeding legs over approximately 82 min, while on 19 and 31 January, only 20% and 40% of the amount released on 20 January (87 and 178 g AgI), respectively, was distributed over two flight legs in about 19–26 min (Table 3). Despite releasing only 40% as much AgI on 31 January relative to 20 January, the amount of LESnow produced on 31 January was 29% more than was produced on 20 January. Further, the amount of LESnow produced on 20 January was only 2 times that amount produced on 19 January, despite releasing about 5 times as much AgI. Clearly, more AgI did not necessarily produce more LESnow, hinting that atmospheric conditions might play an essential role in the amount and distribution of snowfall. For 1 g of AgI released, 1901 m3 of total LESnow was generated on 31 January, 1409 m3 on 19 January, and 542 m3 on 20 January. This implies that environmental conditions must have played an important role in the amount and distribution of snowfall produced through seeding.

b. Impact of LWC and T along the seeding track

Ice yield also depends temperature and LWC (e.g., DeMott et al. 1983; DeMott 1995; Boe and DeMott 1999; Xue et al. 2013; Marcolli et al. 2016). In a cloud chamber experiment, Boe and DeMott (1999) quantified the number of nuclei generated per gram of AgI as a function of temperature and LWC for BIP flares. In this experiment, the yield of ice crystals increases as T decreases from −5.5° to −10.2°C with constant LWC. As T remains constant at −6° and −10°C, more yield was found when LWC = 0.5 g m−3 rather than 1.5 g m−3.

The T along the seeding track only fluctuated by 1°–2°C between the days with −14°C during legs A and B on 19 January, from −15° to −14°C on 20 January, and −13°C on 31 January (Fig. 4). LWC¯ > 0.23 g m−3 was observed along both seeding legs (A and B) on 31 January and two seeding legs (E and H) on 20 January, while all other in-cloud legs (A–D) on 20 January and every leg on 19 January had LWC¯ ranging from 0.04 to 0.18 g m−3 (Table 1). Although the observations do not reveal information on how much AgI was activated, legs D, E, and H on 20 January had the highest measured LWC¯ on that day and lines D′, E′, and H′ showed higher Ze values (peak at 30 dBZe) relative to A′, B′, and G′ with Ze peaks of <20 dBZe (Fig. 12). Lines D′, E′, and H′ also persisted longer (1–2 h) than the other lines on 20 January where snow fell out before 1 h (Fig. 12). Lines D′, E′, and H′ had higher total AgI discharge (>63.2 g per leg) relative to other legs on this day (30.8–66.8 g), with the exception of C′, which totaled 66.8 g of AgI. These observations are consistent in that lines with higher LWC and greater mass discharge of AgI persisted longer and with higher Ze values than the other lines on this day.

On 31 January, the LWC¯ was similar for both legs (0.24 and 0.23 g m−3 for legs A and B, respectively). Also, for both legs the discharge of AgI was comparable (94.8 vs 83.8 g). The resulting seeding lines from BIP (A′ and B′) and EJ flares (A″ and B″) had similar peak Ze, respectively, with higher values associated with the BIP-related lines (30 dBZe for A′ and B′ and 20 dBZe for A″ and B″). Seeding lines persisted as they both advected through the entire ROD. LWC¯ for the two legs (A and B) on 19 January was 0.11 and 0.17 g m−3. The amount of AgI released on these legs was nearly the same (44.8 and 42.6 g). Both legs had a similar maximum Ze (30 dBZe) and persisted for a similar length of time (45 min).

Within a single day, our observations suggest that higher LWC¯ along the seeding track and greater amounts of AgI release correspond to lines with greater Ze that persist longer. However, this relationship does not necessarily hold when comparing across days. Lines associated with higher LWC¯ along the seeding track (19 January: A and B; 20 January: C, D, E, and H; 31 January: A and B) show similar peak Ze of 30 dBZe. However, the width of the seeding line and the persistence within the ROD differs. The widths of the seeding lines on 19 and 20 January are similar, whereas snow fell out rapidly over a smaller area producing 51% more snow on 20 January relative to 19 January (Fig. 3 in Friedrich et al. 2020). On 30 January, seeding lines were wider, covering the largest areas (2410 km2) and the largest amount (339 540 m3) of snowfall among the three cases. This implies that LWC¯ along the seeding track plays an important role for ice initiation and formation of the seeding lines. Yet, enhanced riming might determine how fast snow falls out and wind speed and shear determines AgI dissemination and transport across the ROD.

c. Impact of LWC downwind of the seeding track

While it is important to consider the amount of the LWC along the seeding track, one should also consider how the amount and persistence of LWC downwind of the seeding track may influence the evolution and persistence of seeding lines. The ability for the UWKA to obtain in situ measurements downwind of the seeding track varied by day, due mainly to the presence of supercooled drizzle and its impact on airframe icing. On all three days, cloud droplet concentrations were < 30 cm−3 and mean cloud droplet diameters ranged from 20 to 30 μm (Table 3). UWKA-measured in-cloud LWC¯ was 0.1–0.2 g m−3 on all three days. However, on 31 January the UWKA conducted only a few flight legs in cloud, and those were always within 150 m of cloud top, whereas on 19 and 20 January flight legs penetrated deeper into the cloud, typically 500–1000 m below cloud top. Maximum LWCs observed along legs were greatest on 20 January (0.45–0.6 g m−3) and least on 19 January (0.3–0.4 g m−3). From the UWKA measurements available from 31 January, LWCs appeared to be steadier through the length of the legs than on 19 and 20 January.

