Articles | Volume 9, issue 1
Research article
26 Jan 2016
Research article |  | 26 Jan 2016

Carbon monoxide total columns from SCIAMACHY 2.3  µm atmospheric reflectance measurements: towards a full-mission data product (2003–2012)

T. Borsdorff, P. Tol, J. E. Williams, J. de Laat, J. aan de Brugh, P. Nédélec, I. Aben, and J. Landgraf

Abstract. We present a full-mission data product of carbon monoxide (CO) vertical column densities using the 2310–2338 nm SCIAMACHY reflectance measurements over clear-sky land scenes for the period January 2003–April 2012. The retrieval employs the SICOR algorithm, which will be used for operational data processing of the Sentinel-5 Precursor mission. The retrieval approach infers simultaneously carbon monoxide, methane and water vapour column densities together with a Lambertian surface albedo from individual SCIAMACHY measurements employing a non-scattering radiative transfer model. To account for the radiometric instrument degradation including the formation of an ice-layer on the 2.3 µm detector array, we consider clear-sky measurements over the Sahara as a natural calibration target. For these specific measurements, we spectrally calibrate the SCIAMACHY measurements and determine a spectral radiometric offset and the width of the instrument spectral response function as a function of time for the entire operational phase of the mission. We show that the smoothing error of individual clear-sky CO retrievals is less than ±1 ppb and thus this error contribution does not need to be accounted for in the validation considering the much higher retrieval noise. The CO data product is validated against measurements of ground-based Fourier transform infrared spectrometers at 27 stations of the NDACC-IRWG and TCCON network and MOZAIC/IAGOS aircraft measurements at 26 airports worldwide. Overall, we find a good agreement with TCCON measurements with a mean bias b  = −1.2 ppb and a station-to-station bias with σ  = 7.2 ppb. The negative sign of the bias means a low bias of SCIAMACHY CO with respect to TCCON. For the NDACC-IRWG network, we obtain a larger mean station bias of b  = −9.2 ppb with σ  = 8.1 ppb and for the MOZAIC/IAGOS measurements we find b  = −6.4 ppb with σ  = 5.6 ppb. The SCIAMACHY data set is subject to a small but significant bias trend of 1.47 ± 0.25 ppb yr−1. After trend correction, the bias with respect to MOZAIC/IAGOS observation is 2.5 ppb, with respect to TCCON measurements it is −4.6 ppb and with respect to NDACC-IRWG measurements −8.4 ppb. Hence, a discrepancy of 3.8 ppb remains between the global biases with NDACC-IRWG and TCCON, which is confirmed by directly comparing NDACC-IRWG and TCCON measurements. Generally, the scatter of the individual SCIAMACHY CO retrievals is high and dominated by large measurement noise. Hence, for practical usage of the data set, averaging of individual retrievals is required. As an example, we show that monthly mean SCIAMACHY CO retrievals, averaged separately over Northern and Southern Africa, reflect the spatial and temporal variability of biomass burning events in agreement with the global chemical transport model TM5.