GOES-R ABI and Himawari-8 AHI Training using SIFT

The Satellite Information Familiarization Tool (SIFT) is a python-based visualization application with a Graphical User Interface designed to enhance training of modern geostationary satellite data. It reaffirms understanding of core principles in radiation science, allows forecasters to develop familiarity with Himawari-8's spatial, spectral, and temporal resolution and increases the forecaster's ability to use certain bands of satellite imagery to solve short-term weather analysis and forecast challenges. The software allows seamless transitions between bands to demonstrate how the Earth/Atmosphere system is observed at different wavelengths. Multi-band probing and Density Diagrams allow for quick interchannel comparisons. SIFT has been used for Day-1 Himawari-8 training at the National Weather Service Forecast Offices in Guam and Honolulu. SIFT training combined with training on Weighting Functions and RGBs leads to a more thorough understanding of how satellite observations can be interpreted and used in the forecast process.