Articles | Volume 17, issue 1
https://doi.org/10.5194/amt-17-113-2024
https://doi.org/10.5194/amt-17-113-2024
Research article
 | 
10 Jan 2024
Research article |  | 10 Jan 2024

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

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

Data sets

Data for Objective identification of pressure wave events from networks of 1-Hz, high-precision sensors Matthew Miller and Luke Allen https://doi.org/10.5281/zenodo.8136536

NOAA Next Generation Radar (NEXRAD) Level II Base Data NOAA National Weather Service Radar Operations Center https://doi.org/10.7289/V5W9574V

Automated Surface/Weather Observing Systems (ASOS/AWOS) NOAA National Centers for Environmental Information https://www.ncei.noaa.gov/products/land-based-station/automated-surface-weather-observing-systems

Global BUFR Data Stream: Upper Air Reports from the National Weather Service Telecommunications Gateway (NWS TG) NOAA National Centers for Environmental Information https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C01500

Model code and software

Code for Objective identification of pressure wave events from networks of 1-Hz, high-precision sensors Luke Allen https://doi.org/10.5281/zenodo.10150876

Video supplement

Supplemental videos of the paper "Objective identification of pressure wave events from networks of 1-Hz, high-precision sensors" Luke Allen et al. https://doi.org/10.5446/s_1476

14 Sep 2021 KOKX Reflectivity and Doppler Velocity Waves Luke Allen et al. https://doi.org/10.5446/62542

15 Nov 2020 KBUF Reflectivity and Doppler Velocity Waves Luke Allen et al. https://doi.org/10.5446/62541

04 Feb 2022 KOKX Reflectivity and Doppler Velocity Waves Luke Allen et al. https://doi.org/10.5446/62540

25 Feb 2022 KBUF Reflectivity and Doppler Velocity Waves Luke Allen et al. https://doi.org/10.5446/62539

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