Microbarom radiation and propagation model assessment using infrasound recordings: a vespagram-based approach

Abstract

Abstract. This study investigates the use of a vespagram-based approach as a tool for multi-directional comparison between simulated microbarom soundscapes and infrasound data recorded at ground-based array stations. Data recorded at the IS37 station in northern Norway during 2014–2019 have been processed to generate vespagrams (velocity spectral analysis) for five frequency bands between 0.1 and 0.6 Hz. The back-azimuth resolution between vespagrams and a microbarom model is harmonized by smoothing the modelled soundscapes along the back-azimuth axis with a kernel corresponding to the frequency-dependent array resolution. An estimate of similarity between the output of a microbarom radiation and propagation model and infrasound observations is then generated based on the image processing approach of mean-square difference. The analysis revealed that vespagrams can monitor seasonal variations in the microbarom azimuth distribution, amplitude, and frequency, as well as changes during sudden stratospheric warming. The vespagram-based approach is computationally inexpensive, can uncover microbarom source variability, and has potential for near-real-time stratospheric diagnostics and atmospheric model assessment.

A Bird’s‐Eye View on Ambient Infrasonic Soundscapes

“…Propagating microbaroms are often received at distant infrasound arrays and typically peak around 0.2 Hz (Campus & Christie, 2010). Various studies have focused on comparing microbarom simulations and distant IMS array observations (De Carlo, Hupe, et al, 2020;Landes et al, 2012;Vorobeva et al, 2020). Such studies are hampered by the relatively large distance of the arrays to the microbarom source regions, which is often largely spread out (∼ 2 10,000 km ).…”

Updated global reference models of broadband coherent infrasound signals for atmospheric studies and civilian applications

“…Although the detection of multiple signals at different frequencies is possible, there exists the chance that if there are two or more signals in the same frequency band, that the PMCC approach could miss these secondary signals. Further studies could involve a similar analysis using sensors able to separate coherent signals overlapping in the same time-frequency domain such as the CLEAN algorithm (den Ouden et al, 2020) or the vespagram approach (Vorobeva et al, 2021). By performing a similar analysis on these multi-source results, and generating the same types of reference curves, such data analysis approaches would allow building reference curves for these additional infrasound analysis methods.…”