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| Titel |
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 |
| VerfasserIn |
M. E. Koukouli, D. S. Balis, D. Loyola, P. Valks, W. Zimmer, N. Hao, J.-C. Lambert, M. Roozendael, C. Lerot, R. J. D. Spurr |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 5, no. 9 ; Nr. 5, no. 9 (2012-09-07), S.2169-2181 |
| Datensatznummer |
250003084
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| Publikation (Nr.) |
 copernicus.org/amt-5-2169-2012.pdf |
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| Zusammenfassung |
| The 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 long-term total ozone satellite monitoring database
already in existence through an extensive inter-comparison and validation
exercise using as reference Brewer and Dobson ground-based 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
long-term global total ozone record with the accuracy needed for
climate
monitoring studies. |
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