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Justin K. Weber , Jeffrey S. Tilley 1 , David J. Delene , Matthew S. Gilmore

Relationships between Cloud Liquid Water, Cloud Droplet Number Concentration and Cloud Droplet Distribution for Summertime Convective Clouds in the Northern Plains. Justin K. Weber , Jeffrey S. Tilley 1 , David J. Delene , Matthew S. Gilmore.

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Justin K. Weber , Jeffrey S. Tilley 1 , David J. Delene , Matthew S. Gilmore

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  1. Relationships between Cloud Liquid Water, Cloud Droplet Number Concentration and Cloud Droplet Distribution for Summertime Convective Clouds in the Northern Plains Justin K. Weber, Jeffrey S. Tilley1, David J. Delene, Matthew S. Gilmore Department of Atmospheric Sciences University of North Dakota, Grand Forks, ND 58202 1Regional Weather Information Center

  2. Background • Clouds have significant impact across both large and small timescales • Weather and climate NWS JetStream

  3. Background Gamma distribution Two free parameters Cloud schemes holds both parameters fixed Shape (ν) = 1 Scale (β) = 3 Set of gamma distribution curves for integer values of the shape parameter from 1 to 10. The peaks of the curves shift progressively to the right asνincreases From Walko et. al (1995)

  4. July 13, 2010 Background z = 591 m ν = 1.361 Observed *********** Fitted Distribution z = height above cloud base ν = computed shape parameter z = 157 m ν = 1.431

  5. Background July 9, 2008 July 16, 2011 • No robust relationship across all cases

  6. Methods and Data • Analyze spectra evolution • 1 Hz • Calculate shape parameter from 5 μm to 24 μm • Instrument data best above 5 μm • New growth cloud droplets below 24 μm

  7. Methods and Data • Summertime Convective Cloud Studies • POLCAST 2 (2008) • Goodrich Corp. tests (2011) • Three Cases • Cloud penetration • Bimodal distribution • High shape parameter Forward Scattering Spectrometer Probe (2008), Courtesy Dave Delene Cloud Droplet Probe (2011)

  8. Cloud Entrance

  9. Cloud Entrance Shape = 4.50

  10. Cloud Core

  11. Cloud Core

  12. Results • Mean Diameter = β(3)*ν • Should be a relationship between shape parameter and mean diameter

  13. Bimodal Distribution • Does this occur in the same volume or in different parts of a cloud? Cloud penetration lasting 22 seconds, ~2200 m

  14. Bimodal Distribution

  15. Bimodal Distribution • No shape parameter calculated. • Fitting gamma distribution to a multiple mode distribution

  16. High Shape

  17. High Shape • Mixed phase • Temp range from -12 °C to -8 °C • High mean diameters

  18. High Shape • 2D-C Probe • Records shadows as hydrometeors pass through a laser 2D-C Ice

  19. Summary • Applying theory to observations is not straightforward • Limitations of using a gamma (single mode) distribution • Observations need appropriate filters

  20. Future Work • Calculate shape parameter using 3 μm - 24 μm data • Piecewise fit for multimodal distributions • Apply 7 μm mean diameter filter to data

  21. Acknowledgements • North Dakota Experimental Program to Stimulate Competitive Research (ND EPSCoR), through which the project was funded. • Mentorship, support, and opportunity I’ve received from Dr. Jeff Tilley, Dr. David Delene, and Dr. Matthew Gilmore

  22. Questions

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