Developing improved products to forecast and diagnose aircraft icing conditions based upon drop size

Supercooled large drop (SLD) icing conditions are the focus of relatively new icing regulations under 14 CFR Appendix O to Part 25, which are defined based upon the maximum drop size. This definition poses a challenge to observational and modeling systems to be able to detect and/or predict the specific SLD icing conditions defined by Appendix O. Nonetheless, methods are being explored in order to meet these criteria and develop products useful for detecting and predicting SLD icing. Using case studies with in situ measurements confirming SLD icing conditions, dual-polarization radar products are evaluated to assess their performance at detecting SLD conditions. Additionally, a new method to infer the maximum drop size from numerical weather prediction models is evaluated. The results indicate that in some conditions the radar algorithms can provide useful indications of SLD conditions, while in situations where SLD conditions coexist with large ice crystals, the radar algorithm may need improvement. The performance of the forecasts of SLD icing conditions varied by forecast lead time, yet when the forecast accurately predicted SLD icing, the maximum drop size algorithm was able to correctly assign the appropriate Appendix O category of SLD icing conditions.