Abstract
<strong class="journal-contentHeaderColor">Abstract.</strong> The EarthCARE satellite mission’s objective is to retrieve profiles of the aerosol and water cloud physical properties using the combination of cloud-profiling radar (CPR), high spectral resolution UV lidar (ATLID), and passive multi-spectral spectral imager (MSI) data. Based on synergistic retrievals using data from these instruments, the 3D atmospheric cloud/aerosol state is estimated, which then are used to forward modelled radiative properties, which may then be compared to co-incident broad band radiometer (BBR) measurements. A high spectral resolution lidar enables the independent retrieval of extinction and backscatter but, being space-based, suffers from relatively high signal-to-noise levels. The ATLID FeatureMask (A-FM) product provides a probability mask for the existence of atmospheric features within the lidar profiles. Next to this, it also identifies those regions where the lidar beam has been fully attenuated and when the surface has impacted the measured lidar backscatter signals. From the pixels assigned as clear sky with no features present above, the clear sky averaged profiles for the three ATLID channels, the co-polar Mie channel, the total cross channel and the co-polar Rayleigh channel, are created. These ‘feature-free’ or ‘clear-sky’ profiles are useful for e.g. the quality of the ATLID l1 attenuated backscatters. The scientific goals of the A-FM product is to guide smoothing strategies within the ATLID profile retrieval algorithm which is one step further in the EarthCARE L2 processing chain. As a secondary product a frame-by-frame evaluation of the ATLID L1b cross talk calibration can be preformed by comparing the retrieved clear sky profiles to the expected channel profiles. The A-FM algorithm has been evaluated thoroughly using the synthetic test scenes. The A-FM product has been applied to both synthetic data from the EarthCARE end-to-end simulator (ECSIM) ass well as ALADIN L1 data from the Aeolus wind-lidar mission. Comparisons against the ECSIM model truth indicate A-FM has a percentage correctness > 0.9 and is capable of reliably detecting aerosol and cloud regions with extinctions > 1E-5 m<sup>−1</sup>.
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