Air Quality Research Center, University of California, Davis,
CA 95616, USA
Institute of Mathematics, Technical University of Berlin, 10587 Berlin,
Germany
Anthony S. Wexler
Air Quality Research Center, University of California, Davis,
CA 95616, USA
Departments of Mechanical and Aerospace Engineering, Civil and
Environmental Engineering, and Land, Air and Water Resources, University of
California, Davis, CA 95616, USA
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Large air quality and climate models calculate different physical and chemical phenomena in separate operators within the overall model, some of which are computationally intensive. Machine learning tools can memorize the behavior of these operators and replace them, but the replacements must still obey physical laws, like conservation principles. This work derives a mathematical framework for machine learning replacements that conserves properties, such as mass or energy, to machine precision.
Large air quality and climate models calculate different physical and chemical phenomena in...