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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 17, issue 23
Atmos. Chem. Phys., 17, 14811–14819, 2017
https://doi.org/10.5194/acp-17-14811-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 17, 14811–14819, 2017
https://doi.org/10.5194/acp-17-14811-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 12 Dec 2017

Research article | 12 Dec 2017

Retrieving characteristics of inertia gravity wave parameters with least uncertainties using the hodograph method

Gopa Dutta et al.

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Anna Wenzel on behalf of the Authors (18 Jul 2017)  Author's response
ED: Referee Nomination & Report Request started (08 Aug 2017) by Jayanarayanan Kuttippurath
RR by Anonymous Referee #1 (09 Aug 2017)
RR by Vladimir Gubenko (25 Aug 2017)
ED: Reconsider after major revisions (28 Aug 2017) by Jayanarayanan Kuttippurath
AR by Anna Wenzel on behalf of the Authors (19 Sep 2017)  Author's response
ED: Referee Nomination & Report Request started (21 Sep 2017) by Jayanarayanan Kuttippurath
RR by Vladimir Gubenko (02 Oct 2017)
ED: Reconsider after minor revisions (Editor review) (16 Oct 2017) by Jayanarayanan Kuttippurath
AR by Gopa Dutta on behalf of the Authors (26 Oct 2017)  Author's response    Manuscript
ED: Publish as is (30 Oct 2017) by Jayanarayanan Kuttippurath
AR by Gopa Dutta on behalf of the Authors (31 Oct 2017)  Author's response    Manuscript
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Short summary
Gravity wave stress is crucial for weather prediction purposes. It is found that proper filtering of the data is essential to reduce uncertainties in the popular hodograph method to delineate low-frequency gravity wave parameters. Our research helped in improving the estimates of gravity wave stress by reducing errors.
Gravity wave stress is crucial for weather prediction purposes. It is found that proper...
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