Towards the detection of aircraft icing conditions using operational dual-polarimetric radar
June 25, 2012
7th European Conf. on Radar in Meteorology and Hydrology, ERAD, 25-29 June 2012.
In anticipation of the dual-polarimetric upgrade to the National Weather Service operational radar network (WSR-88D) research is being conducted to utilize this extensive new data source for remote aircraft icing detection. The first challenge is to accurately locate the melting layer. A new image-processing-based algorithm is proposed and demonstrated. The next challenge is to use the dual-polarimetric data above the melting level to distinguish regions containing super-cooled liquid water, which constitutes an aviation icing hazard, from regions of pure ice and snow. It has been well documented that the S-band dual-polarimetric radar signatures at individual range gates of super-cooled liquid water and ice crystals overlap significantly, complicating the identification of icing conditions using individual radar measurements. Recently several investigators have found that the aggregate characteristics of dual-polarimetric radar measurements over regions on the order of several kilometers show distinguishing features between regions containing super-cooled liquid and those with ice only. In this study, the features found in the literature are evaluated, extended and combined using a fuzzy-logic framework to provide an icing threat likelihood. The results of this new algorithm are computed using data collected in Colorado from the Colorado State University CHILL radar and the National Center for Atmospheric Research S-Pol radar (collectively called FRONT – The Front Range Observational Testbed) collected in the winter of 2010/2011 in coordination with the NASA Icing Remote Sensing System (NIRSS) and compared to pilot reports on approach or departure from nearby airports. The preliminary results look encouraging and will be presented. The ultimate goal is to produce an end-to-end algorithm to produce a reliable icing threat product that can then be combined with existing icing detection systems to improve their performance.