Data-driven emulation of modal aerosol microphysics via neural operator-based modeling
Abstract
This repository provides inference model, codes, and instructions for a surrogate ML model - the aerosol deep operator network (ADON), a physics-inspired dual-net architecture for emulating the aerosol microphysics parameterization suite in the version 2 of the Energy Earth System Model (E3SMv2).
Fields of Study & Subjects
Model Reduction and Neural Networks
Atmospheric aerosols and clouds
Meteorological Phenomena and Simulations
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 13 January 2026