What is already known:
What this study adds:
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.