Carbon monoxide total column retrievals from TROPOMI shortwave infrared measurements

Abstract

Abstract. The Tropospheric Monitoring Instrument (TROPOMI) spectrometer is the single payload of the Copernicus Sentinel 5 Precursor (S5P) mission. It measures Earth radiance spectra in the shortwave infrared spectral range around 2.3 µm with a dedicated instrument module. These measurements provide carbon monoxide (CO) total column densities over land, which for clear sky conditions are highly sensitive to the tropospheric boundary layer. For cloudy atmospheres over land and ocean, the column sensitivity changes according to the light path through the atmosphere. In this study, we present the physics-based operational S5P algorithm to infer atmospheric CO columns satisfying the envisaged accuracy (< 15 %) and precision (< 10 %) both for clear sky and cloudy observations with low cloud height. Here, methane absorption in the 2.3 µm range is combined with methane abundances from a global chemical transport model to infer information on atmospheric scattering. For efficient processing, we deploy a linearized two-stream radiative transfer model as forward model and a profile scaling approach to adjust the CO abundance in the inversion. Based on generic measurement ensembles, including clear sky and cloudy observations, we estimated the CO retrieval precision to be ≤ 11 % for surface albedo ≥ 0.03 and solar zenith angle ≤ 70 • . CO biases of ≤ 3 % are introduced by inaccuracies in the methane a priori knowledge. For strongly enhanced CO concentrations in the tropospheric boundary layer and for cloudy conditions, CO errors in the order of 8 % can be introduced by the retrieval of cloud parameters of our algorithm. Moreover, we estimated the effect of a distorted spectral instrument response due to the inhomogeneous illumination of the instrument entrance slit in the flight direction to be < 2 % with pseudo-random characteristics when averaging over space and time. Finally, the CO data exploitation is demonstrated for a TROPOMI orbit of simulated shortwave infrared measurements. Overall, the study demonstrates that for an instrument that performs in compliance with the pre-flight specifications, the CO product will meet the required product performance well.

Carbon monoxide column retrieval for clear-sky and cloudy atmospheres: a full-mission data set from SCIAMACHY 2.3 µm reflectance measurements

“…The SICOR algorithm settings are very similar to those of the TROPOMI CO data processor (Landgraf et al, 2016b, a) but with adaptions to account for the instrument degradation of the SCIAMACHY instrument (Borsdorff et al, 2016). It comprises two main processing steps: first a nonscattering retrieval for cloud detection and subsequently a scattering retrieval to infer CO column abundances.…”

“…For the SCIAMACHY measurements, we choose the spectral window 2311-2338 nm for both retrieval steps. This represents a wider retrieval window than in the TROPOMI settings, which are 2315-2324 nm for the non-scattering retrieval and 2324-2338 nm for the scattering retrieval (Landgraf et al, 2016b). This is necessary to account for the instrument degradation, e.g.…”

“…These parameters are used in a two stream radiative transfer solver 2S-LINTRAN to account for changes to the light path due to light scattering by clouds and aerosols. For cloudy conditions, the CO error induced by this radiative transfer solver occasionally reaches several percent (Landgraf et al, 2016b), but becomes marginal for regional measurement ensembles. The SICOR data product includes the retrieved CO column, its noise estimate and the column averaging kernel.…”

“…The SWIR measurements of TROPOMI and SCIAMACHY will be similar with respect to spectral coverage and resolution, but TROPOMI will have better spatial resolution (7 × 7 km 2 ), a larger signal-to-noise ratio and daily global coverage. Therefore, TROPOMI will extend the record of SWIR measurements from space, and because of its similarity to SCIA-MACHY, it is possible to use the same CO retrieval algorithm for both instruments and thereby provide a consistent data product for a long-term study of CO (Borsdorff et al, 2016;Landgraf et al, 2016b).…”

“…However, to properly interpret these measurements, one has to account for the shielding and scattering effect of clouds. For this purpose, Vidot et al (2012) and Landgraf et al (2016b) proposed the Shortwave Infrared CO Retrieval (SICOR) algorithm for the operational processing of the S5P mission. In addition to trace gas absorption, SICOR estimates two cloud parameters: cloud optical thickness and cloud height.…”