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Microphysical Characteristics and Evolution of Seeded Orographic Clouds

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  • 1 a Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado
  • | 2 b Department of Atmospheric Science, University of Wyoming, Laramie, Wyoming
  • | 3 c Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado
  • | 4 d Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois
  • | 5 e Idaho Power Company, Boise, Idaho
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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

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