Is it feasible to estimate radiosonde biases from interlaced measurements?

Kremser, Stefanie; Tradowsky, Jordis S.; Rust, Henning W.; Bodeker, Greg E.

doi:https://doi.org/10.5194/amt-11-3021-2018

Articles | Volume 11, issue 5

https://doi.org/10.5194/amt-11-3021-2018

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

https://doi.org/10.5194/amt-11-3021-2018

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

Articles | Volume 11, issue 5

Research article

|

24 May 2018

Research article |

| 24 May 2018

Is it feasible to estimate radiosonde biases from interlaced measurements?

Stefanie Kremser, Jordis S. Tradowsky, Henning W. Rust, and Greg E. Bodeker

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Final revised paper (published on 24 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: 'Review amt-2018-16 Kremser et al.', Anonymous Referee #1, 22 Feb 2018
- AC1: 'Response to Reviewer #1', Stefanie Kremser, 24 Apr 2018
RC2: 'Review report', Anonymous Referee #2, 20 Mar 2018
- AC2: 'Response to Reviewer #2', Stefanie Kremser, 24 Apr 2018

Peer-review completion

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

AR by Stefanie Kremser on behalf of the Authors (24 Apr 2018) Author's response Manuscript

ED: Publish as is (03 May 2018) by Roeland Van Malderen

AR by Stefanie Kremser on behalf of the Authors (04 May 2018) Manuscript

Short summary

We investigate the feasibility of quantifying the difference in biases of two instrument types (i.e. radiosondes) by flying the old and new instruments on alternating days, so-called interlacing, to statistically derive the systematic biases between the instruments. While it is in principle possible to estimate the difference between two instrument biases from interlaced measurements, the number of required interlaced flights is very large for reasonable autocorrelation coefficient values.