Non-Gaussian statistics in global atmospheric dynamics: a study with a 10&thinsp;240-member ensemble Kalman filter using an intermediate atmospheric general circulation model

Kondo, Keiichi; Miyoshi, Takemasa

doi:https://doi.org/10.5194/npg-26-211-2019

Articles | Volume 26, issue 3

https://doi.org/10.5194/npg-26-211-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/npg-26-211-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 3

Research article

|

08 Aug 2019

Research article |

| 08 Aug 2019

Non-Gaussian statistics in global atmospheric dynamics: a study with a 10 240-member ensemble Kalman filter using an intermediate atmospheric general circulation model

Keiichi Kondo and Takemasa Miyoshi

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Final revised paper (published on 08 Aug 2019)
Preprint (discussion started on 12 Nov 2018)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Referee report', Anonymous Referee #1, 03 Dec 2018
- AC1: 'Author response', Keiichi Kondo, 27 May 2019
RC2: 'Referee report', Anonymous Referee #2, 05 Dec 2018
- AC2: 'Author response', Keiichi Kondo, 27 May 2019
RC3: 'Reviewer's report', Anonymous Referee #3, 06 Dec 2018
- AC3: 'Author response', Keiichi Kondo, 27 May 2019
EC1: 'Revised version', Olivier Talagrand, 27 May 2019

Peer-review completion

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

AR by Keiichi Kondo on behalf of the Authors (27 May 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (31 May 2019) by Olivier Talagrand

RR by Anonymous Referee #2 (04 Jun 2019)

RR by Anonymous Referee #3 (10 Jun 2019)

RR by Anonymous Referee #1 (17 Jun 2019)

ED: Publish subject to minor revisions (review by editor) (18 Jun 2019) by Olivier Talagrand

AR by Keiichi Kondo on behalf of the Authors (28 Jun 2019) Author's response Manuscript

ED: Publish subject to technical corrections (28 Jun 2019) by Olivier Talagrand

AR by Keiichi Kondo on behalf of the Authors (01 Jul 2019) Author's response Manuscript

Short summary

This study investigates non-Gaussian statistics of the data from a 10240-member ensemble Kalman filter. The large ensemble size can resolve the detailed structures of the probability density functions (PDFs) and indicates that the non-Gaussian PDF is caused by multimodality and outliers. While the outliers appear randomly, large multimodality corresponds well with large analysis error, mainly in the tropical regions and storm track regions where highly nonlinear processes appear frequently.