Icing severity forecast algorithm under both subjective and objective parameters uncertainties

Abstract Based on the traditional deterministic methods for estimating the airplane icing severity, a probabilistic method under considering subjective and objective parameters uncertainties is proposed. In that method, all meteorological observation data are described as random variables, then Monte Carlo method is performed to forecast the probability of airplane icing. In the process of forecasting the airplane icing severity level, the membership function is introduced to describe the subjective uncertainty. Finally, the generalized probabilistic solution formula of estimating the airplane icing severity level is derived. The proposed probabilistic model and solutions for forecasting the airplane icing severity level are proved to be reasonable and applicable by a real airplane icing case.