How well must surface vorticity be organized for tornadogenesis?
Parker, Matthew (2023), How well must surface vorticity be organized for tornadogenesis?, Dryad, Dataset, https://doi.org/10.5061/dryad.mcvdnck4n
This study investigates whether quasi-random surface vertical vorticity is sufficient for tornadogenesis when combined with an updraft typical of tornadic supercells. The viability of this pathway could mean that a coherent process to produce well-organized surface vertical vorticity is rather unimportant. Highly idealized simulations are used to establish random noise as a possible seed for the production of tornado-like vortices (TLVs). A number of sensitivities are then examined across the simulations. The most explanatory predictor of whether a TLV will form (and how strong it will become) is the maximal value of initial surface circulation found near the updraft. Perhaps surprisingly, sufficient circulation for tornadogenesis is often present even when the surface vertical vorticity field lacks any obvious organized structure. The other key ingredient for TLV formation is confirmed to be a large vertical gradient in vertical velocity close to the ground (to promote stretching). Overall, it appears that random surface vertical vorticity is indeed sufficient for TLV formation given adequate stretching. However, it is shown that longer-wavelength noise is more likely to be associated with substantial surface circulation (because it is the areal integral of vertical vorticity). Thus, coherent vorticity sources that produce longer wavelength structures are likely to be the most supportive of tornadogenesis.
The Cloud Model 1 (CM1) is available from https://www2.mmm.ucar.edu/people/bryan/cm1/
This repository includes namelists and input files needed to recreate the simulations in the study using release 20.3 of CM1. (Dryad, as described in README.md)
Post-processing of NetCDF output from CM1 was accomplished using Python scripts developed by the author, which are also included in this repository. (Zenodo, as described in README.md)
The induced flow solver used in this study is the intellectual property of Dr. Johannes Dahl and may be available by contacting him (firstname.lastname@example.org). The induced flow fields it produces (which were used as initial conditions in this study) are included in this repository (binary form, with descriptive .ctl files).
The CM1 model requires a fortran compiler (see https://www2.mmm.ucar.edu/people/bryan/cm1/ for more information).
The plotting scripts require access to NetCDF libraries and Python (including installation of several packages listed in the preamble to the attached Python scripts).
The easiest way to view the contents of the induced_flow.dat files is to use the Gridded Analysis and Display Software (GrADS).
All files are contained within tar archives, and the user will need to unpack them.
National Science Foundation, Award: AGS-2130936