Two Chebyshev Spectral Methods for Solving Normal Modes in Atmospheric Acoustics

The normal mode model is important in computational atmospheric acoustics. It is often used to compute the atmospheric acoustic field under a time-independent single-frequency sound source. Its solution consists of a set of discrete modes radiating into the upper atmosphere, usually related to the continuous spectrum. In this article, we present two spectral methods, the Chebyshev-Tau and Chebyshev-Collocation methods, to solve for the atmospheric acoustic normal modes, and corresponding programs are developed. The two spectral methods successfully transform the problem of searching for the modal wavenumbers in the complex plane into a simple dense matrix eigenvalue problem by projecting the governing equation onto a set of orthogonal bases, which can be easily solved through linear algebra methods. After the eigenvalues and eigenvectors are obtained, the horizontal wavenumbers and their corresponding modes can be obtained with simple processing. Numerical experiments were examined for both downwind and upwind conditions to verify the effectiveness of the methods. The running time data indicated that both spectral methods proposed in this article are faster than the Legendre-Galerkin spectral method proposed previously.

Assessing Raspberry Shake and Boom Sensors for Recording African Elephant Acoustic Vocalizations

Acoustic sensors are increasingly being used in ecological and conservation research, but the choice of sensor can be fraught with trade-offs. In this work we assess the performance of the Raspberry Shake and Boom (RS&B) sensor package for detecting and monitoring African elephants (Loxodonta africana). This is the first documented test of this particular unit for recording animal behavior; the unit was originally designed for detecting tectonic earthquakes and low frequency (<50 Hz) atmospheric acoustics. During a four day deployment in South Africa we tested five RS&B units for recording acoustic and seismic vocalizations generated by a group of African elephants. Our results highlight a varied degree of success in detecting the signals of interest. The acoustic microphone recorded fundamental frequencies of low-frequency (<50 Hz) harmonic vocalizations that were not clearly recorded by more sensitive instruments, but was not able to record higher frequency harmonics due to the low sampling rate (100 Hz). The geophone was not able to consistently record clear seismic waves generated by vocalizations but was able to record higher harmonics. In addition, seismic signals were detected from footsteps of elephants at <50 m distance. We conclude that the RS&B unit currently shows limited potential as a monitoring tool for African elephants and we propose several future directions and deployment strategies to improve the sensitivity of the sensor package.

XVII LEONID BREKHOVSKIKH SCHOOL ON OCEAN ACOUSTICS

The short communication presents the results of the 17th School on Ocean Acoustics known as “L.M. Brekhovskikh School-Seminar” held online from October 19 to 23, 2020. The conference was combined with the XXXIII session of the Russian Acoustic Society. The conference was attended by 138 researchers from 25 research institutes form Russia, Abkhazia, Israel, USA, and Taiwan. Leading scientists gave 6 lectures. 59 oral and poster presentations were presented focusing on topical scientific and technical subjects: acoustic oceanology, sound propagation in the ocean, sound scattering and reflection, engineering, and signal processing, as well as bio-, geo- and atmospheric acoustics.

Assessing Raspberry Shake and Boom sensors for recording African elephant acoustic vocalizations

In this work we assess the performance of the Raspberry Shake and Boom (RS&B) sensor package for detecting and monitoring African elephants (Loxodonta africana). This is the first documented test of this particular unit for recording animal behaviour; the unit was originally designed for detecting tectonic earthquakes and low frequency (<50 Hz) atmospheric acoustics. During a four day deployment in South Africa we tested five RS&B units for recording acoustic and seismic vocalizations generated by a group of African elephants. Our results highlight a varied degree of success in detecting the signals of interest. The acoustic microphone recorded fundamental frequencies of low-frequency (<50 Hz) harmonic vocalizations that were not clearly recorded by more sensitive instruments, but was not able to record higher frequency harmonics due to the low sampling rate (100 Hz). The geophone was not able to consistently record clear seismic waves generated by vocalizations but was able to record higher harmonics. In addition, seismic signals were detected from footsteps of elephants at <50 m distance. We conclude that the RS&B unit shows limited potential as a monitoring tool for African elephants and discuss future directions and deployment strategies to improve the sensitivity of the sensor package.