Statistical-empirical forecasting guidance for the occurrence of fog at Mount Gambier Airport

Abstract

A statistical-empirical decision aid for forecasting morning fogs at Mount Gambier Airport based on pre-dawn data is presented. Of main concern are those fog events significantly impacting on aviation operations, although the model is applicable to other fog events of lesser impact. The aid is restricted to precipitation-absent fogs. The probability of fog occurrence was modelled on a ten-year dependent dataset using the logistic equation. By converting probabilistic forecasts to categorical forecasts of fog events, skill scores of Probability of Detection, False Alarm Rate and Critical Success Index were determined based upon three years of independent data. For operationally significant fogs, the Probability of Detection, False Alarm Rate and Critical Success Index were 73%, 23% and 60% respectively on the independent data. These scores were very similar to those obtained from the dependent dataset of ten years. When fog events were defined less stringently as either fogs per se or shallow fogs, the respective skill scores on the independent data were 84%, 20% and 70%; again with similar scores on the dependent data.