Quantitative bias estimates for tropospheric NO<sub>2</sub> columns retrieved from SCIAMACHY, OMI, and GOME-2 using a common standard for East Asia

Abstract

Abstract. For the intercomparison of tropospheric nitrogen dioxide (NO 2 ) vertical column density (VCD) data from three different satellite sensors (SCIAMACHY, OMI, and GOME-2), we use a common standard to quantitatively evaluate the biases for the respective data sets. As the standard, a regression analysis using a single set of collocated ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations at several sites in Japan and China from 2006-2011 is adopted. Examinations of various spatial coincidence criteria indicates that the slope of the regression line can be influenced by the spatial distribution of NO 2 over the area considered. While the slope varies systematically with the distance between the MAX-DOAS and satellite observation points around Tokyo in Japan, such a systematic dependence is not clearly seen and correlation coefficients are generally higher in comparisons at sites in China. On the basis of these results, we focus mainly on comparisons over China and estimate the biases in SCIAMACHY, OMI, and GOME-2 data (TM4NO2A and DOMINO version 2 products) against the MAX-DOAS observations to be −5 ± 14 %, −10 ± 14 %, and +1 ± 14 %, respectively, which are all small and insignificant. We suggest that these small biases now allow for analyses combining these satellite data for air quality studies, which are more systematic and quantitative than previously possible.

Recent satellite-based trends of tropospheric nitrogen dioxide over large urban agglomerations worldwide

“…There are now several stations worldwide providing observations from ground-based MAX-DOAS instruments (Hönninger et al, 2004;Irie et al, 2012;Kanaya et al, 2014;Hendrick et al, 2014), providing highly accurate measurements of tropospheric columns of various trace gases. Some of these stations now provide time series of 5 yr and more, thus allowing for a direct comparison of satellite-derived trends with trends obtained from a reliable reference source.…”

“…NO 2 retrievals from SCIAMACHY have been validated in numerous studies, e.g., by Heue et al (2005) using airborne multi-axis differential optical absorption spectroscopy observations, by Boersma et al (2009) using in situ surface observations in Israel, and by Irie et al (2012) using inter-comparison techniques with NO 2 products derived from other satellite instruments as well as multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations in Japan and China. The last one showed that SCIAMACHY-based tropospheric NO 2 columns were accurate with a −5 % bias and standard deviation of ±14 %.…”

An evaluation of IASI-NH<sub>3</sub> with ground-based Fourier transform infrared spectroscopy measurements

“…Furthermore, MAX-DOAS systems are used for the validation of retrievals for reactive gases (e.g. Irie et al, 2012), whereas AERONET is widely used to validate satellite-derived aerosol optical depth (e.g. Schaap et al, 2008).…”

Evaluation of OMI operational standard NO<sub>2</sub> column retrievals using in situ and surface-based NO<sub>2</sub> observations

“…Tropospheric NO 2 column retrievals from satellites have been evaluated with in situ NO 2 profile measurements from aircraft (Heland et al, 2002;Martin et al, 2006;Boersma et al, 2008a;Bucsela et al, 2008Bucsela et al, , 2013Celarier et al, 2008;Hains et al, 2010), NO 2 column measurements from groundbased and airborne instruments Celarier et al, 2008;Brinksma et al, 2008;Kramer et al, 2008;Irie et al, 2008Irie et al, , 2012Wenig et al, 2008;Oetjen et al, 2013), in situ surface measurements (Schaub et al, 2006;Blond et al, 2007;Boersma et al, 2009;Lamsal et al, 2008Lamsal et al, , 2010, and a bottom-up NO x emission inventory (Lamsal et al, 2010). Aircraft offer precise in situ measurements within vertical spirals covering a spatial domain over a satellite field of view, but these are generally campaign-based experiments spanning only a few days to weeks and are limited by the need to extrapolate below the lowest measurement altitude (e.g.…”