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Geophysical validation and long-term consistency between GOME-2/MetOp-A total ozone column and measurements from the sensors GOME/ERS-2, SCIAMACHY/ENVISAT and OMI/Aura

dc.contributor.authorKoukouli, M.E.
dc.contributor.authorBalis, D.S.
dc.contributor.authorLoyola, D.
dc.contributor.authorValks, P.
dc.contributor.authorZimmer, W.
dc.contributor.authorHao, N.
dc.contributor.authorLambert, J.-C.
dc.contributor.authorVan Roozendael, M.
dc.contributor.authorLerot, C.
dc.contributor.authorSpurr, R.J.D.
dc.date2012
dc.date.accessioned2016-03-29T10:07:37Z
dc.date.available2016-03-29T10:07:37Z
dc.identifier.urihttps://orfeo.belnet.be/handle/internal/3024
dc.descriptionThe main aim of the paper is to assess the consistency of five years of Global Ozone Monitoring Experiment-2/Metop-A [GOME-2] total ozone columns and the longterm total ozone satellite monitoring database already in existence through an extensive inter-comparison and validation exercise using as reference Brewer and Dobson groundbased measurements. The behaviour of the GOME-2 measurements is being weighed against that of GOME (1995-2011), Ozone Monitoring Experiment [OMI] (since 2004) and the Scanning Imaging Absorption spectroMeter for Atmospheric CartograpHY [SCIAMACHY] (since 2002) total ozone column products. Over the background truth of the ground-based measurements, the total ozone columns are inter-evaluated using a suite of established validation techniques; the GOME-2 time series follow the same patterns as those observed by the other satellite sensors. In particular, on average, GOME-2 data underestimate GOME data by about 0.80 %, and underestimate SCIAMACHY data by 0.37% with no seasonal dependence of the differences between GOME-2, GOME and SCIAMACHY. The latter is expected since the three datasets are based on similar DOAS algorithms. This underestimation of GOME-2 is within the uncertainty of the reference data used in the comparisons. Compared to the OMI sensor, on average GOME-2 data underestimate OMI DOAS (collection 3) data by 1.28 %, without any significant seasonal dependence of the differences between them. The lack of seasonality might be expected since both the GOME data processor [GDP] 4.4 and OMI DOAS are DOAS-type algorithms and both consider the variability of the stratospheric temperatures in their retrievals. Compared to the OMI TOMS (collection 3) data, no bias was found. We hence conclude that the GOME-2 total ozone columns are well suitable to continue the longterm global total ozone record with the accuracy needed for climate monitoring studies.
dc.languageeng
dc.titleGeophysical validation and long-term consistency between GOME-2/MetOp-A total ozone column and measurements from the sensors GOME/ERS-2, SCIAMACHY/ENVISAT and OMI/Aura
dc.typeArticle
dc.subject.frascatiEarth and related Environmental sciences
dc.audienceScientific
dc.subject.freeair temperature
dc.subject.freealgorithm
dc.subject.freeatmospheric chemistry
dc.subject.freeAura (satellite)
dc.subject.freeEnvisat-1
dc.subject.freeERS-2
dc.subject.freegeophysical survey
dc.subject.freeGOME
dc.subject.freeground-based measurement
dc.subject.freelong-term change
dc.subject.freeozone
dc.subject.freesatellite data
dc.subject.freeSCIAMACHY
dc.source.titleAtmospheric Measurement Techniques
dc.source.volume5
dc.source.issue9
dc.source.page2169-2181
Orfeo.peerreviewedYes
dc.identifier.doi10.5194/amt-5-2169-2012
dc.identifier.scopus2-s2.0-84867549596


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