Optimizing an infrasound sensor network for measuring acoustic background noise and its inversion for stratospheric winds

We demonstrate the design of an infrasound network (and the associated analysis) for measuring and inverting low-frequency acoustic background noise (microbaroms) for stratospheric winds. We developed a mathematical framework for the inversion of local stratospheric winds using microbaroms, and found theoretical constraints on the optimum sensor network topology. Based on these results, we deployed, over the winter months (January to March, 2013), a prototype sensor network comprising six infrasound stations separated between 5 and 70 km; the initial analysis shows periods of very high coherency (suitable for our inversion) lasting several hours with associated tropospheric and low stratospheric celerities. We are analyzing the coherency between signals with distance and relative azimuth. Following this pilot study, we are designing a denser sensor network further optimized to capture microbaroms and planning for its validation using independent measurements.