Glyoxal vertical columns from GOME-2 backscattered light measurements and comparisons with a global model

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Discipline
Earth and related Environmental sciences
Subject
air mass
algorithm
atmospheric chemistry
atmospheric modeling
atmospheric transport
backscatter
error analysis
GOME
organic compound
radiative transfer
satellite sensor
vertical distribution
Asia
Audience
Scientific
Date
2010Metadata
Show full item recordDescription
Glyoxal vertical column densities have been retrieved from nadir backscattered radiances measured from 2007 to 2009 by the spaceborne GOME-2/METOP-A sensor. The retrieval algorithm is based on the DOAS technique and optimized settings have been used to determine glyoxal slant columns. The liquid water absorption is accounted for using a two-step DOAS approach, leading to a drastic improvement of the fit quality over remote clear water oceans. Air mass factors are calculated by means of look-up tables of weighting functions pre-calculated with the LIDORT v3.3 radiative transfer model and using a priori glyoxal vertical distributions provided by the IMAGESv2 chemical transport model. The total error estimate comprises random and systematic errors associated to the DOAS fit, the air mass factor calculation and the cloud correction. The highest glyoxal vertical column densities are mainly observed in continental tropical regions, while the mid-latitude columns strongly depend on the season with maximum values during warm months. An anthropogenic signature is also observed in highly populated regions of Asia. Comparisons with glyoxal columns simulated with IMAGESv2 in different regions of the world generally point to a missing glyoxal source, most probably of biogenic origin.
Citation
Lerot, C.; Stavrakou, T.; De Smedt, I.; Müller, J.-F.; Van Roozendael, M. (2010). Glyoxal vertical columns from GOME-2 backscattered light measurements and comparisons with a global model. , Atmospheric Chemistry and Physics, Vol. 10, Issue 24, 12059-12072, DOI: 10.5194/acp-10-12059-2010.Identifiers
scopus: 2-s2.0-78650372101
Type
Article
Peer-Review
Yes
Language
eng