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      Characterization and correction of stray light in TROPOMI-SWIR

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          Abstract

          <p><strong>Abstract.</strong> The shortwave infrared (SWIR) spectrometer module of the Tropospheric Monitoring Instrument (TROPOMI), on board the ESA Copernicus Sentinel-5 Precursor satellite, is used to measure atmospheric CO and methane columns. For this purpose, calibrated radiance measurements are needed that are minimally contaminated by instrumental stray light. Therefore, a method has been developed and applied in an on-ground calibration campaign to characterize stray light in detail using a monochromatic quasi-point light source. The dynamic range of the signal was extended to more than 7 orders of magnitude by performing measurements with different exposure times, saturating detector pixels at the longer exposure times. Analysis of the stray light indicates about 4.4 % of the detected light is correctable stray light. An algorithm was then devised and implemented in the operational data processor to correct in-flight SWIR observations in near-real time, based on Van Cittert deconvolution. The stray light is approximated by a far-field kernel independent of position and wavelength and an additional kernel representing the main reflection. Applying this correction significantly reduces the stray-light signal, for example in a simulated dark forest scene close to bright clouds by a factor of about 10. Simulations indicate that this reduces the stray-light error sufficiently for accurate gas-column retrievals. In addition, the instrument contains five SWIR diode lasers that enable long-term, in-flight monitoring of the stray-light distribution.</p>

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          TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications

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            Zum Einfluß der Spaltbreite auf die Intensitätsverteilung in Spektrallinien. II

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              The operational methane retrieval algorithm for TROPOMI

              Abstract. This work presents the operational methane retrieval algorithm for the Sentinel 5 Precursor (S5P) satellite and its performance tested on realistic ensembles of simulated measurements. The target product is the column-averaged dry air volume mixing ratio of methane (XCH 4 ), which will be retrieved simultaneously with scattering properties of the atmosphere. The algorithm attempts to fit spectra observed by the shortwave and near-infrared channels of the TROPOspheric Monitoring Instrument (TROPOMI) spectrometer aboard S5P. The sensitivity of the retrieval performance to atmospheric scattering properties, atmospheric input data and instrument calibration errors is evaluated. In addition, we investigate the effect of inhomogeneous slit illumination on the instrument spectral response function. Finally, we discuss the cloud filters to be used operationally and as backup. We show that the required accuracy and precision of &lt; 1 % for the XCH 4 product are met for clear-sky measurements over land surfaces and after appropriate filtering of difficult scenes. The algorithm is very stable, having a convergence rate of 99 %. The forward model error is less than 1 % for about 95 % of the valid retrievals. Model errors in the input profile of water do not influence the retrieval outcome noticeably. The methane product is expected to meet the requirements if errors in input profiles of pressure and temperature remain below 0.3 % and 2 K, respectively. We further find that, of all instrument calibration errors investigated here, our retrievals are the most sensitive to an error in the instrument spectral response function of the shortwave infrared channel.
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                Author and article information

                Journal
                Atmospheric Measurement Techniques
                Atmos. Meas. Tech.
                Copernicus GmbH
                1867-8548
                2018
                July 27 2018
                : 11
                : 7
                : 4493-4507
                Article
                10.5194/amt-11-4493-2018
                0728b976-1949-4f0c-8c1b-f376f2e0fbe5
                © 2018

                https://creativecommons.org/licenses/by/4.0/

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