Quantitative analysis of SCIAMACHY carbon monoxide total column measurements

Abstract

[1] This paper presents a first quantitative and systematic analysis of one year of SCIAMACHY Carbon Monoxide (CO) total column retrievals from the IMLM algorithm (v6.3) using a chemistry-transport model simulation. The global distribution of modeled and measured CO show similar spatial patterns: a north-south gradient, low CO over mountains, and high CO over emission regions. CO column errors due to instrument noise are closely related to surface albedo and are less than 6% for monthly means at high surface albedo locations, improving to $1% for ideal circumstances: cloud-free pixels, high surface albedo, and spatial averaging (3°Â 2°). Quantitative comparison shows that measured and modeled seasonality agree very well at several locations with different types of seasonal cycles. Differences between SCIAMACHY CO and model results are less than 13% except for regions with large instrument-noise errors. Differences larger than the 2s instrument-noise error (95% confidence interval) occur in some regions with small noise errors, for example southern Africa. In this case the SCIAMACHY CO variations are different from the model biomass-burning emission seasonal cycle and more in agreement with observed fire count seasonality. The comparison with model results indicates that despite unforeseen time-dependent instrument-calibration complications, SCIAMACHY CO total column retrievals are of sufficient quality to provide useful new information on the global distribution and variation of CO. Citation: de Laat, A. T.

Water vapour total columns from SCIAMACHY spectra in the 2.36 μm window

“…Retrieval results from measurements in this channel have been reported by Gloudemans et al (2005Gloudemans et al ( , 2006 and de Laat et al ( , 2007 applying the methods also used in this paper, and by and Frankenberg et al (2005) using somewhat different retrieval approaches.…”

“…Houweling et al, 2005;Gloudemans et al, 2005Gloudemans et al, , 2006Gloudemans et al, , 2009de Laat et al, , 2007. The retrievals are done including all the features described by Gloudemans et al (2009), using version 7.4 of the retrieval software, but a more elaborate calibration procedure had to be adopted for the effects of the ice layer on the detector window (cf.…”

Comparisons between SCIAMACHY and ground-based FTIR data for total columns of CO, CH<sub>4</sub>, CO<sub>2</sub> and N<sub>2</sub>O

“…However, the correlative data set, for 11 stations over one year only, becomes too small to make an honest assessment of whether monthly mean values over our collocation grid do reach the target precision. Quantitative studies for monthly averaged SCIAMACHY CO data on spatial scales of a few degrees are very promising (de Laat et al, 2006). It is however beyond the scope of this article, and often beyond the capabilities of our dataset, to validate any of such approaches.…”

“…The SCIAMACHY data for CO, CH 4 , CO 2 and N 2 O total columns investigated in this paper have been produced by the algorithms WFM-DOAS v0.5 and v0.4 (Weighting Function Modified DOAS, Institute for Environmental Physics, University of Bremen (Buchwitz et al, 2000(Buchwitz et al, , 2005ade Beek et al, 2006)), IMLM v6.3 (Iterative Maximum Likelihood Method, SRON (Schrijver, 1999;Gloudemans et al, 2005Gloudemans et al, , 2004de Laat et al, 2006)) and IMAP-DOAS v1.1 and v0.9 (Iterative Maximum A Posteriori-DOAS, University of Heidelberg (Frankenberg et al, 2005a, c)). So far, CO 2 and N 2 O data products have been provided by WFM-DOAS v0.4 only.…”

Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES)

“…SCIAMACHY measures solar backscattered radiation at 2.3 µm, which allows for nearly uniform sensitivity through the tropospheric column though with no vertical resolution (Buchwitz et al, 2004(Buchwitz et al, , 2005de Laat et al, 2006). Global coverage is obtained by SCIAMACHY for its nadir measurements in 6 days, but actual coverage is much reduced because of the low ocean reflectivity and the presence of clouds in the relatively large pixels (30 km×120 km) (Buchwitz et al, 2007;Gloudemans et al, 2005Gloudemans et al, , 2008.…”