On 19 January, supercooled drizzle drops were observed in isolated pockets and seldom exceeded 100 μm in diameter. On 20 January, drops with D < 150 μm were observed and occurred more extensively than on 19 January, often along one-third to one-half of a UWKA flight leg. The most supercooled drizzle was observed on 31 January. During the few cloud penetrations made by the UWKA, supercooled drizzle was widespread, with 100 < D < 200 μm.

Across the three days, the greatest amount of LESnow produced through seeding occurred on the day with the largest and most widespread occurrence of supercooled drizzle (31 January). One might conjecture that LWC was also more widespread on this day hence leading to greater drizzle production. However, the inability of the UWKA to penetrate more than 150 m below cloud top made comparison between days difficult. It is clear that the day with the least supercooled drizzle and the lowest LWC along the UWKA flight legs downwind of the seeding track (19 January) produced the smallest amount of LESnow through seeding.

d. Impact of wind shear

The question remains as to why 29% more total LESnow accumulated on 31 January relative to 20 January despite similar values of LWC and AgI released and why seeding lines precipitated out faster on 20 January than on 19 January. Although the observations do not provide information on AgI dispersion and spatiotemporal AgI concentration, we hypothesize that strong shear leads to more efficient dispersion of AgI within supercooled clouds resulting in rapid and efficient precipitation formation, which can be tested in future modeling work. Shear at and below seeding level was ~0.01 s−1 greater on 20 and 31 January than on 19 January (Table 3) resulting in more efficient dispersion of AgI. In particular, the rapid decrease in wind speed with decreasing height (40–30 m s−1 between 4 and 5 km) on 31 January led to a separation of the BIP and EJ flares, which was not observed on 19 and 20 January. This separation of flares shown in the Ze fields further suggested that AgI was activated and distributed over a much larger area (Figs. 17, 18) than on 19 and 20 January (Figs. 5, 6, 12, and 13). The efficient AgI dispersion on 31 January, in combination with greater LWC along and downwind of the seeding track and most supercooled drizzle observed, contributed to the largest area covered by snowfall (2410 km2), highest peak snowfall at 0.25 mm, and highest total accumulations of 339 540 km2 on 31 January as compared with 19 and 20 January (1838–2327 km2; 0.14–1.5 mm; 123 220–241 260 m3; Table 3). Interestingly, on 31 January, reflectivity plumes associated with BIP flares resulted in qualitative larger seeded areas (larger area of Ze > 0 dBZe) relative to EJ flares (Fig. 18).

e. Impact of wind speed

While shear affects AgI dispersion, stronger winds will transport ice particles produced through seeding farther downwind. Winds at the seeding level were strongest on 31 January, with seeding lines remaining only 30 min in the ROD, with not all snow reaching the surface inside the ROD. Conversely, winds were weakest on 20 January and on this day the seeding lines mostly reached the surface within the ROD, approximately within 40 km downwind of the seeding legs. On 19 January, winds were 5–8 m s−1 stronger than on 20 January and 12–25 m s−1 weaker than on 31 January. LESnow on 19 January was almost equally distributed over the ROD, whereas on 20 January snowfall mainly accumulated over an area one-half of the size of that on 19 January (Fig. 3 in Friedrich et al. 2020). Wind speed, therefore, played a role in the residence time of seeding lines within the ROD and the resultant distribution of snowfall.

f. Impact of ice particle growth mechanisms

In situ observations of crystal concentrations and habits were made on both 19 and 20 January. On both days, the approximate time between the release of AgI and the development of a seeding line with Ze > 5 dBZe was 15–30 min. After seeding lines were detected by the UWKA, ice particle concentrations remained, on average, between 2.5 and 8 L−1 on 19 January and slightly less (1–3.8 L−1) on 20 January. Also, IWC within seeding lines ranged from 0.1 to 0.48 g m−3 on 19 January and 0.1–0.27 g m−3 on 20 January. Despite these lower values on 20 January, more LESnow was produced and the lines precipitated out faster on this day.

