10.1 Qualitative and Quantitative Comparisons of a Base-State Substitution Simulation with Dual-Doppler Observations of the 29 May 2012 Kingfisher Supercell

Wednesday, 26 July 2017: 10:30 AM
Coral Reef Harbor (Crowne Plaza San Diego)
Casey E. Davenport, Univ. of North Carolina, Charlotte, NC; and M. I. Biggerstaff and C. L. Ziegler
Manuscript (1.4 MB)

Base-state substitution (otherwise known as BSS) is a recently developed idealized modeling technique that approximates environmental heterogeneity by replacing portions or the entirety of the horizontally homogeneous base-state (as encapsulated by a single sounding) at a user-defined interval. The updated environment embodies both spatial and temporal changes to the environment, allowing the user to conduct controlled experiments in a more realistic setting as a result of the evolving environment.

The goal of BSS is to provide a more accurate representation of the real-world environment (as reflected in a series of environmental soundings) in an idealized framework, thus producing a more realistic storm structure and evolution. Accordingly, it is of interest to determine the extent to which BSS is able to faithfully reproduce observed storm structure and behavior. This will be accomplished using a series of qualitative and quantitative comparisons between the 29 May 2012 Kingfisher supercell thunderstorm observed during the Deep Convective Clouds and Chemistry Experiment (DC3) and BSS simulations of the storm. Three near-inflow soundings collected during DC3 over the lifetime of the Kingfisher supercell will be incorporated over time as the base-state environment. Comparisons of storm evolution, track, structure, and the distribution of various kinematic quantities (such as vorticity and updraft speed) will be made between the BSS simulations, a non-varying control simulation, and one-hour of dual-Doppler data collected during an intensification phase of the storm. Statistical tests will then be used to quantify how well BSS is able to recreate the observed storm versus the control simulation with no changes to the base-state environment.

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