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Evaluation of the Bulk Microphysical Pathways and and Sensitivities Studies for 13-14 December 2001 of IMPROVE 2 Brian A. Colle*, Matt Garvert # , Justin B. Wolfe*, and Clifford F. Mass # *Stony Brook University / SUNY # University of Washington, Seattle, WA.
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Evaluation of the Bulk Microphysical • Pathways and and Sensitivities Studies for • 13-14 December 2001 of IMPROVE 2 • • Brian A. Colle*, Matt Garvert #, Justin B. Wolfe*, and Clifford F. Mass # • *Stony Brook University / SUNY • #University of Washington, Seattle, WA
Vertical Velocity Comparisons NOAA P-3 (23-01Z) MM5 1.33 km (23-25 h) x10-3 m s-1 From Garvert et al. (2004) paper 5.4 (Mon)
* What are the microphysical pathways and sensitivities? Avg. cross location Avg. Micro budget 1.33 km domain (% of observed)
West-East average cross section between 23-01 UTC (23-25 h) Micro budget region Snow, graupel, and cloud water (every 0.2 g kg-1)
APPROACH: Normalize each process by the sum of the water vapor loss (WVL) terms: Reisner2 BMP
Windward Microphysical Budget (% of water vapor loss) 25% fallout fallout fallout Snow spillover
Deposition Snow Sources (x 105 g/(kg s): 500-550 mb average Primary Graupel Source: 675-725 mb average CLW accretion by snow CLW accretion by snow
Accretion O Graupel Melt X X O X O O X X O O X X O O Snow Melt Rain Source (x 105 g kg-1 s-1): 825-775 mb average (2300-0100 UTC) X X O O X O X ‘X’ 90-130% of obs 6-h pcp ‘O’ > 130% of obs 6-h pcp O
Sensitivity to Snow Intercept Parameter NosThe temperature dependent Nos (Houze et al. 1979) was changed to either a variable Nos(qs) or fixed Nos (2107 m-4). Nos(T) Nosfix Nosfix Nos(T) • For qs=0.45 g kg-1, t=-12oC, =0.83 kg m-3, Nos(qs) has more large snow particles and less small particles, while fixed Nos has more smaller particles. Nos(qs)
Difference cross section NosQ-CTL Snow, graupel, and cloud water mixing ratios g kg-1
Difference cross section for Nosfix-CTL Snow, graupel, and cloud water mixing ratios (g kg-1)
Ice Number Verification (Convair at 4.9 km ASL) OBS: 0.25 g kg-1 Fixed NOS NosT: 0.55 g kg-1 NosT Nosq: 0.37 g kg-1 Fix Nos: 0.62 g kg-1 Nosq
Cloud Water Verification (NOAA P3 North-South Average Legs) CTL Nosq Fixed NOS
Surface Precipitation Verification Mean Error (Mean Absolute Error) (1400 UTC 13 DEC to 0800 UTC 14 DEC 2001)
Summary and Conclusions • There are two primary water vapor loss pathways over the windward slope: • The partition between these two pathways and the amount of cloud water are sensitive to parameters such as Nos and snow fall speed. • There is too much snow aloft during this event as suggested by the aircraft data and relationship between snow melt and rain gauge overpredictions. An increased sdep pathway (such as in the SICE scheme) amplifies the spillover problem. • There is little sensitivity to using different cloud water autoconversions and ice initiation schemes (Fletcher versus Cooper, etc…). 27% accr rain 50% clw cond-evap graupel rain riming melt WV 17% sdep 18% snow rain 25% melt 6%
Model versus obs precip profile (12/13/14Z - 12/14/08Z) Warm rain Simple Ice
Snow source (percent contribution of each process at a point) Sband Ice accr and autocvn Rain Source sdep Sdep+ riming Sn to gr autocvn riming Snow melt clw accretion Graupel melt
How do the processes vary across narrow ridges and valleys? xSband
Sensitivity to Snow Fall Speed Vs • Vs=11.72D0.41 (CTRL, Rut&Hobbs83) • Vs=4.84D0.25 (Lin et al. 1983) • Vs=16.8D0.527 (Cox 1988) • Vs=8.97D0.42 (Ferrier 1994) • RH83 Vs is for unrimed radiating assemblages for plates, side planes, bullets and columns, L83 for graupel like snow of hexagonal type, and Cox Vs close to unrimed radiating assemblages of drendrites. • Cox and Ferrier Vs are 20-30% slower than CTRL (RH83).
Difference cross section for Cox-CTL Snow trajectories: red= CTL, blue = Cox Snow, graupel, and cloud water mixing ratio in g kg-1
Kess Nos(qs) P-3 altitude Cox Obs CTL FixNos