As noted earlier, LWC measured by the UWKA was greater on 20 January and supercooled drizzle was more prevalent. This may have resulted in more riming. Indeed, images of ice crystals from the UWKA suggest this to be the case, leading to more rapid fallout. Unlike 20 January, the radar returns on 19 January persistently maintained strong echoes (Ze > 5 dBZe) near cloud top. Evidence of dendritic growth in the upper part of the cloud was continuously observed as the seeding lines passed through the ROD. We hypothesize that ice initiation continuously occurred as unactivated residual AgI was transported farther downwind and updrafts, associated with encountering higher terrain, provided SLW as a result of local orographic ascent. This likely aided in the persistence of the seeding lines on 19 January as compared with 20 January.

g. Impact of snow growth mechanisms

Snow growth mechanisms were similar for all three cases. Dendritic growth was observed in the upper part of the clouds where −10° < T −15°C as the seeding lines passed through the ROD. Snow growth related to riming and aggregation occurred closer to the surface, based on radar polarization signatures. The largest increase in Ze with decreasing height was observed on 31 January (6.25 dBZe over 1 km), the day with the greater LWC along and downwind of the seeding track, most supercooled drizzle, and the largest LESnow. On 20 January, Ze increased by 4.6 dBZe over 1 km with decreasing height, while 3 dBZe over 1 km was observed on 19 January. These increases occurred close to the surface below the dendritic growth zone. Snowfall at the surface was first observed 12 min after seeding on 31 January and 40–45 min on 19 and 20 January (Table 3; Friedrich et al. 2020). Rapid fallout of snow, highest LWC, and highest Ze gradient led to the conclusion that heavy riming must have occurred on 31 January. Riming most likely also occurred on 19 and 20 January, but to a lesser degree. In comparing 19 and 20 January, it is seen that snow fell out faster on 20 January, the day with higher LWC, extensive regions of supercooled drizzle droplets with 50 < D < 150 μm, and more AgI release (445 vs 87.4 g).

Cloud-top heights were the highest on 31 January and lowest on 19 January (Table 2). The primary impact of cloud-top height is to affect the residence time of snow in the air prior to impacting the mountain when seeding is conducted near the cloud top. Given similar winds, longer residence times shift the snow farther downwind across the target area.

7. Conclusions

Ice and snow production and microphysical processes for three airborne cloud-seeding events with well-defined, traceable plumes of enhanced reflectivity were quantified and environmental conditions were studied using airborne and ground-based remote sensing and in situ observations. Figure 20 summarizes the evolution of the seeding lines and the distribution of snowfall during the three cases discussed here. As AgI interacted with the SLW cloud, droplets started to freeze and continued to growth first through deposition and then through riming and aggregation. Wind shear resulted in vertical tilt of the seeding lines. During weak wind conditions (Fig. 20a; 19 and 20 January), rapid growth caused snow falling out 40–45 min after seeding with the heaviest snow accumulating 10–30 km downwind of the seeding track (Friedrich et al. 2020). During snow growth, Ze generally increased with decreasing height. However, along some seeding segments on 19 January, Ze remained enhanced near cloud top. It is hypothesized that ice initiation continuously occurred as unactivated residual AgI was transported farther downward and updrafts, associated with higher terrain, provided SLW during local orographic ascent. As a result, snow was more equally distributed downwind of the seeding tack on 19 January than on 20 January. During strong wind conditions (Fig. 20b; 31 January), snow fell out 12 min after seeding but was transported farther downwind with the heaviest snow accumulating beyond 20 km downwind. Between the three cases, the largest amount of LESnow was observed on 31 January.

Fig. 20.
Fig. 20.

A conceptual illustration of the seeding lines and snowfall with (a) weak horizontal winds (19 and 20 Jan) and (b) strong horizontal winds on 31 Jan (modified Fig. 1 in French et al. 2018). The top plots show temporal evolution of the seeding lines, with yellow–orange–red colors indicating locations and relative magnitude of Ze as a vertical cross section along the UWKA flight track. The bottom plots show a plain view of the distribution of total accumulated liquid equivalent snowfall with intensities increasing from yellow to orange to red colors [modified from Friedrich et al. (2020)]. Observations are limited to the maximum radar range; accumulations most likely occurred farther downwind and beyond the radar range. Yellow dots show locations of ground-based radars, the solid and dashed lines represent a typical flight track for the seeding or Wyoming King Air aircraft, respectively.

Citation: Journal of Applied Meteorology and Climatology 60, 7; 10.1175/JAMC-D-20-0206.1

The distribution and amount of snowfall was also linked to the amount of AgI released and the temporal and spatial evolution of atmospheric variables. While the experimental design, cloud-top temperatures, natural ice particle concentrations, and cloud droplet concentrations were similar during the three seeding events, the amount of AgI released, wind speed and shear, LWC along and downwind of the seeding track, and the presence of supercooled drizzle drops differed. The findings from this study can be summarized as followed:

  • More AgI did not necessarily produce more liquid equivalent snowfall (LESnow). The day (20 January) with the most AgI released (445 g) only produced the second greatest amount of total LESnow (241 260 m−3).

