NWC REU 2015
May 26 - July 31



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The Sensitivity of Supercell Simulations to the Initial Condition Resolution

Elisa Murillo and Corey Potvin


What is already known:

  • Supercells are the least common type of thunderstorm, yet the most prolific producers of severe weather (hail with 2"+ diameter and tornadoes of EF2+ strength).
  • Under the future Warn-on-Forecast paradigm, observations will be assimilated to create the forecast initial condition.
  • The current lack of fine-scale observations will limit the resolution of these initial conditions.
  • Sensitivity of supercell simulations to initial condition resolution has not yet been systematically tested but is important for its impact on storm-scale NWP.

What this study adds:

  • Vorticity is the most sensitive model variable of those examined, while other variables (updraft strength, surface winds, and rainfall) show little sensitivity to the initial condition resolution after the first 10-20 minutes.
  • Storms initialized before storm maturity do not show a distinct connection between forecast quality and the coarseness of the initial condition.
  • Storms initialized during storm maturity show a monotonic degradation of forecast quality with coarser initial conditions.


The effects of initial condition resolution on idealized supercell simulations are analyzed. The motivation for this study is based on the NOAA Warn-on-Forecast (WoF) program, which is developing a convention-allowing ensemble system for operational use. The program envisions a paradigm shift from "warn-on-detection," or prediction of severe convective storms based primarily on current observations, to storm-scale data assimilation and prediction systems playing a much greater role in the severe weather warning process. This study focuses on testing the sensitivity of these supercell simulations to the initial condition resolution, which has not yet been systematically studied. Our focus is on the prediction of model quantities of greatest significance to severe storm forecasters, including updraft strength, low-level vorticity, surface winds, and rainfall.


Idealized simulations are run using the WRF-ARW model with grid spacing fixed at 333 m. Each control simulation uses a thermal bubble to initialize a supercell. The model fields from each control simulation are then filtered at various stages of storm development using cutoff wavelengths of 2, 4, 8, and 16 km. New simulations are then initialized from the coarsened model states and compared to the control simulations to assess the impact of the reduced initial condition resolution. Isolating the error due to limited initial condition resolution enables straightforward evaluation of the scales that need to be resolved by data assimilation to generate reliable model forecasts of various severe storm hazards.


Vorticity is the most sensitive out of the model variables analyzed, which can largely impact the tornado potential forecast. Results also indicate that the simulation sensitivity is dependent on the time of initialization. Errors in the simulations initialized early in the storm life cycle do not steadily increase with cutoff wavelength, whereas the simulations initialized once the storm is mature monotonically degrade as filtering is increased. We hypothesize that this is due to smaller scales having a greater impact on storm evolution as the storm develops.

Full Paper [PDF]