An Online‐Learned Neural Network Chemical Solver for Stable Long‐Term Global Simulations of Atmospheric Chemistry
Abstract A major computational barrier in global modeling of atmospheric chemistry is the numerical integration of the coupled kinetic equations describing the chemical mechanism. Machine‐learned (ML) solvers can offer order of magnitude speedup relative to conventional implicit solvers but past imp...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2022-06-01
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| Series: | Journal of Advances in Modeling Earth Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2021MS002926 |