  • LWC along the seeding track plays an important role for ice initiation and formation of the seeding lines. Seeding legs with LWC¯ > 0.23 g m−3 and greater amounts of AgI release (>63.2 g per leg) correspond to lines with greater Ze (peak at 30 dBZe).

  • The greatest amount of LESnow produced through seeding occurred on the day (31 January) with the largest and most widespread occurrence of supercooled drizzle and largest amount of LWC downwind of the seeding track (Fig. 20b).

  • Wind speed and shear determine AgI dissemination and transport. The day (31 January) with the strongest wind shear produced the greatest amount of LESnow. The stronger the wind is, the farther away the snowfall occurs from the seeding track (Fig. 20).

  • Degree of riming determines how fast snow falls out. Snow fell out within 15–40 min on days (20 and 31 January) with greater LWC along and downwind of the seeding track, and widespread occurrence of supercooled drizzle.

In summary, the greatest amount of LESnow, largest area covered by snowfall, and highest peak snowfall produced through seeding occurred on the day (31 January) with the largest and most widespread occurrence of supercooled drizzle, highest wind shear, and greater LWC along and downwind of the seeding track. The day (19 January) with the least supercooled drizzle and the lowest LWC along the UWKA flight legs downwind of the seeding track produced the smallest amount of LESnow through seeding.

The results from this study provide a first step toward answering the question about how environmental conditions and amount of AgI affect cloud-seeding efficacy. This study, in concert with Friedrich et al. (2020) and French et al. (2018), provides a comprehensive analysis of cloud-seeding efficacy for the three cloud-seeding events. These findings set a stage for analyzing microphysical and dynamical conditions during other cloud-seeding events observed during SNOWIE as well as validating numerical models that simulate the microphysical impacts of cloud seeding and improving interpretation of precipitation observations during cloud-seeding operations. Results can guide process modeling studies focusing on the role of atmospheric conditions and AgI amount and dispersion. Numerical modeling can also be used to explore a quantitative link between the environmental parameters, cloud and precipitation properties, AgI amount, and snowfall amount and distribution.

Acknowledgments

We thank the crews from the University of Wyoming King Air and Doppler on Wheels radars from the Center for Severe Weather Research (CSWR) as well as all students from the Universities of Colorado, Wyoming, and Illinois for their help in operating and deploying instruments during the campaign. Funding for CSWR DOWs and the UWKA was provided through the National Science Foundation (NSF) awards AGS-1361237 and AGS-1441831, respectively. Funding for seeding aircraft was provided by Idaho Power Company. The research was supported under NSF Grants AGS-1547101, AGS-1546963, AGS-1546939, AGS-2016106, AGS-2015829, and AGS-2016077. This material is based upon work supported by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by NSF under Cooperative Agreement 1852977.

Data availability statement

All data presented here are publicly available through the SNOWIE data archive website (https://data.eol.ucar.edu/master_lists/generated/snowie/) maintained by the Earth Observing Laboratory at NCAR and theSNOWIE radar data archive (ftp://snowiepi:cswrsnowie@cswrdata.org) maintained by the CSWR.

APPENDIX A

Observing Systems and Data Processing

a. Aircraft operations and instruments

The seeding aircraft released BIP and EJ flares of AgI and provided flight-level measurements of temperature and cloud liquid water content along its track (Table 1 in Tessendorf et al. 2019). Each seeding leg (solid lines in Fig. 2) was oriented perpendicular to the mean wind direction at flight level and was flown upwind of the ground-based radars. Seeding legs were repeated 2–8 times during a flight. When in cloud, the seeding aircraft released AgI with both BIP and EJ flares. The amount of AgI released during each leg is listed in Table 1. Only EJ flares were used during legs that occurred above clouds.

Detailed measurements of cloud microphysical structure were provided by instruments mounted onboard the UWKA research aircraft (Rodi 2011). The UWKA flew tracks prior to, during, and after cloud seeding. The tracks were flown along the direction of the mean wind perpendicular to the seeding aircraft legs and passed over the radar at the Packer John instrument site (dashed lines in Fig. 2). Typically, the UWKA repeated 10 flight legs over a 4-h flight period, with 2–4 legs completed prior to the start of seeding. Legs were repeated on the same track for a given flight, but tracks were rotated flight to flight, depending on wind direction. If cloud conditions allowed, the UWKA flew within the cloud, at or below the altitude at which the seeding material was released. On 19 January, all flight legs were flown below the cloud top, and on 20 January 4 of the 10 flight legs were above cloud top because of moderate icing conditions. On 31 January, because of severe icing, all legs were flown above cloud top. Therefore, remote sensing observations from the UWKA were available for all three days, whereas in situ measurements were available on two days.

Vertical cross sections of equivalent radar reflectivity factor Ze and vertical Doppler radial velocity Vr along the UWKA flight track were provided by the WCR, a W-band radar on the UWKA (Wang et al. 2012). The WCR has a minimum detectable signal of −40 dBZe at 1 km and was able to detect liquid cloud hydrometeors in the absence of ice and precipitation in the SNOWIE clouds. The Vr measurements were calibrated and corrected for aircraft motion following Haimov and Rodi (2013). The WCR provides an ~30-m (along beam; vertical) and ~15-m (along track; horizontal at 1 km) resolution.

