Published in

American Meteorological Society, Journal of Atmospheric and Oceanic Technology, 3(41), p. 341-354, 2024

DOI: 10.1175/jtech-d-23-0037.1

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An Accurate and Automated Convective Vortex Detection Method for Long-Duration Infrasound Microbarometer Data

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Preprint: archiving allowed
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Postprint: archiving allowed
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Published version: archiving restricted
Data provided by SHERPA/RoMEO

Abstract

Abstract Heating of the surficial layer of the atmosphere often generates convective vortices, known as “dust devils” when they entrain visible debris. Convective vortices are common on both Earth and Mars, where they affect the climate via dust loading, contribute to wind erosion, impact the efficiency of photovoltaic systems, and potentially result in injury and property damage. However, long-duration terrestrial convective vortex activity records are rare. We have developed a high-precision and high-recall method to extract convective vortex signatures from infrasound microbarometer data streams. The techniques utilizes a wavelet-based detector to capture potential events and then a template matching system to extract the duration of the vortex. Since permanent and temporary infrasound sensors networks are present throughout the globe (many with open data), our method unlocks a vast new convective vortex dataset without requiring the deployment of specialized instrumentation. Significance Statement Convective vortices, or “dust devils,” contribute to regional dust loading in Earth’s atmosphere. However, long-duration convective vortex activity records are rare. We came up with a way to autonomously detect the pressure signatures left by convective vortices striking low-frequency sound, or “infrasound,” sensors. Since permanent infrasound stations have been active for decades, our method has the potential to add orders-of-magnitude more events than previously catalogued.