A low-order reduced model for the long range propagation of infrasound in the atmosphere

International audienceThis paper considers a class of low-order, range-dependent propagation models obtained from the normal mode decomposition of infrasounds in complex atmospheres. The classicalnormal mode method requires calculating eigenvalues for large matrices making the computation expensive, even though some modes have little influence on the numerically obtainedresults. By decomposing atmospheric perturbations into a wavelet basis, it is shown thatthe most sensitive eigenvalues provide the best reduced model for infrasound propagation.These eigenvalues lie on specific curves in the complex plane that can be directly deducedfrom atmospheric data through a WKB approach. The computation cost can be reducedby computing the invariant subspace associated with the most sensitive eigenvalues. Thereduction method is illustrated in the case of the Fukushima explosion (12 March 2011).The implicitly-restarted Arnoldi algorithm is used to compute the 3 most sensitive modesand the correct tropospheric arrival is found with a cost of 2 % of the total run time. Thecost can be further reduced by using a stationary phase technique. Finally, it is shown thatadding uncertainties triggers a stratospheric arrival even though the classical criteria, basedon the ratio of stratospheric sound speed to that at ground level, is not satisfie