Verification of aviation icing algorithms from the Second Alliance Icing Research Study

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Wednesday, 1 February 2006: 11:15 AM
Verification of aviation icing algorithms from the Second Alliance Icing Research Study
A301 (Georgia World Congress Center)
Michael B. Chapman, NCAR, Boulder, CO; and A. Holmes and C. A. Wolff

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The Second Alliance Icing Research Study (AIRS II) was conducted over Southeastern Canada from November 2003 to February 2004. One of the main objectives of this field project was to develop systems to diagnose and forecast in-flight icing conditions over short time periods (0 12h). Several operational in-flight icing algorithms were available during this time period for evaluation. These algorithms include Current Icing Potential (CIP), Forecast Icing Potential (FIP), System of Icing Geographic identification in Meteorology for Aviation (SIGMA), the Goes-derived Cloud Products (GDCP), the Global Environmental Multi-scale (GEM) model and the Penn State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model (MM5). This study presents an evaluation of the forecasting capabilities of these algorithms. CIP is a diagnostic in-flight icing algorithm which generates an icing potential product by combining satellite, radar, surface, lightning and pilot reports (PIREPs) with fields from the 20-km Rapid Update Cycle (RUC). FIP is a short-term forecasting algorithm which uses fields from the 20-km RUC to generate forecasts of icing potential out to 12 hours. Both CIP and FIP were developed at NCAR. SIGMA is a diagnostic in-flight icing algorithm developed by MeteoFrance which utilizes satellite, radar, and fields from a numerical model (RUC for this specific study) to generate an icing potential product. The GDCP is generated by NASA Langley Research Center (LaRC) with the algorithm determining cloud characteristics such as cloud phase, liquid water or ice path, optical depth, effective temperature, effective particle size, and effective height. The GEM is an operational meso-scale model produced at the Canadian Meteorological Centre (CMC). The MM5 also is a meso-scale model, developed in the United States by Penn State University and NCAR. For verification of the algorithms, several research aircraft datasets are available from the AIRS II project. The three data sets that are utilized to provide icing observations are from the NASA Glenn Twin Otter, the University of North Dakota Citation, and the National Research Council Convair-580. All of these aircraft were equipped with standard cloud microphysical probes. In addition, pilot reports (PIREPs) of icing were available over the CONUS during the AIRS II period. This study includes an evaluation of both the diagnostic and forecast algorithms/models using the AIRS II research aircraft data. A secondary evaluation is presented for the CONUS for the November 2003 to February 2004 time period, with the analyses based on icing PIREPs. CIP, FIP, SIGMA, MM5, GEM and the NASA LaRC GDCP are included in this evaluation, and their performance characteristics are compared.