In the last decades there have been many temporary engine failures, engine-related events and erroneous airspeed indication measurements that occurred by a phenomenon known as Ice Crystal Icing (ICI). This type of icing mainly occurs in high altitudes close to tropical convection in areas with a high concentration of ice crystals. Direct measurements or in-situ pilot observations of ICI that could be used as a warning to other air-traffic are rare to nearly non-existent. To detect those dangerous high Ice Water Content (IWC) areas with already existing airborne measurement instruments, Lufthansa analyzed observed Total Air Temperature (TAT) anomalies and used a self-developed search algorithm, depicting those TAT anomalies that are related to ice crystal icing events.
To optimize the flight route for dispatchers several hours before the flight, e.g. for long distance flights through the intertropical convergence zone (ITCZ), reliable forecasts to identify hazardous high IWC regions are necessary. For this purpose, detected TAT anomalies were used as training data to find correlations in between these and the DWD’s ICON (ICOsahedral Non-hydrostatic) model output. The combination of obtained frequency distributions of model cloud ice water content, base and top of moist convection and specific humidity by a fuzzy logic leads to a model-based prototype to forecast areas with high IWC in a simple manner. To show the high potential of the prototype’s procedure, an ICI event as observed during the CIRRUS-HL (Cirrus in High Latitudes) flight campaign in 2021 serves as good validation case. Here we show first promising, as it is still under development.