The Relationship between Regional Icing Distribution and Environmental Conditions

Pilot reports (PIREPs) are used to describe current flight conditions. This information provides details on the actual weather environment in which an aircraft is flying. Data provided in the report includes location, altitude, aircraft type, sky cover conditions, turbulence, ambient temperature, and any known icing the aircraft has encountered. These reports are made available to aviation weather forecasters who are then able to relay and use this information to better understand current atmospheric conditions that exist in real time.

The Current Icing Product (CIP) is an algorithm that produces icing severity output over the continental United States and southern Canada. This algorithm uses a combination of numerical weather prediction models, satellite, radar, surface and pilot observations, and lightning to help determine where icing and supercooled large drops (SLD) are occurring on a three-dimensional grid. One of CIP's many abilities is to provide necessary information for detecting icing environments that exist in the atmosphere. Once icing is determined to exist at a certain location, observations and vertical profiles of the model are used to help decide which of eight icing scenarios is probable at that location. These scenarios include no precipitation, below the warm nose, above the warm nose, all snow, cold rain, warm precipitation, cold non snow/rain, and convection.

This study examines the distribution of icing PIREPs regionally by CIP scenario and season and will provide information regarding which weather scenarios produce the most amount of icing and the intensity associated with each scenario. This will allow the CIP developers to determine what scenarios are most common in each region and season and if any of the scenarios are representative of the expected icing conditions. This information will also be valuable as the CIP transitions to a more regionally driven icing diagnosis system and will allow the developers to tune the algorithm to produce the best answer for each region.