The goals of this project including collaborating with NOAA-NESDIS and UW-CIMSS scientists to support the development of an Algorithm Theoretical Basis Document (ATBD) for imagery and visualization applications using the GOES-R Advanced Baseline Imager (ABI). The focus of work will be on the usage of Red/Green/Blue (RGB) color composite imagery techniques applied to multispectral ABI data as a way of highlighting specific features of the potentially complex meteorological scene. These ‘value-added’ imagery techniques, which can be regarded as qualitative representations of environmental information based on the same physical principles used to retrieve quantitative information, have proven extremely effective in providing forecasters with quick-look depictions of the specific information required for rapid scene characterization and short-term forecasting (nowcasting) guidance. An inherent advantage of these imagery techniques is that the enhanced component of the image is retained within the context of the meteorology, topography, etc., allowing for users to understand how the features of interest fit (and potentially interact) within the bigger picture.
ABI RGB (true-color) images compared to MODIS true-color images. The top row contains a simulated ABI image (upper-left) using MODIS 16-day albedos and forward-model calculations, and an actual MODIS image (upper-right) of the same area. The bottom row contains RGB (true-color) images for both ABI (lower-left) and MODIS (lower-right) where the Green band is first created from the Red, Near-IR, and Blue bands.