An array of in situ instruments measured cloud dynamical, thermodynamical, and microphysical parameters along the flight track of the UWKA. Tessendorf et al. (2019) list the instruments on the UWKA. Here, we briefly describe those relevant to this study. Details of processing and related uncertainties are presented in the “supporting information” in French et al. (2018). Bulk cloud water and ice mass was provided by a deep-cone Nevzorov probe mounted on the nose of the UWKA (Korolev et al. 2013). The method for calibrating and retrieving the liquid and ice water content from the Nevzorov probe on the UWKA is discussed in Faber et al. (2018). Hydrometeor size distributions were compiled from data collected from three optical probes: a cloud droplet probe (CDP; Lance et al. 2010; Faber et al. 2018), a 2DS (Lawson et al. 2006), and a two-dimensional precipitation probe (2DP; Knollenberg 1981; Baumgardner et al. 2017). Distributions were computed for hydrometeors with diameters ranging from 2 um to several millimeters. For particles with diameters larger than 50 μm, two-dimensional images were captured that were used to identify particle type and phase.

b. Ground-based radars

Two dual-polarization scanning X-band DOW (Wurman 2001) radars were deployed, one at PJ (2138 m MSL) and the other at SB (2503 m MSL; Fig. 2) ridgetop sites. The range resolution was 50 m, and the maximum range was 50 km (gray shaded area in Fig. 2). DOW radars provided Vr, Ze, differential reflectivity Zdr, special differential phase Kdp, and correlation coefficient ρhv. The scan strategy for both radars is shown in Table 2. Friedrich et al. (2020) provide information on quality control, calibration, and ground clutter removal. The raw data were converted to quality-controlled volumetric data in Cartesian coordinates at 100-m horizontal resolution and 250-m vertical resolution for 19 and 31 January from the SB radar and for 20 January from the PJ radar. Seeding lines were isolated from the background precipitation through manual identification and masking of the surrounding Ze. To further reduce the influence of natural precipitation surrounding the seeding lines, seeding lines were defined by isolating areas of Ze > 10 dBZe. Mean dual-polarization parameters were derived as a function of height for individual seeding lines (19 January), regions containing seeding lines (20 January), or a combination of all seeding lines (31 January).

In addition to the two scanning radars, a vertically pointing Ka-band METEK Micro Rain Radar (MRR; Peters et al. 2002) was deployed at PJ. The instrument operated in a continuous wave mode at 24.23 GHz, providing vertical profiles of Ze, Vr, and spectral width at a vertical resolution of 100 m up to 5.2 km MSL (31 range gates). Data were averaged over 1-min intervals. A Doppler spectra postprocessing technique (Maahn and Kollias 2012) was implemented to improve sensitivity for snow and to dealias Doppler velocities so that vertical particle motions could be distinguished within ±12 m s−1. The first two range gates were unreliable and were removed in this postprocessing.

APPENDIX B

List of Abbreviations

AgI

Silver iodide

BIP

Burn-in-place

D

Diameter

DGL

Dendritic growth layer

DOW

Doppler on Wheels

EJ

Ejectable

IWC

Ice water content

Kdp

Special differential phase

LESnow

Liquid equivalent snowfall

LWC

Liquid water content

MRR

Micro Rain Radar

PJ

Packer John site

ROD

Radar observational domain

SB

Snowbank site

SLW

Supercooled liquid water

SNOWIE

Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment

T

Temperature

UWKA

University of Wyoming King Air

Vr

Radial velocity

WCR

Wyoming Cloud Radar

Zdr

Differential reflectivity

Ze

Radar reflectivity factor

ρhv

Correlation coefficient

REFERENCES

  • Andrić, J., M. Kumjian, D. Zrnić, J. Straka, and V. 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.

    • Search Google Scholar
    • Export Citation
  • Baumgardner, D., and Coauthors, 2017: Cloud ice properties: In situ measurement challenges. 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-16-0011.1.

  • 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.

    • Search Google Scholar
    • Export Citation
  • Boe, B. A., and P. J. DeMott, 1999: Comparisons of Lohse wing-tip generators and burn-in-place pyrotechnics in the North Dakota cloud modification project. J. Wea. Modif., 31, 109118.

    • Search Google Scholar
    • Export Citation
  • Cober, S. G., J. W. Strapp, and G. A. Isaac, 1996: An example of supercooled drizzle drops formed through a collision–coalescence process. J. Appl. Meteor., 35, 22502260, https://doi.org/10.1175/1520-0450(1996)035<2250:AEOSDD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • DeMott, P. J., 1995: Quantitative description of ice formation mechanisms of silver iodide-type aerosols. Atmos. Res., 38, 6399, https://doi.org/10.1016/0169-8095(94)00088-U.

