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

Abstract

Abstract. We discuss the retrieval of carbon monoxide (CO) vertical column densities from clear-sky and cloud contaminated 2311-2338 nm reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) from January 2003 until the end of the mission in April 2012. These data were processed with the Shortwave Infrared CO Retrieval algorithm (SICOR) that we developed for the operational data processing of the Tropospheric Monitoring Instrument (TROPOMI) that will be launched on ESA's Sentinel-5 Precursor (S5P) mission. This study complements previous work that was limited to clear-sky observations over land. Over the oceans, CO is estimated from cloudy-sky measurements only, which is an important addition to the SCIAMACHY clear-sky CO data set as shown by NDACC and TCCON measurements at coastal sites. For Ny-Ålesund, Lauder, Mauna Loa and Reunion, a validation of SCIAMACHY clear-sky retrievals is not meaningful because of the high retrieval noise and the few collocations at these sites. The situation improves significantly when considering cloudy-sky observations, where we find a low mean bias b = ±6.0 ppb and a strong correlation between the validation and the SCIAMACHY results with a mean Pearson correlation coefficient r = 0.7. Also for land observations, cloudy-sky CO retrievals present an interesting complement to the clear-sky data set. For example, at the cities Tehran and Beijing the agreement of SCIAMACHY clear-sky CO observations with MOZAIC/IAGOS airborne measurements is poor with a mean bias of b = 171.2 ppb and 57.9 ppb because of local CO pollution, which cannot be captured by SCIAMACHY. For cloudy-sky retrievals, the validation improves significantly. Here the retrieved column is mainly sensitive to CO above the cloud and so not affected by the strong local surface emissions. Adjusting the MOZAIC/IAGOS measurements to the vertical sensitivity of the retrieval, the mean bias adds up to b = 52.3 ppb and 5.0 ppb for Tehran and Beijing. At the less urbanised region around the airport Windhoek, local CO pollution is less prominent and so MOZAIC/IAGOS measurements agree well with SCIAMACHY clear-sky retrievals with a mean bias of b = 15.5 ppb, but can be even further improved for cloudy SCIAMACHY observations with a mean bias of b = 0.2 ppb. Overall the cloudy-sky CO retrievals from SCIA-MACHY short-wave infrared measurements present a major extension of the clear-sky-only data set, which more than triples the amount of data and adds unique observations over the oceans. Moreover, the study represents the first application of the S5P algorithm for operational CO data processing on cloudy observations prior to the launch of the S5P mission.

Validation of Carbon Monoxide Total Column Retrievals from SCIAMACHY Observations with NDACC/TCCON Ground-Based Measurements

“…In general, the results in Figure 7 agree with the findings by Borsdorff et al [9,10] within around −5 to −10% for most sites. However, the CO mixing ratios calculated from the BIRRA retrieval have consistently low bias with respect to all sites in both networks, while Borsdorff et al [9,10] found slightly positive biases at some sites.…”

“…However, the CO mixing ratios calculated from the BIRRA retrieval have consistently low bias with respect to all sites in both networks, while Borsdorff et al [9,10] found slightly positive biases at some sites. The data show different magnitudes of biases for different sites.…”

“…So far, only Borsdorff et al [9,10] have presented full-mission data set validation of SCIAMACHY CO vertical column densities employing the SICOR algorithm. Dils et al [25] considered SCIAMACHY data that covered the January to December 2003 time period that were produced using three different retrieval algorithms, namely the WFM-DOAS algorithm (version 0.5 for CO), the IMAP-DOAS method (version 0.9 for CO), and the IMLM (version 6.3).…”

“…In recent years, additional validation efforts have been carried out by Borsdorff et al [9,10], De Laat et al [21], and Schneising et al [26]. Borsdorff et al [9] additionally included Tracer Model version 5 (TM5) data for large-scale (northern and southern hemispheric Africa) intercomparison and Measurement of Ozone on Airbus In-service Aircraft (MOZAIC)/In-service Aircraft for Global Observing System (IAGOS) measurements.…”

“…Several codes have been developed for SCIAMACHY nadir SWIR spectra at different European institutes, e.g., the Weighted Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS) algorithm [5,6], the Iterative Maximum A Posteriori (IMAP)-DOAS [7] method, the Iterative Maximum Likelihood Method (IMLM) [3], and the Beer InfraRed Retrieval Algorithm (BIRRA) [8]. Recently, SCIAMACHY spectra have also been processed with the Shortwave Infrared CO Retrieval (SICOR) algorithm developed for the operational data processing of the Tropospheric Monitoring Instrument (TROPOMI) that was launched on the European Space Agency's (ESA) Sentinel-5 Precursor (S5P) mission [9,10]. Concurrent validation is a crucial task in processor/algorithm development in order to confirm applicability for scientific tasks and ultimately qualify operational algorithms or scientific tools.…”