Improved retrieval of global tropospheric formaldehyde columns from GOME-2/MetOp-A addressing noise reduction and instrumental degradation issues

Abstract

Abstract. We present a new dataset of formaldehyde vertical columns retrieved from observations of GOME-2 on board the EUMETSAT MetOp-A platform between 2007 and 2011. The new retrieval scheme, which has been optimised for GOME-2, includes a two-step fitting procedure that strongly reduces the impact of spectral interferences between H2CO and BrO, and a modified DOAS approach that better handles ozone absorption effects at moderately low sun elevations. Owing to these new features, the noise in the H2CO slant columns is reduced by up to 40% in comparison to baseline retrieval settings used operationally. Also, the previously reported underestimation of the H2CO columns in tropical and mid-latitude regions has been largely eliminated, improving the agreement with coincident SCIAMACHY observations. To compensate for the drift of the GOME-2 slit function and to mitigate the instrumental degradation effects on H2CO retrievals, an asymmetric Gaussian line-shape is fitted during the irradiance calibration. Additionally, external parameters used in the tropospheric air mass factor computation (surface reflectances, cloud parameters and a priori profile shapes of H2CO) have been updated using most recent databases. Similar updates were also applied to the historical datasets of GOME and SCIAMACHY, leading to the generation of a consistent multi-mission H2CO data record covering the time period from 1997 until 2011. Comparing the resulting time series of monthly averaged H2CO vertical columns in 12 large regions worldwide, the correlation coefficient between SCIAMACHY and GOME-2 columns is generally higher than 0.8 in the overlap period, and linear regression slopes differ by less than 10% from unity in most of the regions. In comparison to SCIAMACHY, the largely improved spatial sampling of GOME-2 allows for a better characterisation of formaldehyde distribution at the regional scale and/or at shorter timescales, leading to a better identification of the emission sources of non-methane volatile organic compounds.