Reducing representativeness and sampling errors in radio occultation–radiosonde comparisons

Gilpin, Shay; Rieckh, Therese; Anthes, Richard

doi:https://doi.org/10.5194/amt-11-2567-2018

Articles | Volume 11, issue 5

https://doi.org/10.5194/amt-11-2567-2018

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

https://doi.org/10.5194/amt-11-2567-2018

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

Articles | Volume 11, issue 5

Research article

|

03 May 2018

Research article |

| 03 May 2018

Reducing representativeness and sampling errors in radio occultation–radiosonde comparisons

Shay Gilpin, Therese Rieckh, and Richard Anthes

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Final revised paper (published on 03 May 2018)
Preprint (discussion started on 31 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 report', Anonymous Referee #1, 21 Feb 2018
- AC1: 'Response to Referee #1', Shay Gilpin, 29 Mar 2018
RC2: 'accepted after revision', Anonymous Referee #2, 01 Mar 2018
- AC2: 'Response to Referee #2', Shay Gilpin, 29 Mar 2018
RC3: 'comments', Anonymous Referee #3, 07 Mar 2018
- AC3: 'Response to Referee #3', Shay Gilpin, 29 Mar 2018

Peer-review completion

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

AR by Shay Gilpin on behalf of the Authors (29 Mar 2018) Author's response Manuscript

ED: Publish as is (15 Apr 2018) by Marcos Portabella

AR by Shay Gilpin on behalf of the Authors (16 Apr 2018)

Short summary

Comparing observational systems when observations are not taken at the exact same time or location can introduce sampling errors that can be come significant during error analysis. In this study, we develop two methods to reduce sampling errors: using ellipse distance constraints rather than circles and subtracting model background. We found that both the ellipses and subtracting model background from the observations reduce sampling errors caused by spatial and temporal differences.