Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 11
Articles | Volume 18, issue 11
https://doi.org/10.5194/gmd-18-3509-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-3509-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 11
Development and technical paper
 | 
13 Jun 2025
Development and technical paper |  | 13 Jun 2025

DustNet (v1): skilful neural network predictions of dust aerosols over the Saharan desert

Trish E. Nowak, Andy T. Augousti, Benno I. Simmons, and Stefan Siegert

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Short summary
The DustNet model uses deep neural networks to accurately predict Saharan mineral dust transport in the atmosphere. It offers fast and precise forecasts with predictions achieved in just 2.1 s on a standard computer. This innovative approach outperforms traditional models, which take hours to produce a forecast and use high-energy supercomputers. By making high-quality dust monitoring accessible and efficient, DustNet can improve weather, climate, and air quality forecasts.
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