Improved retrieval of global tropospheric formaldehyde columns from GOME-2/MetOp-A addressing noise reduction and instrumental degradation issues
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 H 2CO 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 H 2CO slant columns is reduced by up to 40% in comparison to baseline retrieval settings used operationally. Also, the previously reported underestimation of the H 2CO 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 H 2CO 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 H 2CO) 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 H 2CO data record covering the time period from 1997 until 2011. Comparing the resulting time series of monthly averaged H 2CO 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.