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Investigating Microphysics of Mesoscale Snowbands: Implications for Snow Forecasting

Mesoscale snowbands are significant meteorological phenomena that produce intense snowfall. They exhibit a specific structure with widths ranging from 20 to 100 km and lengths exceeding 250 km, maintaining high rainfall rates for extended periods. This study emphasizes the need for an in-depth examination of ice particle microphysics within these snowbands, particularly over the Midwest. Key processes such as riming, aggregation, and deposition influence snowfall rates and crystal types. Improved understanding is critical for enhancing model parameterizations and verification against observational data.

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Investigating Microphysics of Mesoscale Snowbands: Implications for Snow Forecasting

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  1. Microphysics in mesoscalesnowbands A modest proposal

  2. Mesoscalesnowbands • 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

  3. From Novak et al. 2004

  4. Mesoscalesnowbands • Often develop in north or northwest quadrants of extratropical cyclones • Vertical motions forced by frontogenesis • Moist symmetric instability is present (although assessment is difficult)

  5. From Novak et al. 2004

  6. Motivation • 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)

  7. Motivation • 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.

  8. 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

  9. 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. Doppler 915 MHz wind profiler

  10. From Novak et al. 2004

  11. 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)

  12. Focus on riming (accretion) • Riming growth is much faster than deposition or aggregation

  13. Deposition • =ffor spherical symmetry • ∫dm=dt • m

  14. Riming • =for spherical symmetry • ∫dm=dt • t • m

  15. Aggregation • =for spherical symmetry • ∫dm=dt • t • m

  16. 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

  17. 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)

  18. light riming (0-1)

  19. moderate riming (2-3)

  20. heavy riming (4-5)

  21. 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

  22. 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)

  23. 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

  24. Other data streams • SCSU disdrometer • Size and fallspeed information • Newly available ZDR data • It’s all about shape! • Local soundings? • Numerical modeling?

  25. 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

  26. Questions and/or comments?

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