NWC REU 2011
May 23 - July 29



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Sensitivity of Microphysical Parameters on the Evolution of a Supercell

Samuel Lillo and Edward Mansell


What is already known:

  • Parameterization schemes in models use many constants that have large uncertainties.
  • Storm scale models have been proposed to assist in advanced warnings.
  • For these models to be useful, we need to understand how the uncertainty surrounding these constants can impact model forecasts.

What this study adds:

  • Perturbing microphysical parameters in the model can affect the motion, intensity, and severe characteristics of the storm.
  • These results demonstrate the need for storm-scale ensemble physics diversity using multi-moment microphysics in future Warn-on-Forecast applications.


Due to limited computational resources, critical microphysical processes must be accounted for in models through parameterization schemes. These schemes use many constants that have large uncertainties and may vary in nature spatially and temporally. By perturbing individual parameters within a single scheme, an ensemble can be created to attempt to account for the uncertainty in the model physics.


Five ensembles are created to test the sensitivity of a simulated supercell to the following parameters: cloud condensation nuclei (CCN) concentration, the efficiency of cloud water collection by graupel and hail, the fraction of liquid water allowed on graupel and hail, rime density function, and the drag coefficient as a function of particle density. A range of values was chosen for each parameter to represent the uncertainty that exists within the model microphysics. All ensembles exhibited growing variance through the simulation. Monotonic association to the storm evolution was most prominent in the CCN ensemble, in which there were notable variance in the track and intensity of the supercell.

Full Paper [PDF]