Investigating Spaceborne Millimeter-Wave Ice Cloud Imager Geolocation Using Landmark Targets and Frequency-Scaling Approach

Abstract

The forthcoming spaceborne Ice Cloud Imager (ICI) radiometer has 11 channels in the millimeter (mm) and sub-mm wave range from 183 up to 664 GHz. At some of these frequencies, the atmosphere is very opaque due to strong gaseous and cloud extinction, precluding the observation of the surface. We aim at investigating how to evaluate the ICI channels geolocation error using surface landmark targets. The most transparent ICI channels, i.e., those around 183.3 ± 7.0 GHz at vertical (V) polarization (ICI-1) and around 243.2 ± 2.5 GHz (ICI-4) at horizontal (H)/ V polarization, are considered. Starting from a previous work, we extend the database of the surface landmark targets to cover boreal and austral dry seasons at various latitudes. For testing the geolocation approach, we use satellite Special Sensor Microwave Imager/Sounder (SSMIS) available data at 183.31 ± 6.6 GHz at H-polarization during 2017, obtaining an overall mean error of about 5.0 km and standard deviation of about 2.2 km, well within the ICI geolocation error assessment specifications. Since no imagers are available at 243 GHz, we extrapolate SSMIS data to 243.2 ± 2.5 GHz using a model-based neural-network approach, named Blended Artificial-neural-network Microwave Imager Simulator (BAMIS). The latter is trained by radiative-transfer simulations and global-scale atmospheric reanalyses data as well as SSMIS data. Results confirm that the proposed approach can be successfully exploited for ICI-4 geolocation error assessment at 243.2 ± 2.5 GHz, with results close to those obtained for the SSMIS 183.31 ± 6.6-GHz channel.