Sensitivity of Supercell Tornado Simulations to Variations in Microphysical Parameters

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 Look100m 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.