Masiello, G.; Serio, C.; Venafra, S.; Poutier, L.; Göttsche, F.-M. SEVIRI Hyper-Fast Forward Model with Application to Emissivity Retrieval. Sensors2019, 19, 1532.
Masiello, G.; Serio, C.; Venafra, S.; Poutier, L.; Göttsche, F.-M. SEVIRI Hyper-Fast Forward Model with Application to Emissivity Retrieval. Sensors 2019, 19, 1532.
Timely processing of observations from hyper-spectral imagers, such as SEVIRI (Spinning Enhanced Visible and Infrared Imager), largely depends on fast radiative transfer calculations. This paper mostly concerns the development and implementation of a new forward model for SEVIRI to be applied to real time processing of infrared radiances for the physical retrieval of surface temperature and emissivity. The new radiative transfer model improves computational time by a factor of ≈ 7 compared to the previous versions and makes it possible to process SEVIRI data at nearly real time. The new forward model has been applied for the simultaneous retrieval of surface temperature and emissivity in three infrared channels (8.7, 10.8, 12 μm). The inverse scheme relies on a Kalman filter approach, which allows us to exploit a sequential processing of SEVIRI observations. Based on the new forward model, the paper also presents a validation retrieval performed with in situ observations acquired during a field experiment carried out in 2017 at Gobabeb (Namib desert) validation station. Furthermore, a comparison with IASI (Infrared Atmospheric Sounder Interferometer) emissivity retrievals has been performed as well. It has been found that the retrieved emissivities are in good agreement with each other and with in situ observations, i.e. average differences are generally well below 0.01.
Fast Forward Model, Infrared, Emissivity Spectrum, Satellite, Validation
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