Using barometric time series of the IMS infrasound network for a global analysis of thermally induced atmospheric tides

Hupe, Patrick; Ceranna, Lars; Pilger, Christoph

doi:https://doi.org/10.5194/amt-11-2027-2018

Articles | Volume 11, issue 4

https://doi.org/10.5194/amt-11-2027-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-11-2027-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 11, issue 4

Research article

|

10 Apr 2018

Research article |

| 10 Apr 2018

Using barometric time series of the IMS infrasound network for a global analysis of thermally induced atmospheric tides

Patrick Hupe, Lars Ceranna, and Christoph Pilger

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Final revised paper (published on 10 Apr 2018)
Preprint (discussion started on 22 Dec 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Referee’s report amt-2017-465', Anonymous Referee #1, 19 Jan 2018
- AC1: 'Authors' response to Referee #1', Patrick Hupe, 08 Mar 2018
RC2: 'Review of 'Using barometric time series of the IMS infrasound network for a global analysis of thermally induced atmospheric tides'', Anonymous Referee #2, 19 Jan 2018
- AC2: 'Authors' response to Referee #2', Patrick Hupe, 08 Mar 2018

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Patrick Hupe on behalf of the Authors (08 Mar 2018) Author's response Manuscript

ED: Publish as is (14 Mar 2018) by Gerd Baumgarten

AR by Patrick Hupe on behalf of the Authors (14 Mar 2018)

Short summary

Explosions in the atmosphere produce infrasound, recorded as very small pressure fluctuations. The relatively new infrasound technology also provides information on atmospheric dynamics. Within the ARISE2 project we have analysed the tidal variability using the data of the global IMS infrasound network. Our findings are compared with reanalysis data. We claim our methodology to be applicable for geographical and temporal studies of dynamic features and propose future applications.