Reflectance-based cross-calibration of GOME and SCIAMACHY spectrometers enhanced by polarization monitoring devices data

Abstract

Spectrometer instruments have significantly contributed to monitoring atmospheric composition and climate change for decades. Among them, the Global Ozone Monitoring Experiment (GOME, 1995–2011) and the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY, 2002–2012) were two well-known sensors whose missions overlapped by nearly a decade. Both instruments provided valuable data for atmospheric applications. However, to ensure data consistency and extend long-term time series, cross-calibration between the two instruments is important. The Fundamental Data Record for Atmospheric Composition (FDR4ATMOS) project, initiated by the European Space Agency (ESA), aims at harmonizing GOME and SCIAMACHY Level 1 data, i.e., irradiance and reflectance measurements. This paper presents, for the first time, a cross-calibration methodology for the top-of-atmosphere (TOA) reflectance of the spectrometers developed within the FDR4ATMOS project. Sub-pixel variability analysis, based on Polarization Monitoring Devices (PMD) data, enabled the evaluation of the homogeneity and similarity of the scene as observed by GOME and SCIAMACHY, thereby reducing the uncertainty in the cross-calibration process. Key challenges, including differing spatial resolutions, the absence of exact spatiotemporal overlap, and the need to preserve spectral structure, were addressed through targeted strategies. These included the selection of scenes with minimal acquisition time differences over Pseudo-Invariant Calibration Sites (PICS) characterized by stable meteorological and atmospheric conditions. A critical step consisted of spatially weighted averaging of SCIAMACHY pixels within each GOME footprint, followed by the computation of spectral channel–wise ratios across Bands 2B, 3, and 4, covering the ultraviolet, visible, and near-infrared (UV/VIS/NIR) spectral regions where many dominant trace gases are present. Furthermore, PMD data from both GOME and SCIAMACHY were analyzed to assess the spatial homogeneity of the pixels used in the cross-calibration and to evaluate its impact on cross-calibration performance. Observations under near-clear-sky conditions from 2003 were collocated over PICS and used to derive transfer functions (TFs). Polynomial TFs were fitted for Bands 2B and 3, while a constant TF was used for Band 4. The TFs showed dependence on viewing zenith angle (VZA), degradation, and wavelength. The uncertainty in the TFs increased with wavelength due to decreasing homogeneity of the cross-calibrated pixels, as indicated by the PMD data analysis, where pixel-to-pixel variability became larger. Using PMD measurements from cross-calibrated pixels as an indicator to filter out non-homogeneous pixels of the main spectral channels resulted in an uncertainty reduction of up to 70 % in the TFs. Overall, the presented cross-calibration approach and PMD-based analysis provide a pathway toward generating consistent and long-term spectrometer records. This work highlights the potential for extending the cross-calibration beyond traditional PICS and ideally suited scenes, increasing robustness across varied surfaces and atmospheric conditions.