Algorithms for estimating precipitation from satellite data often use only the 10.7-micron infrared window channel. However, data from other channels in the visible and infrared regions have proven to be useful for deriving cloud properties, especially when differences between channels are considered. This capability has been exploited on a limited basis using Geostationary Operational Environmental Satellite (GOES) data by such algorithms as the GOES Multi-Spectral Rainfall Algorithm (GMSRA). However, the operational exploitation of multi-channel information for preciptiation applications has been limited by the relatively small channel selection presently available on the GOES imager.

The advent of the Advanced Baseline Imager (ABI) on the GOES-R series of satellites will expand the channel selection available on the GOES Imager from 5 to as many as 16 channels, providing a considerable amount of new multispectral data for operational satellite precipitation retrievals. To evaluate the potential impact of these new data on both rain/no rain discrimination and rain rate estimation, MODerate-resolution Imaging Spectroradiometer (MODIS) data have been amtched with 15-minute radar reflectivity composites and Stage IV radar/raingauge data sets for analysis. The findings are described, keeping in mind that the high optical thickness of raining clouds (and many non-raining clouds) limits the usefulness of multispectral data for these particular applications.