The Advanced Baseline Imager (ABI) aboard the GOES-R series will have a number of additional spectral channels at significantly improved spatial and temporal resolution compared to the current GOES Imager. This wealth of data likely contains some useful information about the pre-storm environment as well as active thunderstorms. In designing new algorithms to extract this information, one must find the most suitable combination of bands.

This paper describes how we take simulated ABI imagery at the proper spatial and temporal resolution and calculate Principal Component (PC) images. PC imagery highlights areas which explain the most variance in the data, and the corresponding eigenvectors can be used to determine what linear combination of spectral bands is most suitable for studying certain features. For example, in looking at low-level moisture depth, PC Analysis has revealed that a certain combination of the 11.2, 12.3, and 13.3 µm bands provides the most information. We plan to use a similar analysis to develop a number of severe weather products. Studies of this nature are important in preparation for the launch of GOES-R.