1. 10 Dec 2007 Precipitation Uncertainty due to Variations in Particle Parameters within a Simple Microphysics Scheme Dr. Matt Gilmore DAS/UIUC (Photo Credit: NCAR/NSF) Presented 10 Dec 2007

2. 10 Dec 2007 Collaborators Jerry Straka - OU School of Meteorology Erik Rasmussen - OU/NSSL Special Thanks to Bob Wilhelmson, Adam Houston, Leigh Orf, Ted Mansell, Lou Wicker Sue van den Heever

3. 10 Dec 2007 Purpose Test precip. sensitivity to hail, snow, and rain particle characteristics in a single-moment bulk ice microphysics package (used in WRF) Can we trust precipitation forecasts from such models? Tornado forecasts? Motivate the use of more sophisticated microphysics

4. 10 Dec 2007 National Hail Research Experiment 1972-1974, 1976, Grover, CO (Photo Credit: NCAR/NSF) Examined the influence of cloud seeding on hailfall (Photo Credit: NCAR/NSF) Former division that worked on NHRE became MMM.

5. 10 Dec 2007 “... the specific sources of error must be identified in current microphysical parameterizations, and physically based improvements to the model physics must be developed, particularly for ice formation...” (MMM/NCAR Science Plan, Oct. 2000) Prediction of Precipitating Weather Systems - Cloud Microphysics and Precipitation (Photo Credit: NCAR/NSF) The Costner’s, April 1975

6. 10 Dec 2007 Top-5 Severe Weather Hazards that Caused Crop and Property Damage (1995 - 2000) Average Cost Per Year (Billions of U.S. dollars) F l o o d T o r n a d o H u r r i c a n e H a i l D r o u g h t $0.0 $1.0 $2.0 $3.0 27% 25% 11% 9% 8% Total=$11.2 Billion per Year (NWS Natural Hazard Statistics)

7. 10 Dec 2007 Hail Vulnerability Tobacco, tea, and soybeans -> numerous 5 mm hail, (Changnon 1971, 1977, 1999) Other crops, farm animals, & property -> larger hail (Largest from supercells; Changnon 2001) Could we someday forecast hail occurrence & its characteristics? (Photo Credit: NCAR/NSF)

8. 10 Dec 2007 Supercell Flooding Potential Hypothesized that supercells might contribute to climatology of extreme rainfall (100-year recurrence interval). (Smith et al. 2001, J. Hydrometeor.) e.g., dense gauge network, max rainfall rates: Orlando, FL: 330 mm h –1 (26 Mar. 1992) Dallas, TX: 231 mm h –1 (5-6 May 1995) Would cloud model flooding predictions help?

9. 10 Dec 2007 Hail Climatology Changnon and Changnon (1999) Changnon (1996) # Hail Days/year (1901- 1994) Mean Hail Diameter (cm)

10. 10 Dec 2007 Hail Forecasting Climatology Synoptic Pattern Based –See review articles by Longley and Thompson (1965); Johns and Doswell (1992). Sounding Based –Edwards and Thompson (1998) demonstrated thermodynamic parameters to be practically useless in hail severity forecasting: VIL, CAPE, maximum parcel level, EL, convective cloud depth, wet-bulb zero, freezing level. Suggested that forecasts of storm rotation be made. Progress? Reliable NWP cloud model forecasts? (We show …not yet)

11. 10 Dec 2007 Numerical Experiments Straka Atmospheric 3-D Cloud Model (SAM). Similar to the N-COMMAS model. 6th order Crowley advection on scalars. 2nd order flux scheme on momentum. Prognostic equations for u, v, w, , p, TKE, qv, qc, qr. Optional ice physics.

12. 10 Dec 2007 Model Set-up 91x91x22 km domain dx,dy = 1000 m, dz = 500 m 1°C perturbation bubble. Horizontally homogeneous environment

13. 10 Dec 2007 Experimental Design Idealized environments from Weisman and Klemp (1984). Hodographs T, T d Profile CAPE= 2200 J kg-1

14. 10 Dec 2007 Experimental Design Microphysics scheme: –Three-class bulk ice scheme (ice, snow, and hail/ graupel). [Lin et al. (1983), “LFO”] Includes warm rain scheme for cloud and rain. Referred to herein as “3-ICE” –Scheme described in Gilmore et al. (2004; MWR, August issue) –Similar schemes still being used (Purdue-Lin and WSM-6)

15. 10 Dec 2007 “3-ICE” Process Rates 6 species Single moment

16. 10 Dec 2007 Many Limitations Species are constrained to a predefined distribution function which experiences bulk/average fallout. Scheme doesn’t predict number concentration or other moments. Inconsistencies in diameter’s used for different processes (see McFarquhar & Black 2004; Potter 1991) Efficiencies are assumed constant.

