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.