Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 21
Articles | Volume 19, issue 21
https://doi.org/10.5194/gmd-19-10763-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-10763-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 21
Model description paper
 | 
12 Nov 2026
Model description paper |  | 12 Nov 2026

aiLand v1: physics-based land surface emulator with observational fine-tuning

Nina Raoult, Ewan Pinnington, Mario Santa Cruz, Florian Pinault, Baudouin Raoult, Natalie Zelenka, Gabriele Arduini, Gianpaolo Balsamo, Souhail Boussetta, Matthew Chantry, Patricia de Rosnay, Peter Dueben, and Christoph Rüdiger

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Short summary
The land surface shapes our weather and climate by controlling how heat and water move between the ground and the air, so the models representing it matter enormously. But they are costly to run and carry built-in errors. We built a faster artificial-intelligence version of one, then used real measurements from sites worldwide to correct some of these errors. The result stays reliable over years and better captures these heat and water exchanges; a quicker, more accurate tool for forecasting.
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