17. 10 Dec 2007 Limitations (continued) Only a single graupel/hail (qh) species. Pick parameters such as the particle intercepts, densities, and fall velocity coefficients a priori (There are many more “gotchas”… but we will focus on the two above)

18. 10 Dec 2007 NHRE-Motivated Sensitivity Testing Relative Frequency 10 4 10 6 10 8 Intercept (dm -3 mm -1 ).06.12 Knight et al. (1982)

19. 10 Dec 2007 Intercept Observations Hail/graupel intercept (n oh ) (dm -3 mm -1 ) References 10 3 – 10 5 (hail) Federer and Waldvogel (1975), Dennis et al. (1971), and Spahn (1976) 10 2 – 10 6 Cheng et al. (1985) 10 4 – 10 8 graupel/hail Knight et al. (1982)

20. 10 Dec 2007 Particle Density Observations Density (kg m -3 ) Hail: 700 to 900 Graupel: 50 to 890 Hail: 400 Reference Pruppacher and Klett (1978) D. Zrnić, personal communication

21. 10 Dec 2007 Species Size Distributions Standard LFO params nono

22. 10 Dec 2007 Species Fallspeeds Larger and more dense fall faster

23. 10 Dec 2007 4x 3x

24. 10 Dec 2007 2 h accumulation of qr & qh

25. 10 Dec 2007 N3  9 Peas Dimes Golfballs

26. 10 Dec 2007 Peas Dimes

27. 10 Dec 2007 Peas

28. 10 Dec 2007 Hail counts over a 100 m 2 area

29. 10 Dec 2007 Midlevel Storm Structure and Surface Gust Front Evolution t=30t=60t=90t=120

30. 10 Dec 2007 Midlevel Storm Structure and Surface Gust Front Evolution t=30t=60t=90t=120 Warmer!

31. 10 Dec 2007 Getting microphysics “right” is important for simulating the right downdraft Z ~ 500 m Z = 0 m

32. 10 Dec 2007 Low-level Storm Structure and Surface Gust Front t=60 min (Us=50)

33. 10 Dec 2007 Temporally and Horizontally-Averaged Vertical Profiles

34. 10 Dec 2007 Temporally and Horizontally-Averaged Vertical Profiles (cont’d)

35. 10 Dec 2007 Thus, N8r4 case has larger mass of qh but spread over larger area Smaller fall velocities

36. 10 Dec 2007 Second Sensitivity Test When the intercepts for the following species were increased individually by 2 orders of magnitude, then total precipitation fall decreased by... –Rain (N6 to N8): 3 Tg –Snow (N5 to N7): 4 Tg –Large Ice (N4 to N6): 12 Tg Greatest sensitivity to qh

37. 10 Dec 2007 Third Sensitivity Test Change the ground-relative (GR) motion but not the vertical wind shear... Result: point rainfall and hailfall doubles although total system mass preserved New GR-Motion: subtract 10 m s –1 from u windspeeds

38. 10 Dec 2007 Results Summary Mass fallout changes by a factor of 4 when the “large ice” distribution is varied within its observational limits. Weaker shear shows differences of a factor of 3. Us=20 m/s cases (not shown) had factor of 2. Thus, sensitive to the vertical wind shear Model precipitation is more sensitive to changes in the “large ice” distribution than the snow or rain distribution. Precipitation depth is also a function of GR-storm motion.

39. 10 Dec 2007 Conclusion While simple bulk microphysics schemes such as LFO can be “tuned” and may have value in a research mode, they are probably not well suited for precipitation forecasts.

40. 10 Dec 2007 Future Work: Improved schemes Multiple Moments for 3 or 4 ice categories e.g., Ferrier (1994), Siefert and Beheng (2001) More ice categories (necessary - McCumber et al.) More liquid and ice categories, more moments, particle density prediction, Straka and Gilmore (2008)

41. 10 Dec 2007 Two Moment, 5-ice, 3-rain scheme Straka and Gilmore (2008) –Will this reduce the precipitation uncertainty?

42. 10 Dec 2007 (Photo Credit: NCAR/NSF) Joe and Jill Newham, April 1975 Thanks for your attention!

43. 10 Dec 2007

44. Rates t = 30 min

45. 10 Dec 2007 Supplemental Figures Rates t = 30 min

46. 10 Dec 2007 Rates t = 90 min

47. 10 Dec 2007 Supplemental Figures Rates t = 90 min

48. 10 Dec 2007 Conventional versus Dual-Polarization Radar Light Rain Wet Snow Heavy Rain Large Drops Moderate Rain Vertical Ice Horizontal Ice Dry Snow Hail Graupel/Small Hail Rain/Hail Conventional Radar Reflectivity Hydrometeor Classification Cimmaron, OK, az=148.2°, 2316 UTC 6 June 1996. (Adapted from Zrnic et al. 2001).