A decision support model to assess the braking performance on snow and ice contaminated runways

Abstract

Pilots need accurate predictions on the quality of runway surface conditions when operating on snow/ice contaminated runways. These predictions are typically made by friction measurements, or by expert judgments of runway inspectors. This study presents a decision support model (the IRIS runway model) for runway inspectors that interprets descriptive data from SNOWTAM reports and predicts the braking action on the common scale from 1 to 5, ranging from “poor” to “good”. The model is tested on two airports in Norway during the winter seasons 2008/2009 to 2010/2011. Two other predictors of the braking action (assessments by runway inspectors and friction measurements) were also included. Analyses of 1261 friction-limited landings of commercial airplanes were used to compare predicted and measured braking actions.The IRIS runway model was found to be more conservative than the assessments of Norwegian runway inspectors, and even more conservative than friction measurements. In 86% of the landings, the IRIS runway model predicted the conditions within ±1 category of what the airplanes experienced, compared to 77% achieved by the runway inspectors. The predictions by the friction measurement devices were the least conservative and predicted the conditions within ±1 category in 61% of the landings. The model is now implemented in 15 airports in Norway.