EGU24-18251, updated on 11 Mar 2024
https://doi.org/10.5194/egusphere-egu24-18251
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

On the fidelity of numerical weather prediction model forecasts to identify ice supersaturated regions for aircraft contrail management

Adam Durant1,2, Greg Thompson1,3, Chloé Sholzen1, Scott O’Donoghue1, Max Haughton1, Rod Jones1,4, and Conor Farrington1
Adam Durant et al.
  • 1SATAVIA Ltd., Park House, Castle Park, Cambridge, CB3 0DU, United Kingdom
  • 2Geological and Mining Engineering and Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI49931, USA
  • 3Joint Center For Satellite Data Assimilation, University Corporation for Atmospheric Research, Boulder, CO 80307, USA
  • 4Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, United Kingdom

The potential atmospheric warming and impact on climate by aircraft contrails may be similar in magnitude to the direct effect from carbon dioxide emissions across all aviation.  Contrail management via optimized flight planning considering aircraft performance and CO2 emissions, and the presence of ice supersaturated regions (ISSR), could mitigate any potential climate impacts.  The success of aircraft deviations depends on accurate predictions of the water vapor in the upper troposphere and lower stratosphere (UTLS). 

To evaluate the performance of two global numerical weather prediction (NWP) models (the US Global Forecast System, GFS; and the European Integrated Forecast System, IFS), one reanalysis model (the European fifth generation ECMWF atmospheric reanalysis, ERA5), and one research-grade mesoscale model to predict UTLS moisture and ISSR, we compared humidity forecasts to observations from 383 aircraft flights and radiosondes from 168 launch times over Europe and the Middle East for 10 months in 2022.

The research model mirrored observed distributions of relative humidity with respect to ice (RHice)  at all locations above 25,000 ft AMSL, while GFS and IFS forecasts poorly reproduced the observed distribution, and ERA 5 reanalysis only slightly improved on the skill of the IFS. Furthermore, ISSR validation was performed using near equal-area neighbourhoods to compute the Matthew Correlation Coefficient and F1-score and demonstrated a higher model score (F1=0.66) than IFS (F1=0.62), while the GFS score is close to zero (F1≈0) due to an absence of predictions of RHice greater than 100% in stark contrast to observations.  Importantly, the research model also correctly predicts RHice<100% in 92% of model-observation comparisons, identifying where atmospheric conditions are not conducive to persistent contrail formation. 

In summary, NWP model skill is adequate, when configured for the use case, to identify both ISSR and dry atmosphere locations and ensure a mitigation of the atmospheric warming caused by aircraft contrails through aircraft routing to reduce non-CO2 climate impact of aviation.

How to cite: Durant, A., Thompson, G., Sholzen, C., O’Donoghue, S., Haughton, M., Jones, R., and Farrington, C.: On the fidelity of numerical weather prediction model forecasts to identify ice supersaturated regions for aircraft contrail management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18251, https://doi.org/10.5194/egusphere-egu24-18251, 2024.