Aircraft icing is a major aviation safety hazard and has been linked to numerous aircraft accidents. In response, the Federal Aviation Administration (FAA) Aviation Weather Research program has sponsored research and development activities for the improvement of inflight icing detection and forecasting. As part of the research and development, the Research Applications Program at the National Center for Atmospheric Research (NCAR/RAP) has combined a number of different techniques into an Integrated Icing Diagnosis Algorithm (IIDA) that makes use of the strengths of individual algorithms while minimizing their weaknesses. The IIDA uses gridded data from the Rapid Update Cycle model; GOES-8 satellite imagery; NEXRAD mosaic; and National Weather Service surface observations to produce three- dimensional grids of Icing Potential, Supercooled Large Drop Potential, and Icing Type. In order to gain operational feedback for development purposes, the FAA William J. Hughes Technical Center conducted an assessment of the IIDA during the 1998 winter and spring season using operational forecasters at the National Centers for Environmental Prediction Aviation Weather Center. Forecasters utilized the IIDA in determining areas of hazardous aircraft icing. Results of the assessment identified what components of the IIDA were most useful, the added value of the IIDA over existing icing detection and forecast techniques, and measured the overall utility, reliability, and accuracy of the IIDA for aviation forecasting operations. In addition, assessment results provided insight into AWC forecaster operations that will be beneficial for the transition of future research products into operational use
The 8th Conference on Aviation, Range, and Aerospace Meteorology