Impact of Forecast Stability on Navigational Contrail Avoidance

TL;DR

This study evaluates the stability of upper troposphere and lower stratosphere forecasts for contrail avoidance, demonstrating that despite some errors, forecast stability is sufficient for effective pre-tactical flight rerouting to significantly reduce climate impact.

Contribution

It systematically quantifies forecast stability's impact on contrail avoidance effectiveness, showing that current forecast errors still enable substantial climate benefits.

Findings

Contrail forecast errors are spatially small but pointwise inconsistent.

Trajectory optimization can reduce contrail climate forcing by 80-90%.

Forecasts with 8-24 hour lead times are sufficiently stable for practical use.

Abstract

MMitigating contrail-induced warming by re-routing flights around contrail-forming regions requires accurate and stable forecasts of the state of the upper troposphere and lower stratosphere. Forecast stability (i.e., consistency between forecast cycles with different lead times) is particularly important for "pre-tactical" contrail avoidance strategies that adjust routes based on forecasts with lead times as long as 24-48 hours. However, no study to date has systematically quantified the degree to which forecast stability limits the effectiveness of pre-tactical avoidance. This study addresses this gap by comparing contrail forecasts generated using ECMWF HRES weather forecasts with lead times up to 48 hours to contrail hindcasts generated based on ECMWF ERA5 reanalysis. An analysis of forecast errors show low pointwise consistency between persistent-contrail-forming regions in forecasts and reanalysis, with pointwise error rates similar to those found in previous comparisons of contrail-forming regions in reanalysis and reality. However, we also show that spatial errors in the locations of contrail-forming regions are relatively small, both when forecasts are compared to reanalysis and when reanalysis is compared to in-situ measurements. Finally, we show that designing a trajectory optimizer to take advantage of relatively small spatial errors allows flight trajectory optimizations based on contrail forecasts to reduce contrail climate forcing evaluated based on reanalysis by 80-90% at the 8-24 hour lead times most relevant to flight planning, with fuel penalties under 0.4%. Our results show that forecasts with lead times relevant to flight planning are stable enough to be used for pre-tactical contrail avoidance.