On contrail prediction under realistic weather forecast uncertainty using the example of WAWFOR data

Contrail avoidance by operational means is often considered a quick and easy way to mitigate the climate impacts of aviation. However, several studies in the past assumed that the necessary weather forecasts were perfect. This is, of course, not true, and the question arises how imperfect weather forecasts impact contrail avoidance measures. Imperfections have several origins, but the most important one is the non-linear character of atmospheric dynamics, which renders forecasts of ice supersaturation as well as many other atmospheric features like rain and fronts difficult: In general, predicted features are not located where they are observed and they appear earlier or later than predicted. We demonstrate this for two versions of a weather forecast model (World Aviation Weather FORecast (WAWFOR), produced by the global numerical weather prediction model ICON, Icosahedral Nonhydrostatic) equipped with two kinds of ice cloud micro-physics, a one-moment and a two-moment scheme. The results are similar, which clearly shows that good treatment of microphysics is not a sufficient condition for successful contrail forecasts. For contrail avoidance, the imperfection leads to false alarms and misses which spoils the avoidance measures and diminishes the desired climate benefit. Whether the currently achievable benefit is sufficient is a question beyond the scope of the present study. But the situation can obviously be improved. To this end, it would be necessary to keep the forecast of ice supersaturation always close to measured reality. This implies the necessity of humidity measurements in the upper troposphere for data assimilation, which are currently rare. Potential data sources would be modern high-quality radiosondes and humidity measurements from passenger and cargo aircraft.