Flying around storms: Structured supersaturation at weather systems

The relative humidity to ice water is crucial to determining whether or not ice crystals in contrails are able to persist. Inaccurate weather model data for this key meteorological input to contrail models is widely appreciated to be the limiting factor in current contrail models to produce accurate contrail persistence statistics. Identifying biases and constraining the inaccuracies in this weather data is needed to enable analysis of contrail models without this as a confounding factor.

Extratropical low pressure systems (storms) in the North Atlantic structure the weather in this region. These storms have a well-understood structure.  Averaging composites of many storm systems is a frequently used method to observe features in both weather model output and observations. We show that a similar method can be used to identify the structures in the contrail-sustaining ice-supersaturated regions, and the regions of flight traffic through them. In-situ humidity observations give an understanding of the accuracy of the meteorological data. Humid features are seen where models are subject to saturation adjustment but can be constrained to an accurate understanding of ice-supersaturation. Conversely, downwelling air—which is typically dry—is not as well constrained when humidity does occur. This work identifies opportunities to begin exploring contrail model validation, but also acts to steer development of more accurate weather models.