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Sensitivity of Supercell Tornado Simulations to Variations in Microphysical Parameters

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

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  1. Sensitivity of Supercell Tornado Simulations to Variations in Microphysical Parameters Nathan Snook and Ming Xue School of Meteorology, University of Oklahoma February 17, 2006

  2. 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).

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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).

  9. 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.

  10. 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.

  11. 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.

  12. 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.

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