    • Search Google Scholar
    • Export Citation
  • DeMott, P. J., W. G. Finnegan, and L. O. Grant, 1983: An application of chemical kinetic theory and methodology to characterize the ice nucleation properties of aerosols used for weather modification. J. Appl. Meteor., 22, 11901203, https://doi.org/10.1175/1520-0450(1983)022<1190:AAOCKT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Deshler, T., and D. W. Reynolds, 1990: The persistence of seeding effects in a winter orographic cloud seeded with silver iodide burned in acetone. J. Appl. Meteor., 29, 477488, https://doi.org/10.1175/1520-0450(1990)029<0477:TPOSEI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Deshler, T., D. W. Reynolds, and A. W. Huggins, 1990: Physical response of winter orographic clouds over the Sierra Nevada to airborne seeding using dry ice or silver iodide. J. Appl. Meteor., 29, 288330, https://doi.org/10.1175/1520-0450(1990)029<0288:PROWOC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Faber, S., J. R. French, and R. Jackson, 2018: Laboratory and in-flight evaluation of measurement uncertainties from a commercial Cloud Droplet Probe (CDP). Atmos. Meas. Tech., 11, 36453659, https://doi.org/10.5194/amt-11-3645-2018.

    • Search Google Scholar
    • Export Citation
  • Field, P. R., and A. J. Heymsfield, 2003: Aggregation and scaling of ice crystal size distributions. J. Atmos. Sci., 60, 544560, https://doi.org/10.1175/1520-0469(2003)060<0544:AASOIC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • French, J. R., and Coauthors, 2018: Precipitation formation from orographic cloud seeding. Proc. Natl. Acad. Sci. USA, 115, 11681173, https://doi.org/10.1073/pnas.1716995115.

    • Search Google Scholar
    • Export Citation
  • Friedrich, K., and Coauthors, 2020: Quantifying snowfall from orographic cloud seeding. Proc. Natl. Acad. Sci. USA, 117, 51905195, https://doi.org/10.1073/pnas.1917204117.

    • Search Google Scholar
    • Export Citation
  • Fukuta, N., and T. Takahashi, 1999: The growth of atmospheric ice crystals: A summary of findings in vertical supercooled cloud tunnel studies. J. Atmos. Sci., 56, 19631979, https://doi.org/10.1175/1520-0469(1999)056<1963:TGOAIC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Geerts, B., Q. Miao, Y. Yang, R. Rasmussen, and D. Breed, 2010: An airborne profiling radar study of the impact of glaciogenic cloud seeding on snowfall from winter orographic clouds. J. Atmos. Sci., 67, 32863302, https://doi.org/10.1175/2010JAS3496.1.

    • Search Google Scholar
    • Export Citation
  • Geerts, B., and Coauthors, 2013: The AgI Seeding Cloud Impact Investigation (ASCII) campaign 2012: Overview and preliminary results. J. Wea. Modif., 45, 2443.

    • Search Google Scholar
    • Export Citation
  • Geresdi, I., R. M. Rasmussen, and W. Grabowski, 2005: Sensitivity of freezing drizzle formation in stably stratified clouds to ice processes. Meteor. Atmos. Phys., 88, 91105, https://doi.org/10.1007/s00703-003-0048-5.

    • Search Google Scholar
    • Export Citation
  • Grazioli, J., G. Lloyd, L. Panziera, C. Hoyle, P. Connoly, J. Henneberger et al., 2015: Polarimetric radar and in situ observations of riming and snowfall microphysics during CLACE, 2014. Atmos. Chem. Phys., 15, 13 78713 802, https://doi.org/10.5194/acp-15-13787-2015.

    • Search Google Scholar
    • Export Citation
  • Griffin, E., T. Schuur, and A. 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.

    • Search Google Scholar
    • Export Citation
  • Haimov, S., and A. Rodi, 2013: Fixed-antenna pointing-angle calibration of airborne Doppler cloud radar. J. Atmos. Oceanic Technol., 30, 23202335, https://doi.org/10.1175/JTECH-D-12-00262.1.

    • Search Google Scholar
    • Export Citation
  • Harimaya, T., and M. Sato, 1989: Measurement of the riming amount on snowflakes. J. Fac. Sci. Hokkaido Univ., 8, 355366.

  • Hobbs, P. V., 1975: The nature of winter clouds and precipitation in the Cascade Mountains and their modification by artificial seeding. Part III: Case studies of the effects of seeding. J. Appl. Meteor., 14, 819858, https://doi.org/10.1175/1520-0450(1975)014<0819:TNOWCA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hobbs, P. V., J. H. Lyons, J. D. Locatelli, K. R. Biswas, L. F. Radke, R. R. Weiss Sr., and A. L. Rangno, 1981: Radar detection of cloud-seeding effects. Science, 213, 12501252, https://doi.org/10.1126/science.213.4513.1250.

