Remote sensing observations of winter aircraft icing conditions - A case study

Abstract

This article describes how various combinations and arrays of remote sensors can be used to successfully predict aircraft icing conditions aloft. A case study, validated by pilot reports, is developed to illustrate the use of remote sensor data to predict aircraft icing conditions as well as verify icing forecasts. Surface-based remote sensing instruments and conventional instruments were used to study aircraft icing conditions during the winter storm of January 24-25, 1989, in the Denver, Colorado area. A unique combination of arrays of remote sensors was used to determine spatial and temporal distribution of supercooled liquid water. The remote sensors used were profiling radars, radio-acoustic sounding systems, multichannel microwave radiometers, and lidar ceilometers. Measurements used to predict aircraft icing conditions aloft included cloud liquid water, temperature profiles with high vertical (—150 m) and temporal (—15 min) resolutions, and the heights of cloud base, as well as estimates of cloud-top height with a temporal resolution of 15 min. Arrays of remote sensing instruments are shown to enhance detection and prediction of aircraft icing. Present and future remote sensing capabilities for detecting aircraft icing events are described. This icing case study is unique in combining arrays of remote sensors of various types to define the spatial and temporal distributions of supercooled liquid water, and in making comparisons with pilot reports as a means of verification.