08 Oct 2021

08 Oct 2021

Review status: this preprint is currently under review for the journal AMT.

Detecting Wave Features in Doppler Radial Velocity Radar Observations

Matthew A. Miller1, Sandra E. Yuter1, Nicole P. Hoban1, Laura M. Tomkins1, and Brian A. Colle2 Matthew A. Miller et al.
  • 1North Carolina State University, Raleigh, NC
  • 2Stony Brook University, Stony Brook, NY

Abstract. Mesoscale, wave-like perturbations in horizontal air motions in the troposphere (velocity waves) are associated with vertical velocity, temperature, and pressure perturbations that can initiate or enhance precipitation within clouds. The ability to detect velocity waves from horizontal wind information is an important tool for atmospheric research and weather forecasting. This paper presents a method to routinely detect velocity waves using Doppler radial velocity data from a scanning weather radar. The method utilizes the difference field between consecutive PPI scans at a given elevation angle. Using the difference between fields a few minutes apart highlights small scale perturbations associated with waves because the larger scale wind field changes more slowly. Image filtering retains larger contiguous velocity bands and discards noise. Wave detection scales are limited by the size of the temporal difference relative to the wave motion and the radar resolution volume size.

Matthew A. Miller et al.

Status: open (until 13 Nov 2021)

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Matthew A. Miller et al.

Video supplement

Animation-Figure-8 Matthew Miller

Animation-Figure-7 Matthew Miller

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Animation-Figure-5 Matthew Miller

Animation-Figure-4 Matthew Miller

Animation-MotionStudy2 Matthew Miller

Animation-MotionStudy1 Matthew Miller

Animation-Figure-3 Matthew Miller

Animation-Figure-2 Matthew Miller

Animation-Figure-1 Matthew Miller

Matthew A. Miller et al.


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Short summary
Apparent waves in the atmosphere and similar features in storm winds can be detected by taking the difference between successive Doppler weather radar scans measuring radar-relative storm air motions. Applying image filtering to the difference data better isolates the detected signal. This technique is a useful tool in weather research and forecasting since such waves can trigger or enhance precipitation.