Development of New Icing Products for Supercooled Large Drop Conditions

Supercooled large drops (SLD) pose an enhanced threat to aviation safety compared to traditional small drop icing conditions due to their higher collision frequency, rougher texture, and ability to accumulate behind deicing boots. In recent years, the Federal Aviation Administration (FAA) has imposed new icing regulations under 14 CFR Appendix O to Part 25 to address hazards associated with SLD icing conditions, augmenting existing regulations regarding small drop icing conditions in Appendix C. Appendix O SLD conditions, defined as drops of at least 100 um in diameter, are further broken down into 4 subcategories based on the maximum drop size (Dmax) and the median volume diameter (MVD). These new regulations and associated environmental categories have necessitated research on how to provide operational drop size guidance to the aviation community.

The availability of more capable Numerical Weather Prediction (NWP) models along with improved observational networks facilitates development of icing weather tools with enhanced capability for classifying drop size. Specifically, the High Resolution Rapid Refresh (HRRR) model, running operationally at the National Center for Environmental Prediction, features the Thompson-Eidhammer bulk microphysics parameterization, which provides forecasts of mixing ratio and number concentration for both the cloud and rain hydrometeor categories. Using these predicted quantities, drop size information (i.e. Dmax and MVD) can be derived and used to advance operational icing tools, such as the Current Icing Product (CIP) and Forecast Icing Product (FIP).

This paper describes the approach used to distinguish small and large drop icing conditions and further categorize the SLD conditions based on drop size in support of Appendix O regulations. The HRRR-based drop size forecasts are compared to observations, primarily in situ aircraft measurements from research flights in Idaho, to evaluate the capability of the model to accurately distinguish small and large drop icing

* This research is in response to requirements and funding by the Federal Aviation Administration (FAA). The views expressed are those of the authors and do not necessarily represent the official policy or position of the FAA.