Extended Abstract (312K)3.2
The forecast icing potential (FIP) algorithm
Frank McDonough, NCAR, Boulder, CO; and B. C. Bernstein, M. K. Politovich, and C. A. Wolff
The Forecast Icing Potential (FIP) was developed at the National Center for Atmospheric Research by members of the FAA's Inflight Icing Product Development Team. It uses National Center for Environmental Prediction (NCEP) Rapid Update Cycle (RUC) model output to determine the potential for inflight icing conditions. FIP output is created every 3 h and gives 3, 6, 9, and 12-h forecasts over the CONUS from the surface to 30,000 ft MSL.
FIP's predecessor, CIP (Current Icing Potential), combines model output with observations to diagnose current icing conditions. Data from satellites, radar, METARs and PIREPs are first used to determine the locations of clouds and precipitation, then to assess the potential for icing conditions throughout the cloudy portion of the model domain. Since observations are not available for future times, the FIP uses model output surrogates to estimate cloud top temperature, precipitation type and other icing-relevant parameters. The remainder of the algorithm mimics the CIP approach to the diagnosis of icing potential.
FIP uses the model relative humidity to determine whether or not a column contains a cloudy layer and to extract information about the cloud such as base and top height and the number of layers. The cloud information is combined with temperature to yield information on the cloud temperature range. After determining the locations of clouds and precipitation, FIP combines temperature, cloud top temperature, relative humidity, vertical velocity, supercooled liquid water, and QPF information to determine the potential for icing conditions. All of the above data are combined in a physically-based, situational, fuzzy logic system using interest maps that represent the relevance of each parameter to inflight icing. The membership functions for the interest maps vary based on the meteorological situation identified for each model vertical column (e.g., single-layer non-precipitating clouds, convective clouds, etc.) In this way, FIP acts like a human forecaster, applying model output in the best way depending on the situation to forecast icing potential. The membership functions are based on forecasting experience, in-situ data sets from research aircraft, and are consistent with a large dataset of voice pilot reports.
FIP produces accurate forecasts based on case studies and verification using pilot reports and performs similarly to CIP.
Session 3, Advances and Applications in Transportation Weather (ROOM 613/614)
Monday, 12 January 2004, 10:45 AM-12:00 PM, Room 613/614
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