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Titel |
Validation of OMI total ozone retrievals from the SAO ozone profile algorithm and three operational algorithms with Brewer measurements |
VerfasserIn |
J. Bak, X. Liu, J. H. Kim, K. Chance, D. P. Haffner |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1680-7316
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Digitales Dokument |
URL |
Erschienen |
In: Atmospheric Chemistry and Physics ; 15, no. 2 ; Nr. 15, no. 2 (2015-01-19), S.667-683 |
Datensatznummer |
250119332
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Publikation (Nr.) |
copernicus.org/acp-15-667-2015.pdf |
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Zusammenfassung |
The accuracy of total ozone computed from the Smithsonian Astrophysical
Observatory (SAO) optimal estimation (OE) ozone profile algorithm (SOE)
applied to the Ozone Monitoring Instrument (OMI) is assessed through
comparisons with ground-based Brewer spectrometer measurements from 2005 to
2008. We also compare the three OMI operational ozone products, derived from
the NASA Total Ozone Mapping Spectrometer (TOMS) algorithm, the KNMI (Royal Netherlands Meteorological
Institute)
differential optical absorption spectroscopy (DOAS) algorithm, and KNMI's
Optimal Estimation (KOE) algorithm. The best agreement is observed between
SAO and Brewer, with a mean difference of within 1% at most individual
stations. The KNMI OE algorithm systematically overestimates Brewer total
ozone by 2% at low and mid-latitudes and 5% at high latitudes while the
TOMS and DOAS algorithms underestimate it by ~1.65% on
average. Standard deviations of ~1.8% are calculated for
both SOE and TOMS, but DOAS and KOE have higher values of 2.2% and
2.6%, respectively. The stability of the SOE algorithm is found to have
insignificant dependence on viewing geometry, cloud parameters, or total
ozone column. In comparison, the KOE–Brewer differences are significantly
correlated with solar and viewing zenith angles and show significant
deviations depending on cloud parameters and total ozone amount. The TOMS
algorithm exhibits similar stability to SOE with respect to viewing geometry
and total column ozone, but has stronger cloud parameter dependence. The
dependence of DOAS on observational geometry and geophysical conditions is
marginal compared to KOE, but is distinct compared to the SOE and TOMS
algorithms. Comparisons of all four OMI products with Brewer show no
apparent long-term drift, but seasonal features are evident, especially for
KOE and TOMS. The substantial differences in the KOE vs. SOE algorithm
performance cannot be sufficiently explained by the use of soft calibration
(in SOE) and the use of different a priori error covariance matrices;
however, other algorithm details cause fitting residuals larger by a factor
of 2–3 for KOE. |
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