Examining Contrail Formation Models with Open Flight and Remote Sensing Data

One of the biggest challenges facing the aerospace industry today is its sustainability. As the number of flights is expected to rise globally, aviation’s climate impact will continue to increase. Current research has extensively addressed the rerouting of aircraft through wind-optimization in order to minimize fuel burn and emissions. Such optimization is currently implemented for flight planning. Although this strategy is optimized for fuel burn and emissions, it does not necessarily minimize the overall climate impact. Navigating optimally through wind fields could mean flying through regions with a higher climate impact, where warming contrails are formed. This can occur when contrails trap outgoing terrestrial radiation and so contribute to global warming. This warming contrail creation could potentially forfeit the climate gain of the reduced emissions from the wind-optimized route. In order to implement such a climate-optimized routing model, knowledge about the atmospheric conditions under which contrails form is required. One existing theorem is the Schmidt-Appleman Criterion, which uses the air temperature, relative humidity and ambient air pressure to determine whether contrail formation is possible. In addition, the ice-supersaturation criterion model indicates contrail persistence. In this paper, multiple open data sources are used to examine the use of this established criterion, to evaluate the appropriateness of these data sources for future use in a climate-optimized routing model. Based on the obtained results, we show that, with these data sources, the combination of Schmidt-Appleman and the ice-supersaturation criterion can produce a more reliable determination of contrail formation. The results can be used for an improved unified and data-driven model for the purposes of climate-optimized routing.