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Sensitivity of Supercell Tornado Simulations to Variations in Microphysical Parameters Nathan Snook and Ming Xue School of Meteorology, University of Oklahoma February 17, 2006 Motivation
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Sensitivity of Supercell Tornado Simulations to Variations in Microphysical Parameters Nathan Snook and Ming Xue School of Meteorology, University of Oklahoma February 17, 2006
Motivation • Tornadoes spawned by supercell thunderstorms are a major severe weather hazard in the central United States, causing multiple fatalities and millions of dollars in damage each year. • Accurate numerical simulation of tornadic supercells remains a challenge, as the solution is affected by grid resolution and model parameters, such as microphysics. • Most models assume a Marshall-Palmer inverse exponential dropsize distribution. • Observational studies of Marshall-Palmer intercept parameters for rain, snow, and hail have yielded values that vary by several orders of magnitude (Gilmore et al., 2004).
Goals • Investigate the sensitivity of supercell storm dynamics to variation in Marshall-Palmer intercept parameters for rain, hail, and snow dropsize distributions, and hail density. • Cold Pool Intensity • Organizational Mode • Precipitation Distribution and Intensity • Explore the impacts of these effects on tornado potential and tornado formation.
Methods • Idealized modeling studies using the Advanced Regional Prediction System (ARPS). • 13 simulations at 1 km horizontal resolution • 7 simulations at 100 m horizontal resolution • Varied Marshall-Palmer intercept parameters for rain, hail, and snow, as well as hail density. • Horizontally homogeneous base state using composited sounding from May 20, 1977 Del City, Oklahoma supercell case.
Which Parameters Affect Supercell Dynamics? • Parameters Studied: • Rain, hail, and snow Marshall-Palmer intercept parameters • Hail density • 13 ARPS Simulations • 128 x 128 x 16 km domain with 1km horizontal grid spacing. • Noted variations in cold pool intensity and storm mode.
1 km Results: Cold Pool Intensity • Wide variation in storm mode and cold pool intensity among 1km simulations. • Hail and rain intercept parameters were most influential.
Getting a Closer Look–100m Simulations • 7 ARPS runs on a 64 x 64 x 16 km domain with 100 m horizontal grid spacing. • Varied Marshall-Palmer rain and hail intercept parameters. • Focused on impacts to dynamics and tornadogenesis potential.
100 m Results: Comparisons and Contrasts N0r = 8 x 105 m4, N0h = 4x104 m4 N0r = 8 x 107 m4, N0h = 4x106 m4 Large raindrops Small raindrops and hailstones Lin Scheme Defaults: N0r = 8x106 m4, N0h = 4x104 m4 • In simulations with stronger cold pools, the gust front was stronger and propagated eastward more quickly, often advancing several kilometers ahead of the storm. • A more linear storm mode was favored in the simulation with the strongest cold pool (h6r7, pictured on the right of Fig. 3a).
100 m Results: Vorticity Timeseries Large Raindrops (r5) Maximum intensity:f2 Duration: 9 min. Control (CON) Maximum intensity:f2 Duration: 4 min. • Simulations favoring large hydrometeors (weak cold pools) were most favorable for development of long-lived tornadoes. • In simulations favoring small hydrometeors (strong cold pools), tornadic spinups that did occur tended to be weak and short-lived.
100 m Results: Tornadic Vortex • Closeup of tornadic circulation in simulation favoring large raindrops (r5). • Maximum tornado intensity: f2 • Tornado duration: Approximately 9 min. • Location and development of tornado match well with theory and observations.
100 m Results: Vertical Structure • Simulations favoring large hydrometeors resulted in relatively strong, vertically-oriented, sustained updrafts, resulting in steady supercells. • Simulations favoring small hydrometeors resulted in weaker, tilted, pulse-like updrafts that resulted in cyclic or non-supercellular behavior.
Conclusions • There is a tremendous sensitivity of storm mode, cold pool strength, and tornadogenesis potential to microphysics. • Changing intercept parameters alone is sufficient to determine the success or failure of tornadogenesis. • Simulations favoring large raindrops, using the current ice physics, were more favorable for tornadogenesis. • Weak cold pool due to reduced evaporational cooling. • Better positioning of gust front allowing for sustained, intense, vertically-oriented updraft. • Better microphysics with reduced uncertainty in e.g., intercept parameters, will be necessary for reliable simulation and prediction of tornadoes and their parent storms.