Processing and quality control of FY-3C GNOS data  used in numerical weather prediction applications

Liao, Mi; Healy, Sean; Zhang, Peng

doi:https://doi.org/10.5194/amt-12-2679-2019

Articles | Volume 12, issue 5

https://doi.org/10.5194/amt-12-2679-2019

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

https://doi.org/10.5194/amt-12-2679-2019

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

Articles | Volume 12, issue 5

Research article

|

09 May 2019

Research article |

| 09 May 2019

Processing and quality control of FY-3C GNOS data used in numerical weather prediction applications

Mi Liao, Sean Healy, and Peng Zhang

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Final revised paper (published on 09 May 2019)
Preprint (discussion started on 14 Nov 2018)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review of Liao, Healy and Zhang, amt-2018-271', Anonymous Referee #2, 26 Nov 2018
- SC4: 'Author comment to review1', Mi Liao, 20 Dec 2018
- AC1: 'Final response to reviewer#1', Mi Liao, 03 Feb 2019
RC2: 'Review of paper “Processing and quality control with FY3C/GNOS data used in numerical weather prediction applications”', Anonymous Referee #1, 07 Dec 2018
- SC3: 'Author comments to review2', Mi Liao, 20 Dec 2018
  - AC1: 'Final response to reviewer#1', Mi Liao, 03 Feb 2019
- SC5: 'Additional statistics plots requested by reviewer 2', Sean Healy, 20 Dec 2018
- AC2: 'Final response to review#2', Mi Liao, 06 Feb 2019
RC3: 'Reviewer_Report', Anonymous Referee #3, 12 Dec 2018
- SC1: 'Review 3, Major Comment 3', Sean Healy, 14 Dec 2018
  - SC2: 'Review 3, Major Comment 7, Section 5', Sean Healy, 18 Dec 2018
- SC6: 'reply to RC3', Mi Liao, 07 Jan 2019
- AC3: 'final response to review#3', Mi Liao, 07 Feb 2019
- AC2: 'Final response to review#2', Mi Liao, 06 Feb 2019

Peer-review completion

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

AR by Mi Liao on behalf of the Authors (21 Mar 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (22 Mar 2019) by Joanna Joiner

RR by Anonymous Referee #1 (04 Apr 2019)

RR by Anonymous Referee #4 (14 Apr 2019)

ED: Publish as is (14 Apr 2019) by Joanna Joiner

Short summary

This paper describes a new method for improving the data of the Chinese radio occultation sounder, GNOS, which has large biases. The new method can effectively eliminate about 90 % of the large departures. In addition, this paper also describes the quality control (QC) for the GNOS data. The GNOS data with the new L2 extrapolation are suitable for assimilation into numerical weather prediction systems.