    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., P. R. Field, A. J. Illingworth, R. J. Cotton, and T. W. Choularton, 2002: Properties of embedded convection in warm-frontal mixed-phase cloud from aircraft and polarimetric radar. Quart. J. Roy. Meteor. Soc., 128, 451476, https://doi.org/10.1256/003590002321042054.

    • 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.

    • Search Google Scholar
    • Export Citation
  • Knollenberg, R. G., 1981: Technique for probing cloud microstructure. Clouds, Their Formation, Optical Properties, and Effects, P. V. Hobbs and A. Deepak, Eds., Academic Press, 15–91.

  • Korolev, A., J. W. Strapp, G. A. Isaac, and E. Emery, 2013: Improved airborne hot-wire measurements of ice water content in clouds. J. Atmos. Oceanic Technol., 30, 21212131, https://doi.org/10.1175/JTECH-D-13-00007.1.

    • Search Google Scholar
    • Export Citation
  • Lamb, D., and J. Verlinde, 2011: Physics and Chemistry of Clouds. Cambridge University Press, 584 pp.

  • Lance, S., C. A. Brock, D. Rogers, and J. A. Gordon, 2010: Water droplet calibration of the Cloud Droplet Probe (CDP) and in-flight performance in liquid, ice and mixed-phase clouds during ARCPAC. Atmos. Meas. Tech., 3, 16831706, https://doi.org/10.5194/amt-3-1683-2010.

    • Search Google Scholar
    • Export Citation
  • Lawson, R. P., P. Zmarzly, K. Weaver, Q. Mo, D. O’Connor, B. Baker, and H. Jonsson, 2006: The 2D-S (stereo) probe: Design and preliminary tests of a new airborne, high-speed, high-resolution particle imaging probe. J. Atmos. Oceanic Technol., 23, 14621477, https://doi.org/10.1175/JTECH1927.1.

    • Search Google Scholar
    • Export Citation
  • Ludlam, F. H., 1955: Artificial snowfall from mountain clouds. Tellus, 7, 277290, https://doi.org/10.3402/tellusa.v7i3.8908.

  • 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.

    • Search Google Scholar
    • Export Citation
  • Majewski, A., and J. French, 2020: Supercooled drizzle development in response to semi-coherent vertical velocity fluctuations within an orographic layer cloud. Atmos. Chem. Phys., 20, 50355054, https://doi.org/10.5194/acp-20-5035-2020.

    • Search Google Scholar
    • Export Citation
  • Marcolli, C., B. Nagare, A. Welti, and U. Lohmann, 2016: Ice nucleation efficiency of AgI: Review and new insights. Atmos. Chem. Phys., 16, 89158937, https://doi.org/10.5194/acp-16-8915-2016.

    • Search Google Scholar
    • Export Citation
  • Mitchell, D. L., R. Zhang, and R. L. Pitter, 1990: Mass-dimensional relationships for ice particles and the influence of riming on snowfall rates. J. Appl. Meteor., 29, 153163, https://doi.org/10.1175/1520-0450(1990)029<0153:MDRFIP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Moisseev, D., E. Saltikoff, and M. Leskinen, 2009: Using dual-polarization weather radar observations to improve quantitative precipitation estimation in snowfall. Proc. Eighth Int. Symp. on Tropospheric Profiling, Delft, Netherlands, Royal Netherlands Meteorological Institute, S11-O04.

  • Moisseev, D., S. Lautaportti, J. Tyynela, and S. Lim, 2016: Dual-polarization radar signatures in snowstorms: Role of snowflake aggregation. J. Geophys. Res., 121, 12 64412 655, https://doi.org/10.1002/2015JD023884.

    • Search Google Scholar
    • Export Citation
  • Moisseev, D., A. von Lerber, and J. Tiira, 2017: Quantifying the effect of riming on snowfall using ground-based observations. J. Geophys. Res., 122, 40194037, https://doi.org/10.1002/2016JD026272.

    • Search Google Scholar
    • Export Citation
  • Murakami, M., Y. Yamada, T. Matsuo, H. Mizuno, and K. Morikawa, 1992: Microphysical structures of warm-frontal clouds. The 20 June 1987 case study. J. Meteor. Soc. Japan, 70, 877895, https://doi.org/10.2151/jmsj1965.70.5_877.

    • Search Google Scholar
    • Export Citation
  • Peters, G., B. Fischer, and T. Andersson, 2002: Rain observations with a vertically looking Micro Rain Radar (MRR). Boreal Environ. Res., 7, 353362.

    • Search Google Scholar
    • Export Citation
  • Pokharel, B., B. Geerts, X. Jing, K. Friedrich, J. Aikins, D. Breed, R. Rasmussen, and A. Huggins, 2014: The impact of ground-based glaciogenic seeding on clouds and precipitation over mountains: A multi-sensor case study of shallow precipitating orographic cumuli. Atmos. Res., 147–148, 162182, https://doi.org/10.1016/j.atmosres.2014.05.014.

