edward mansell national severe storms laboratory donald macgorman and conrad ziegler national severe...
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Edward MansellNational Severe Storms Laboratory
Donald MacGorman and Conrad ZieglerNational Severe Storms Laboratory, Norman, OK
Funding sources in the Office of Naval Research, NSF, NSSL, the National
Research Council, and the Oklahoma State Regents
Lightning at NSSL: Numerical Modeling and Data Assimilation
• Storm electrification modeling:
• Basic understanding of electrification processes
• Lightning-storm relationships
• Lightning data assimilation (COAMPS)
• On mesoscale (>10km), control convection parameterization scheme.
• Storm-scale EnKF radar data assimilation
Modeling Activities/Capabilities
Storm Model (COMMAS)• Full dynamic, microphysical, and
electrical simulation model
• Collisional charge separation, explicit small ion processes, branched lightning.
• Two-moment bulk microphysics: Predict particle concentrations (and mass) for all hydrometeors (droplets, rain, ice crystals, snow, graupel, hail) and simple bulk CCN.
• MPI capable
[Mansell et al. 2002, 2005, (2009 in review), also Fierro et al, Kuhlman et al.]
Supercell Simluation
Small Storm Simluation
Lightning and Charge Structure
Inferred charge structure from lightning sources
+
+–
Model-simulated charge structure and lightning
West -30km -25km East
Alti
tude
(km
)
Sensitivity to CCN concentration
Volume
Simulated Lightning Rate Correlations
Isolated cells: 0.7
multiple cells: 0.5
Total Flash Rate Correlation Coefficient with
Parameter Isolated Storms Storm Systems
Maximum Elec. Field 0.08 0.10
Graupel Volume 0.69 0.50
Updraft Mass Flux (-10°C) 0.82 0.39
Updraft Volume (>10 m s-1) 0.73 0.29
Cloud Ice Mass Flux (-30°C)
0.79 0.65
Cloud Ice Mass 0.25 0.36
Rain Mass 0.64 0.63
Maximum Updraft 0.30 0.06
Assimilating Lightning Data
[Mansell, Ziegler, and MacGorman, 2007]
Method is similar to Rogers et al. (2000) for radar assimilation.
Force/suppress Kain-Fritsch based on presence/absence of lightning. Add up to 1.0 g/kg of moisture to get deep convection (10m/s updraft, 7km cloud depth).
Allow KF scheme to generate precipitation rates and latent heating and evaporative cooling. (Other methods can be used to adjust or impose latent heating rates based on rainfall relations)
LMA sources
KSCO
NE
Case study with COAMPS on 20-21 July 2000
Test caseSpin-up period: Obs. Precip vs. Control
Spin-up period: Obs. Precip vs. Assimilation
Spin-up period: Control vs. Assimilation
Surface Temperature (C)
Warm-start Model Conditions:Control Assimilation
01 UTC 21 July
02 UTC 21 July
0-6 hr Precip: Obs and forecastsControl
Fcst from ltg. assim.
Summary
Issues
• Must consider lightning location accuracy in terms of model resolution.
• What does a “flash” represent in the observing system? (large variations in flash extent) Method tied to data source.
• For resolved convection or convection-permitting EnKF, need to relate lightning to model variables or derived quantities. And/Or use lightning mainly to initiate deep convection.