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

Friday, 19 August 2016: 8:45 AM
Madison Ballroom CD (Monona Terrace Community and Convention Center)
Ray K. Garcia, Univ. of Wisconsin-Madison, Madison, WI; and D. Hoese, J. J. Gerth, S. S. Lindstrom, K. I. Strabala, T. J. Schmit, and B. Ward

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.
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