The ice supersaturation biases limiting contrail modelling are structured around extratropical depressions

Driver, Oliver G. A.; Stettler, Marc E. J.; Gryspeerdt, Edward

doi:10.5194/acp-25-16411-2025

Articles | Volume 25, issue 22

https://doi.org/10.5194/acp-25-16411-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-25-16411-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 22

Research article

|

21 Nov 2025

Research article |

| 21 Nov 2025

The ice supersaturation biases limiting contrail modelling are structured around extratropical depressions

Oliver G. A. Driver, Marc E. J. Stettler, and Edward Gryspeerdt

Data sets

IAGOS final quality controlled Observational Data L2 - Time series D. Boulanger et al. https://doi.org/10.25326/06

Model code and software

pycontrails: Python library for modeling aviation climate impacts M. Shapiro et al. https://doi.org/10.5281/zenodo.10182539

ogad/compositrails_public: Compositrail: Analysis Code O. G. A. Driver https://doi.org/10.5281/zenodo.17643614

Short summary

Contrails are ice clouds caused by planes. They have a warming effect, so are important to model. In humid (ice supersaturated) regions, ice crystals are stable so can persist. However, weather model data doesn't represent ice supersaturated regions well enough. We demonstrate that ice supersaturation modelling is structured by North Atlantic storm systems. Averaging many systems, we link the bias to underling processes being modelled, and gain insight into how the existing data could be used.