07 Sep 2023
 | 07 Sep 2023
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

Objective identification of pressure wave events from networks of 1-Hz, high-precision sensors

Luke Robert Allen, Sandra E. Yuter, Matthew Allen Miller, and Laura M. Tomkins

Abstract. Mesoscale pressure waves including atmospheric gravity waves, outflow and frontal passages, and wake lows are outputs of and can potentially modify clouds and precipitation. A wavelet-based method for identifying and tracking these types of wave signals in time series data from networks of low-cost, high-precision (0.8-Pa noise floor, 1-Hz recording frequency) pressure sensors is demonstrated. Strong wavelet signals are identified using a wave period-dependent (i.e., frequency-dependent) threshold, then those signals are extracted by inverting the wavelet transform. Wave periods between 1 minute and 120 minutes were analyzed, a range which would include several types of mesoscale disturbances in the troposphere. After extracting the signals from a network of pressure sensors, the cross-correlation function is used to estimate the time difference between the wave passage at each pressure sensor. From those time differences, the wave phase velocity vector is calculated using a least-squares fit. If the fitting error is sufficiently small (thresholds of RMSE < 90 s and NRMSE < 0.1 were used), then a wave event is considered robust and trackable.

Luke Robert Allen et al.

Status: open (until 12 Oct 2023)

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  • RC1: 'Referee comments', Anonymous Referee #3, 15 Sep 2023 reply
  • RC2: 'Comment on egusphere-2023-1600', Anonymous Referee #1, 18 Sep 2023 reply
  • RC3: 'Comment on egusphere-2023-1600', Anonymous Referee #4, 20 Sep 2023 reply
  • RC4: 'Comment on egusphere-2023-1600', Anonymous Referee #2, 24 Sep 2023 reply

Luke Robert Allen et al.

Data sets

Data for Objective identification of pressure wave events from networks of 1-Hz, high-precision sensors Matthew A. Miller and Luke R. Allen

Video supplement

Supplemental videos of the paper "Objective identification of pressure wave events from networks of 1-Hz, high-precision sensors" Luke R. Allen, Laura M. Tomkins, Sandra E. Yuter

Luke Robert Allen et al.


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Short summary
A data set of high-precision surface air pressure observations and a method for detecting wave signals from the time series of pressure are presented. From networks of pressure sensors spaced ~tens of km apart, the wave phase speed and direction are estimated. A wavelet-based method is used to find wave signals at specific times and wave periods. Examples of wave events and their meteorological context are shown using radar data, weather balloon data, and other surface weather observations.