Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 5
Articles | Volume 18, issue 5
https://doi.org/10.5194/gmd-18-1809-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-1809-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 5
Development and technical paper
 | 
17 Mar 2025
Development and technical paper |  | 17 Mar 2025

NeuralMie (v1.0): an aerosol optics emulator

Andrew Geiss and Po-Lun Ma

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Short summary
Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
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