A prediction method for aircraft icing severity forecast based on probability model and meteorological observation data

Abstract

Abstract Aircraft flight performance and safety are inevitably affected by adverse meteorological conditions, one such weather is icing. Aircraft icing can cause severe aerodynamic and flight mechanical effects, thus threatens aircraft flight safety. This study presents an aircraft icing severity prediction method with probabilistic model, in which meteorological observation data are described as random variables and the airplane icing severity level is defined as fuzzy variables with membership function. When the information of aircraft flying cloud type, altitude, speed, temperature, pressure and dew point temperature is known, the probability of aircraft icing severity during aircraft fly can be effectively predicted by a weighted icing forecasting method. Using the proposed method into two aircraft icing cases, the analysis results show that the proposed method is accurate and valid. It can provide technical support for aircraft icing forecasting.