A framework for estimating stratospheric wind speeds from unknown sources and application to the 2010 December 25 bolide

We present a methodology for infrasonic remote sensing of winds in the stratosphere that does not require discrete ground-truth events. Our method uses measured time delays between arrays of sensors to provide group velocities (referred to here as celerities) and then minimizes the difference between observed and predicted celerities by perturbing an initial atmospheric specication.Becausewe focus on interarray propagation effects, it is not necessary to simulate the full propagation path fromsource to receiver. This feature allows us to use a relatively simple forward model that is applicable over short-regional distances. By focusing on stratospheric returns, we show that our non-linear inversion scheme converges much better if the starting model contains a strong stratospheric duct. Using the Horizontal Wind Model (HWM)/Mass Spectrometer Incoherent Scatter (MSISE) empirical climatology as a starting model, we demonstrate that the inversion scheme is robust to large uncertainties in backazimuth, but that uncertainties in the measured trace velocity and celerity require the use of prior constraints to ensure suitable convergence. The inversion of synthetic data, using realistic estimates of measurement error, shows that our scheme will nevertheless improve upon a starting model undermost scenarios. The inversion scheme is applied to infrasound data recorded froma large event on 2010 December 25, which is presumed to be a bolide, using data from a nine-element infrasound network in Utah. We show that our recorded data require a stronger zonal wind speed in the stratosphere than is present in the HWM prole, and are more consistent with the Ground-to-Space (G2S) prole.