1. Simulating Supercell Thunderstorms in a Horizontally-Heterogeneous Convective Boundary Layer Christopher Nowotarski, Paul Markowski, Yvette Richardson Pennsylvania State University George Bryan National Center for Atmospheric Research 25 th Severe Local Storms Conference Denver, CO September 14, 2010

2. Motivation Previous 3D numerical simulations of supercells and tornadoes generally use horizontally homogeneous environments and exclude surface fluxes. Observations and simulations suggest that supercells are favored in areas with significant vertical wind shear and instability (CAPE). Convective Boundary Layers (CBLs) are characterized by local variations in these quantities. Consequently, supercells simulated in such environments may behave differently than in a homogeneous environment.

3. Background -Mesoscale variations in low-level vertical wind shear and moisture “profoundly influence the morphology of deep convective storms” (Richardson et al. 2007, Richardson 1999). -Storms became more organized and stronger when moving to areas of increased shear. -Storms propagated towards areas of increased low-level moisture in weak shear regimes -Isolated supercells in areas of increased moisture showed both higher updraft speeds and stronger low-level rotation. -Tornadoes tend to be more likely in environments with higher 0-1 km shear and lower lifting condensation levels (Markowski and Richardson 2009)

4. Background - HCRs -Boundary layer convection is a source of heterogeneity in the atmosphere. -Because of low-level shear requirements, supercell environments are likely characterized by rolls or disorganized convection. -Variations in thermodynamic quantities result from increased convergence in updraft branches. (Weckwerth 1996) -Potential temperature can be 0.5 K higher in updraft -Mixing ratio is 1.5 – 2.5 g kg -1 higher in updraft -Increased instability, lower LCLs, and favored regions for cloud formation in updraft branches. -Roll axes tends to be aligned with mean CBL wind (Weckwerth 1999) -Organized boundary layer convection results in local, periodic variations in low-level vertical wind shear. -Maxima tend to be in areas without strong magnitudes of vertical velocity. (from: Weckwerth 1996) (from: Markowski and Richardson 2007)

5. Background 24 May 2008 (from: NOAA comprehensive Large Array-Data Stewardship System)

6. Experiment Design Two high resolution simulations of supercells One simulation allows a convective boundary layer to develop before initializing deep convection. The other is a “typical” horizontally-homogeneous simulation. Compare simulations, focusing on behavior and structure of mature storms (rather than initiation).

7. Model Configuration Model – CM1, version 1, release 14 (with modifications) – dt = 0.75 s, 0.125 s for acoustic calculations – periodic lateral boundary conditions Grid – dimensions: 200 km x 150 km x 18 km – dx, dy = 200 m – dz = stretched from 50 m (below 3 km) to 500 m (above 9.5 km) Parameterizations – Ice microphysics (Lin et al. 1983) – land surface scheme using two-layer soil model (Noilhan and Planton 1989) CBL run only – Radiation (REFERENCE!!!!) CBL run only

8. What about mixing out shear? No large-scale horizontal temperature gradient or Coriolis force, so vertical wind shear is mixed out in CBL. To maintain requisite shear for HCRs and supercells, we need to artificially relax the horizontal winds at low- levels towards the initial state. Add constant velocity tendency to each gridpoint on a vertical level that nudges the average wind at that height towards the initial average. Some reduction in shear is still allowed! Modification of technique applied by Robe and Emmanuel (2001) +

9. Base States CBL simulation – 35 m s -1 0-6 km shear – SBCAPE: 2819 J kg -1 – Small capping inversion to prevent widespread convection Homogeneous simulation – Average of CBL simulation after one hour of simulation time – Low level moisture and temperature have increased (CAPE too) – Some reduction in low-level shear from mixing

10. Results Simulated CBL (before storm initiation)

11. Results

15. Summary

16. Future Work