On the fidelity of high-resolution numerical weather forecasts of contrail-favorable conditions.

The potential climate-warming impact from aircraft contrails may be similar in magnitude to the direct effect from carbon dioxide emissions across all aviation. The warming impact may be mitigated through pre-tactical flight trajectory optimization to avoid ice supersaturation regions (ISSRs) while also considering aircraft performance and CO 2 emissions. The ability to perform such deviations depends on accurate predictions of water vapor in the upper troposphere and lower stratosphere (UTLS). Herein we evaluated the performance of two leading global numerical weather prediction (NWP) models: the Global Forecast System (GFS) developed in the USA and the Integrated Forecast System, (IFS) developed in Europe, and a research mesoscale model, Weather Research and Forecasting configured by SATAVIA (S-WRF) to predict UTLS moisture and ISSR. We compared humidity forecasts to observations from 383 aircraft flights and 3480 radiosonde profiles comprising approximately 1.5 million measurements over Europe and the Middle East for 10 months in 2022. Neither GFS nor IFS properly reproduced the observed distribution of relative humidity with respect to ice (RH ice). Moreover, in addition to not being usable for prospective flight planning, the ERA5 reanalysis only slightly improved the outcome of the IFS. Only the S-WRF model with multi-moment cloud physics and high spatial resolution (5 km grid spacing) closely reproduced the observed relative frequency distribution of RH ice. Furthermore, ISSR validation using near equal-area neighborhoods when computing Matthews Correlation Coefficient and F1 score showed that S-WRF scored higher (F1 = 0.66) than the IFS (F1 = 0.62), while the GFS had near zero score due to its near complete lack of predictions of RH ice greater than 100 % in stark contrast to observations. In fact, S-WRF also correctly predicts 92 % of the time when conditions were not conducive to contrail formation. Ultimately, the S-WRF model could be used to alter flight plans to deviate above or below nearly certain contrail formation regions to reduce non-CO 2 climate impacts of aviation. • Statistical analysis of upper-tropospheric, lower-stratospheric moisture predictions. • Skill of forecasts of relative humidity with respect to ice. • Numerical weather prediction of ice supersaturation and contrail formation regions. • Applicability of numerical weather prediction of contrails to re-route aircraft in order to prevent contrails. • Reducing non carbon dioxide impacts of aviation by contrail management. [ABSTRACT FROM AUTHOR]