Articles | Volume 11, issue 7
https://doi.org/10.5194/amt-11-4309-2018
https://doi.org/10.5194/amt-11-4309-2018
Research article
 | 
20 Jul 2018
Research article |  | 20 Jul 2018

Evaluating two methods of estimating error variances using simulated data sets with known errors

Therese Rieckh and Richard Anthes

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Therese Rieckh on behalf of the Authors (08 May 2018)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (23 May 2018) by Ad Stoffelen
RR by Anonymous Referee #1 (28 May 2018)
RR by Anonymous Referee #2 (08 Jun 2018)
ED: Publish subject to minor revisions (review by editor) (19 Jun 2018) by Ad Stoffelen
AR by Therese Rieckh on behalf of the Authors (25 Jun 2018)  Author's response   Manuscript 
ED: Publish subject to technical corrections (25 Jun 2018) by Ad Stoffelen
AR by Therese Rieckh on behalf of the Authors (26 Jun 2018)  Author's response   Manuscript 
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Short summary
We compare the two-cornered hat (2CH) and three-cornered hat (3CH) method for estimating the error variances of two or more independent data sets using simulated data with various error correlations and biases. We assess the accuracy of the 3CH and 2CH estimates and examine the sensitivity of the estimated error variances to the degree of error correlation between the data sets as well as sample size. The 3CH method is less sensitive to these factors and hence more accurate.