A Fuzzy Logic System for the Analysis and Prediction of Cloud Ceiling and Visibility

Low ceiling and poor visibility largely contribute to aviation safety and efficiency related problems. In an effort to provide accurate and timely diagnoses of these atmospheric conditions, a method is presented for the analysis and short-term forecast (0-6 hr) of cloud ceiling and visibility. Fuzzy logic is used to develop an integrated algorithm that combines in situ, satellite, climatology and numerical model data. The RUC (Rapid Update Cycle) and COAMPS (Coupled Ocean-Atmospheric Mesoscale Prediction System) models serve as the primary numerical models in the investigation, with model simulated, state of the atmosphere variables, being translated into cloud ceiling and visibility fields. Operationally, forecasters currently subjectively examine data to reach conclusions about the future state of ceiling and visibility, whereas the algorithm developed herein uses these data to objectively analyze and forecast ceiling and visibility by means of physically based parameters. Continued algorithm development focuses on implementing other data sources that may prove beneficial in reducing ceiling and visibility forecast errors.