Infrasound, low-frequency acoustic waves that can propagate over hundreds of kilometers, can become a key tool to study the Earth’s atmosphere. As infrasound propagates, it incorporates information about the atmospheric structure, including temperature and wind variations. As a result, this information can be used to reinforce the numerical weather prediction models, allowing a better representation of the vertical structure of winds and atmospheric temperature. In particular, this study focuses on atmospheric imaging through the development of numerical tools to characterize the sensitivity of infrasound waveforms to the atmospheric domain. To this end, full waveform inversion methods, typically used in seismology, are exploited. These methods estimate the sensitivity of waveforms to geophysical domain parameters using the adjoint method. By adapting this method to infrasound waves, it is shown, for the first time, an estimate of infrasound waveform sensitivities to wind and wave speed variations. The method is applied to the real case of an explosion at the Hukkakero site (Finland), recorded on a CTBT infrasound network. This study also addresses the influence of the source on sensitivity kernels. Given encouraging results on sensitivity, this method is integrated into an inverse problem framework to recover the atmospheric structure in synthetic cases.
Gérier et al. (Tue,) studied this question.
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