Instantaneous variance scaling of AIRS thermodynamic profiles using a circular area Monte Carlo approach

Dorrestijn, Jesse; Kahn, Brian H.; Teixeira, João; Irion, Fredrick W.

doi:https://doi.org/10.5194/amt-11-2717-2018

Articles | Volume 11, issue 5

https://doi.org/10.5194/amt-11-2717-2018

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

https://doi.org/10.5194/amt-11-2717-2018

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

Articles | Volume 11, issue 5

Research article

|

08 May 2018

Research article |

| 08 May 2018

Instantaneous variance scaling of AIRS thermodynamic profiles using a circular area Monte Carlo approach

Jesse Dorrestijn, Brian H. Kahn, João Teixeira, and Fredrick W. Irion

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Final revised paper (published on 08 May 2018)
Preprint (discussion started on 03 Jan 2018)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Referee comment', Anonymous Referee #1, 06 Feb 2018
- AC1: 'response to reviewer 1', Brian Kahn, 20 Feb 2018
- AC4: 'final respinse to reviewer #1', Brian Kahn, 28 Mar 2018
RC2: 'Dorrestijn_al_2018_review', Anonymous Referee #2, 06 Feb 2018
- AC2: 'response to reviewer #2', Brian Kahn, 20 Feb 2018
- AC3: 'final response to reviewer #2', Brian Kahn, 28 Mar 2018

Peer-review completion

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

AR by Brian Kahn on behalf of the Authors (31 Mar 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (03 Apr 2018) by Andrew Sayer

RR by Anonymous Referee #2 (17 Apr 2018)

ED: Publish as is (18 Apr 2018) by Andrew Sayer

Short summary

Atmospheric Infrared Sounder (AIRS) satellite observations are used to quantify the scale-dependent variance of temperature and water vapor in the atmosphere. The scale dependence is much more variable than previously thought, using a new methodology based on individual satellite swaths. A break in the scale dependence is found to vary from less than 100 to greater than 1000 km. These new variance scaling results are of high importance for improving climate GCM subgrid parameterizations.