Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 25, issue 5
Articles | Volume 25, issue 5
https://doi.org/10.5194/acp-25-2845-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-2845-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 5
Research article
 | 
07 Mar 2025
Research article |  | 07 Mar 2025

Machine learning for improvement of upper-tropospheric relative humidity in ERA5 weather model data

Ziming Wang, Luca Bugliaro, Klaus Gierens, Michaela I. Hegglin, Susanne Rohs, Andreas Petzold, Stefan Kaufmann, and Christiane Voigt

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Short summary
Upper-tropospheric relative humidity bias in the ERA5 weather model is corrected by 10 % by an artificial neural network using aircraft in-service humidity data and thermodynamic and dynamical variables. The improved skills of the weather model will advance cirrus research, weather forecasts, and measures for contrail reduction.
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