Exercising CIP Severity: An Investigation of Methodologies within the CIP Severity Algorithm

The Current Icing Product (CIP) provides an hourly diagnosis of the severity of icing occurring based on multiple data sources. Pilot reports (PIREPs) and surface observations (METARs), as well as satellite, numerical weather prediction (NWP) model, radar, and lightning data are all utilized within the algorithm. The accurate identification of cloud base is a large factor in the algorithm's determination of icing severity. Current methods employ the METAR observation of ceiling to identify the cloud base over a specified area within the CIP domain. The temperature from the Rapid Update Cycle (RUC) NWP model at the height of the observed METAR ceiling can be utilized as a proxy for the amount of condensate in the cloud. The likelihood of a large amount of condensate in the identified cloud increases with increasing cloud base temperature. As the amount of liquid water diagnosed by CIP severity increases, so does the estimated icing severity. The icing severity estimated by CIP severity will also increase in response to a deeper diagnosed cloud layer depth. This is a direct result of the assumption that a cloud contains more condensate the deeper into it one gets.

To verify these methodologies, PIREPs from an archived database will be analyzed and matched to a METAR observation, if that observation exists within a prescribed distance and time of the PIREP. Cloud base temperature and depth of the cloud layer will both be extracted from the CIP severity output for single layer cloud cases. Trends in cloud base temperatures (i.e. warmer vs. colder) and the cloud layer thickness (i.e. shallower vs. deeper) will be compared with PIREPs to identify any correlation between the cloud properties and observed icing intensity.