the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Parameterizations for global thundercloud corona discharge distributions
Sergio Soler
Francisco J. Gordillo-Vázquez
Francisco J. Pérez-Invernón
Patrick Jöckel
Torsten Neubert
Olivier Chanrion
Victor Reglero
Nikolai Østgaard
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Our research explored changes in ozone levels in the northwest Pacific region over 30 years, revealing a significant increase in the middle-to-upper troposphere, especially during spring and summer. This rise is influenced by both stratospheric and tropospheric sources, which affect climate and air quality in East Asia. This work underscores the need for continued study to understand underlying mechanisms.
nudgeto the observed winds. Here we systematically evaluate how well this technique performs across a large suite of chemistry–climate models in terms of its ability to reproduce key aspects of both the tropospheric and stratospheric circulations.
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Climate models are crucial for predicting climate change in detail. This paper proposes a balanced approach to improving their accuracy by combining traditional process-based methods with modern artificial intelligence (AI) techniques while maximizing the resolution to allow for ensemble simulations. The authors propose using AI to learn from both observational and simulated data while incorporating existing physical knowledge to reduce data demands and improve climate prediction reliability.