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Atmospheric acoustic waves from volcanoes at infrasonic frequencies (0.01–20 Hz) can be used to estimate source parameters for hazard modeling, but signals are often distorted by wavefield interactions with topography, even at local recording distances (<15 km). We present new developments toward a simple empirical approach to estimate attenuation by topographic diffraction at reduced computational cost. We investigate the applicability of a thin screen diffraction relationship developed by Maekawa [1968, doi: https://doi.org/10.1016/0003-682X(68)90020- 0]. We use a 2D axisymmetric finite-difference method to show that this relationship accurately predicts power losses for infrasound diffraction over an idealized kilometer-scale screen; thus validating the scaling to infrasonic wavelengths. However, the Maekawa relationship overestimates attenuation for realistic volcano topography (using Sakurajima Volcano as an example). The attenuating effect of diffraction may be counteracted by constructive interference of multiple reflections along concave volcano slopes. We conclude that the Maekawa relationship is insufficient as formulated for volcano infrasound, and suggest modifications that may improve the prediction capability. 

Abstract Volcanic eruption source parameters may be estimated from acoustic pressure recordings dominant at infrasonic frequencies (< 20 Hz), yet uncertainties may be high due in part to poorly understood propagation dynamics. Linear acoustic propagation of volcano infrasound is commonly assumed, but nonlinear processes such as wave steepening may distort waveforms and obscure the sourcing process in recorded waveforms. Here we use a previously developed frequency-domain nonlinearity indicator to quantify spectral changes due to nonlinear propagation primarily in 80 signals from explosions at Yasur Volcano, Vanuatu. We find evidence for$$\le$$ $\le$10⁻³ dB/m spectral energy transfer in the band 3–9 Hz for signals with amplitude on the order of several hundred Pa at 200–400 m range. The clarity of the nonlinear spectral signature increases with waveform amplitude, suggesting stronger nonlinear changes for greater source pressures. We observe similar results in application to synthetics generated through finite-difference wavefield simulations of nonlinear propagation, although limitations of the model complicate direct comparison to the observations. Our results provide quantitative evidence for nonlinear propagation that confirms previous interpretations made on the basis of qualitative observations of asymmetric waveforms. 

Abstract Sound waves generated by erupting volcanoes can be used to infer important source dynamics, yet acoustic source‐time functions may be distorted during propagation, even at local recording distances (15 km). The resulting uncertainty in source estimates can be reduced by improving constraints on propagation effects. We aim to quantify potential distortions caused by wave steepening during nonlinear propagation, with the aim of improving the accuracy of volcano‐acoustic source predictions. We hypothesize that wave steepening causes spectral energy transfer away from the dominant source frequency. To test this, we apply a previously developed single‐point, frequency domain, quadspectral density‐based nonlinearity indicator to 30 acoustic signals from Vulcanian explosion events at Sakurajima Volcano, Japan, in an 8‐day data set collected by five infrasound stations in 2013 with 2.3‐ to 6.2‐km range. We model these results with a 2‐D axisymmetric finite‐difference method that includes rigid topography, wind, and nonlinear propagation. Simulation results with flat ground indicate that wave steepening causes up to2 dB (1% of source level) of cumulative upward spectral energy transfer for Sakurajima amplitudes. Correction for nonlinear propagation may therefore provide a valuable second‐order improvement in accuracy for source parameter estimates. However, simulations with wind and topography introduce variations in the indicator spectra on order of a few decibels. Nonrandom phase relationships generated during propagation or at the source may be misinterpreted as nonlinear spectral energy transfer. The nonlinearity indicator is therefore best suited to small source‐receiver distances (e.g.,2 km) and volcanoes with simple sources (e.g., gas‐rich strombolian explosions) and topography.