SCIAMACHY is a passive imaging spectrometer onboard ENVISAT designed to obtain trace gas abundances from measured radiances and irradiances in the UV to SWIR range in nadir-, limb- and occultation-viewing modes. Its grating spectrometer introduces a substantial sensitivity to the polarization of the incoming light with nonnegligible effects on the radiometric calibration. To be able to correct for the polarization sensitivity, SCIAMACHY utilizes broadband Polarization Measurement Devices (PMDs). While for the nadir-viewing mode the measured atmospheric polarization has been validated against POLDER data (Tilstra and Stammes, 2007, 2010), a similar validation study regarding the limb-viewing mode has not yet been performed. This paper aims at an assessment of the quality of the SCIAMACHY limb polarization data. Since limb polarization measurements by other air/spaceborne instruments in the spectral range of SCIAMACHY are not available, a comparison with radiative transfer simulations by SCIATRAN V3.1 (Rozanov et al., 2013) using a wide range of atmospheric parameters is performed. SCIATRAN is a vector radiative transfer model (VRTM) capable of performing calculations of the multiply scattered radiance in a spherically symmetric atmosphere. The study shows that the limb polarization data exhibit a large time-dependent bias that decreases with wavelength. Possible reasons for this bias are a still unknown combination of insufficient accuracy or inconsistencies of the on-ground calibration data, scan mirror degradation and stress induced changes of the polarization response of components inside the optical bench of the instrument. It is shown that it should in principle be feasible to recalibrate the effective polarization sensitivity of the instrument using the in-flight data and VRTM simulations. © Author(s) 2013.
CITATION STYLE
Liebing, P., Bramstedt, K., Noël, S., Rozanov, V., Bovensmann, H., & Burrows, J. P. (2013). Polarization data from SCIAMACHY limb backscatter observations compared to vector radiative transfer model simulations. Atmospheric Measurement Techniques, 6(6), 1503–1520. https://doi.org/10.5194/amt-6-1503-2013
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