EGU23-7085, updated on 25 Feb 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Evaluating atmospheric models in the stratosphere using oceanic infrasound ambient noise.

Pierre Letournel1,2, Constantino Listowski1, Marc Bocquet2, Alexis Le Pichon1, Alban Farchi2, Julien Vergoz1, and Marine De Carlo3
Pierre Letournel et al.
  • 1CEA/DAM/DIF, Arpajon, France
  • 2CEREA, Ecole des Ponts and EDF R&D, Île-de-France, France.
  • 3Laboratoire d’Océanographie Physique et Spatiale, Université de Bretagne Occidentale, CNRS, IRD, Ifremer, IUEM, Brest, France

Oceanic ambient noise (microbaroms) records are examined to retrieve information on the state of the middle atmosphere. We present an approach to compare ground-based infrasound observations with simulated infrasound detections obtained by combining a microbarom source model [1] with a semi-empirical attenuation law. Comparisons using this continuous and global infrasound source are presented for large time periods to assess performances on both seasonal and finer time scales. Infrasound detections obtained with a cross-correlation algorithm (PMCC) as well as with the new MCML (MultiChannel Maximum Likelihood) method [2] are considered. The sensitivity of simulated infrasound detections to the middle atmosphere model and to the propagation model (the transmission loss parametrisation) is evaluated. We discuss how this method may help to assess the performance of an atmospheric model in the middle atmosphere, as well as to select best members in an ensemble reanalysis.


[1] De Carlo, M., Accensi, M., Ardhuin, F., and Le Pichon, A.: ARROW (AtmospheRic InfRasound by Ocean Waves): a new real-time product for global ambient noise monitoring., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7564,, 2022.

[2] B Poste, M Charbit, A Le Pichon, C Listowski, F Roueff, J Vergoz, The multichannel maximum-likelihood (MCML) method: a new approach for infrasound detection and wave parameter estimation, Geophysical Journal International, Volume 232, Issue 2, February 2023, Pages 1099–1112,

How to cite: Letournel, P., Listowski, C., Bocquet, M., Le Pichon, A., Farchi, A., Vergoz, J., and De Carlo, M.: Evaluating atmospheric models in the stratosphere using oceanic infrasound ambient noise., EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7085,, 2023.