    • Search Google Scholar
    • Export Citation
  • Pokharel, B., B. Geerts, X. Jing, K. Friedrich, K. Ikeda, and R. Rasmussen, 2017: A multi-sensor study of the impact of ground-based glaciogenic seeding on clouds and precipitation over mountains in Wyoming. Part II: Seeding impact analysis. Atmos. Res., 183, 4257, https://doi.org/10.1016/j.atmosres.2016.08.018.

    • Search Google Scholar
    • Export Citation
  • Politovich, M. K., 1989: Aircraft icing caused by large supercooled droplets. J. Appl. Meteor., 28, 856868, https://doi.org/10.1175/1520-0450(1989)028<0856:AICBLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Pruppacher, H. R., and J. D. Klett, 1997: Microphysics of Clouds and Precipitation. 2nd ed. Kluwer Academic, 954 pp.

  • Rangno, A. L., and P. V. Hobbs, 1991: Ice particle concentrations and precipitation development in small polar maritime cumuliform clouds. Quart. J. Roy. Meteor. Soc., 117, 207241, https://doi.org/10.1002/qj.49711749710.

    • Search Google Scholar
    • Export Citation
  • Rasmussen, R. M., B. C. Bernstein, M. Murakami, G. Stossmeister, and B. Stankov, 1995: The 1990 Valentine’s Day Arctic outbreak. Part I: Mesoscale and microscale structure and evolution of a Colorado Front Range shallow upslope cloud. J. Appl. Meteor., 34, 14811511, https://doi.org/10.1175/1520-0450-34.7.1481.

    • Search Google Scholar
    • Export Citation
  • Rauber, R. M., and Coauthors, 2019: Wintertime orographic cloud seeding—A review. J. Appl. Meteor. Climatol., 58, 21172140, https://doi.org/10.1175/JAMC-D-18-0341.1.

    • Search Google Scholar
    • Export Citation
  • Reinking, R. F., 1979: The onset and early growth of snow crystals by accretion of droplets. J. Atmos. Sci., 36, 870881, https://doi.org/10.1175/1520-0469(1979)036<0870:TOAEGO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rodi, A., 2011: King of the air: The evolution and capabilities of Wyoming’s observation aircraft. Meteor. Technol. Int., 2011 (5), 4447, http://viewer.zmags.com/publication/852ec8f8#/852ec8f8/46.

    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., and D. S. Zrnic, 1998: Discrimination between rain and snow with a polarimetric radar. J. Appl. Meteor., 37, 12281240, https://doi.org/10.1175/1520-0450(1998)037<1228:DBRASW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Schneebeli, M., N. Dawes, M. Lehning, and A. Berne, 2013: High-resolution vertical profiles of X-Band polarimetric radar observables during snowfall in the Swiss Alps. J. Appl. Meteor. Climatol., 52, 378394, https://doi.org/10.1175/JAMC-D-12-015.1.

    • 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.

    • Search Google Scholar
    • Export Citation
  • Takahashi, T., T. Endoh, G. Wakaham, and N. Fukuta, 1991: Vapor diffusional growth of freefalling snow crystals between −3 and −23°C. J. Meteor. Soc. Japan, 69, 1530, https://doi.org/10.2151/jmsj1965.69.1_15.

    • Search Google Scholar
    • Export Citation
  • Tessendorf, S. A., B. Boe, B. Geerts, M. J. Manton, S. Parkinson, and R. Rasmussen, 2019: A transformational approach to winter orographic weather modification research: The SNOWIE Project. Bull. Amer. Meteor. Soc., 96, 21952198, https://doi.org/10.1175/BAMS-D-15-00146.1.

    • Search Google Scholar
    • Export Citation
  • Wang, Z., and Coauthors, 2012: Single aircraft integration of remote sensing and in situ sampling for the study of cloud microphysics and dynamics. Bull. Amer. Meteor. Soc., 93, 653668, https://doi.org/10.1175/BAMS-D-11-00044.1.

    • Search Google Scholar
    • Export Citation
  • Williams, E. D., and Coauthors, 2015: Measurements of differential reflectivity in snowstorms and warm season stratiform systems. J. Appl. Meteor. Climatol., 54, 573595, https://doi.org/10.1175/JAMC-D-14-0020.1.

    • Search Google Scholar
    • Export Citation
  • Wurman, J., 2001: The DOW mobile multiple-Doppler network. Preprints, 30th Int. Conf. on Radar Meteorology, Munich, Germany, Amer. Meteor. Soc., 95–97.

  • Xue, L., and Coauthors, 2013: Implementation of a silver iodide cloud seeding parameterization in WRF. Part I: Model description and idealized 2D sensitivity tests. J. Appl. Meteor. Climatol., 52, 14331457, https://doi.org/10.1175/JAMC-D-12-0148.1.

    • Search Google Scholar
    • Export Citation

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