Articles | Volume 11, issue 7
Atmos. Meas. Tech., 11, 4239–4260, 2018
https://doi.org/10.5194/amt-11-4239-2018
Atmos. Meas. Tech., 11, 4239–4260, 2018
https://doi.org/10.5194/amt-11-4239-2018

Research article 19 Jul 2018

Research article | 19 Jul 2018

Estimating observation and model error variances using multiple data sets

Richard Anthes and Therese Rieckh

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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 (10 May 2018)  Author's response    Manuscript
ED: Reconsider after major revisions (23 May 2018) by Ad Stoffelen
AR by Therese Rieckh on behalf of the Authors (21 Jun 2018)  Author's response    Manuscript
ED: Publish as is (22 Jun 2018) by Ad Stoffelen
AR by Therese Rieckh on behalf of the Authors (25 Jun 2018)  Author's response    Manuscript
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Short summary
We show how multiple data sets, including observations and models, can be combined using the "N-cornered hat method" to estimate vertical profiles of the errors of each system. Using data from 2007, we estimate the error variances of radio occultation, radiosondes, ERA-Interim, and GFS model data sets at four radiosonde locations in the tropics and subtropics. A key assumption is the neglect of error correlations among the different data sets, and we examine the consequences of this assumption.