Severe thunderstorms and their associated tornadoes pose significant threats to life and property, and using radar data to accurately measure the rotational velocity of circulations in thunderstorms is essential for appropriate, timely warnings. One key factor in accurately measuring circulation velocity is the azimuthal spacing between radar data points, which is referred to as the azimuthal sampling interval. Previous studies have shown that reducing the azimuthal sampling interval can aid in measuring circulation velocity; however, this comes at the price of increased computational complexity. Thus, choosing the best compromise requires knowledge of the relationship between the radar azimuthal sampling interval and the accuracy of the circulation strength as measured from the radar data. In this work, we use simulations to quantify the impact of azimuthal sampling on the strength of radar-observed circulations and show that the improvements get progressively smaller as the azimuthal sampling interval decreases. Thus, improved characterization of circulations can be achieved without using the finest possible sampling grid. We use real data to validate the results of the simulations, which can be used to inform the selection of an appropriate azimuthal sampling interval that balances the accuracy of the radar-observed circulations and computational complexity.

https://doi.org/10.1175/JTECH-D-19-0152.1

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