microphysics in mesoscale snowbands n.
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Microphysics in mesoscale snowbands. A modest proposal. Mesoscale snowbands. Snow is concentrated in snowbands Snowband : linear radar reflectivity structure 20–100 km in width, >250 km in length, with an intensity >30 dB Z , which is maintained for at least 2 h (Novak et al., 2004)

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mesoscale snowbands
  • Snow is concentrated in snowbands
  • Snowband: linear radar reflectivity structure 20–100 km in width, >250 km in length, with an intensity >30 dBZ, which is maintained for at least 2 h (Novak et al., 2004)
  • Very high snowfall rates and snow totals may occur
  • Importance in forecasting is obvious
mesoscale snowbands1
  • Often develop in north or northwest quadrants of extratropical cyclones
  • Vertical motions forced by frontogenesis
  • Moist symmetric instability is present (although assessment is difficult)
  • Little is known of ice particle microphysics in snowbands over the Midwest
      • ice habits, degree of riming, fallspeeds
  • Relative importance of growth processes uncertain
    • Deposition (growth from vapor)
    • Accretion or riming(collection of supercooled droplets)
    • Aggregation (collision and “sticking” of two crystals, dendrites and thin plates most commonly)
  • How does microphysics change as thermodynamics and dynamics evolve?
  • Better model parameterizations are needed
    • There is large variability in model microphysics, thus a need for verification with observations.
to assess ice particle growth knowledge of vertical motions needed
To assess ice particle growth, knowledge of vertical motions needed
  • Vertical motions are maximized in snowbands
  • Increased flux of water vapor (mixing ratio not different, VV is)
  • This benefits deposition, but is there more to story?
  • More and larger cloud droplets: increased LWC enhances riming!
  • Residence time is increased too
vertical velocities are uncertain
Vertical velocities are uncertain
  • Theory: Emmanuel (1983) predicts ~ 1 m s-1 in CSI
  • Modeling: ~ 10 cm s-1 (e.g. Zhang & Cho, 1995)
  • Measurements:

Sanders and Bosart (1985) ~ 1 m s-1 max in N.Eng.

Houze (1981) ~ 0.8 m s-1 max in Pacific Northwest

Cronce et al. (2007) 35% > 1 m s-1, 9% > 2 m s-1 in central & southern U.S.


915 MHz wind profiler


KOKX 0.5 deg reflectivity at 1000Z 20 Dec 2009

3-km RUC at 0500Z 20 Dec 2009

Omega (μbar/s)

KOKX WSR-88D and 1from Colle et al. (2012)

focus on riming accretion
Focus on riming (accretion)
  • Riming growth is much faster than deposition or aggregation
  • =ffor spherical symmetry
  • ∫dm=dt
  • m
  • =for spherical symmetry
  • ∫dm=dt
  • t
  • m
  • =for spherical symmetry
  • ∫dm=dt
  • t
  • m
how important is riming possible methodology
How important is riming? Possible methodology
  • Observe snow crystals every 15-30 minutes under a microscope with camera
  • Classify crystals (81 types given by Magono and Lee (1966)).

• Estimate percentage of each crystal type for each observation time

  • Obtain snow density by measuring the snow volume and melted volume
assessment of riming
Assessment of riming
  • Adopt scale of Mosimann et al. (1994)
  • degree of riming based on visual observation under magnification
  • 0-5 scale (no riming to heavy riming)
what of mass in snow is due to accreted cloud droplets
What % of mass in snow is due to accreted cloud droplets?
  • Compare snowfall rates for unrimed vs. rimed crystals of varying degrees of riming
  • Feng & Grant (1982) and Mitchell et al (1990) show as much as a doubling of the snowfall rate due to riming
    • More field studies are needed!
  • Snow depth will not be increased proportionally if rimed crystals have a higher density
    • Matt Taraldsen’s SLR study (next talk) can help
importance of 15 c
Importance of -15°C
  • Dendritic mode in operation here
  • Highest growth rate by deposition here
  • Growth of dendrites by deposition and aggregation produces greatest snowfall rates and accumulations (Passarelli, 1978)
dendrites are also good rimers
Dendrites are also good rimers
  • Air passes around crystal and through it, too
  • This enhances the collection efficiency
  • Irregular rotating and tumbling fall behavior likewise helps collect droplets
  • Can occur simultaneously with aggregation (Fujiyoshi and Wakahama, 1985), as one might expect
other data streams
Other data streams
  • SCSU disdrometer
    • Size and fallspeed information
  • Newly available ZDR data
    • It’s all about shape!
  • Local soundings?
  • Numerical modeling?
ahs 452 projects anyone
AHS 452 projects, anyone?
  • Opportunities for senior research projects
  • See me if interested!

Senior Research Paper

Investigation of Critical Thicknesses for Snowman Melting

AHS 452

St Cloud State University

Spring 2013

Jane Q. Public