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dc.contributor.author
Ball, William T.
dc.contributor.author
Alsing, Justin
dc.contributor.author
Mortlock, Daniel J.
dc.contributor.author
Rozanov, Eugene
dc.contributor.author
Tummon, Fiona
dc.contributor.author
Haigh, Joanna D.
dc.date.accessioned
2017-12-20T11:20:32Z
dc.date.available
2017-10-29T02:48:08Z
dc.date.available
2017-12-20T11:20:32Z
dc.date.issued
2017
dc.identifier.issn
1680-7324
dc.identifier.issn
1680-7375
dc.identifier.other
10.5194/acp-17-12269-2017
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/202027
dc.identifier.doi
10.3929/ethz-b-000202027
dc.description.abstract
Observations of stratospheric ozone from multiple instruments now span three decades; combining these into composite datasets allows long-term ozone trends to be estimated. Recently, several ozone composites have been published, but trends disagree by latitude and altitude, even between composites built upon the same instrument data. We confirm that the main causes of differences in decadal trend estimates lie in (i) steps in the composite time series when the instrument source data changes and (ii) artificial sub-decadal trends in the underlying instrument data. These artefacts introduce features that can alias with regressors in multiple linear regression (MLR) analysis; both can lead to inaccurate trend estimates. Here, we aim to remove these artefacts using Bayesian methods to infer the underlying ozone time series from a set of composites by building a joint-likelihood function using a Gaussian-mixture density to model outliers introduced by data artefacts, together with a data-driven prior on ozone variability that incorporates knowledge of problems during instrument operation. We apply this Bayesian self-calibration approach to stratospheric ozone in 10° bands from 60° S to 60° N and from 46 to 1 hPa (∼ 21–48 km) for 1985–2012. There are two main outcomes: (i) we independently identify and confirm many of the data problems previously identified, but which remain unaccounted for in existing composites; (ii) we construct an ozone composite, with uncertainties, that is free from most of these problems – we call this the BAyeSian Integrated and Consolidated (BASIC) composite. To analyse the new BASIC composite, we use dynamical linear modelling (DLM), which provides a more robust estimate of long-term changes through Bayesian inference than MLR. BASIC and DLM, together, provide a step forward in improving estimates of decadal trends. Our results indicate a significant recovery of ozone since 1998 in the upper stratosphere, of both northern and southern midlatitudes, in all four composites analysed, and particularly in the BASIC composite. The BASIC results also show no hemispheric difference in the recovery at midlatitudes, in contrast to an apparent feature that is present, but not consistent, in the four composites. Our overall conclusion is that it is possible to effectively combine different ozone composites and account for artefacts and drifts, and that this leads to a clear and significant result that upper stratospheric ozone levels have increased since 1998, following an earlier decline.
en_US
dc.format
application/pdf
dc.language.iso
en
en_US
dc.publisher
European Geophysical Society
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/3.0/
dc.title
Reconciling differences in stratospheric ozone composites
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 3.0 Unported
dc.date.published
2017-10-16
ethz.journal.title
Atmospheric Chemistry and Physics
ethz.journal.volume
17
en_US
ethz.journal.issue
20
en_US
ethz.journal.abbreviated
Atmos. Chem. Phys.
ethz.pages.start
12269
en_US
ethz.pages.end
12302
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.grant
SPARC International Project office
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Munich
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02717 - Institut für Atmosphäre und Klima / Inst. Atmospheric and Climate Science::03517 - Peter, Thomas (emeritus) / Peter, Thomas (emeritus)
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02717 - Institut für Atmosphäre und Klima / Inst. Atmospheric and Climate Science::03517 - Peter, Thomas (emeritus) / Peter, Thomas (emeritus)
ethz.grant.agreementno
138017
ethz.grant.fundername
SNF
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.program
Forschungsinfrastrukturen
ethz.date.deposited
2017-10-29T02:48:11Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-12-20T11:20:39Z
ethz.rosetta.lastUpdated
2023-02-06T15:01:55Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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