Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 13, issue 6
Articles | Volume 13, issue 6
https://doi.org/10.5194/gmd-13-2569-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-2569-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 13, issue 6
Development and technical paper
 | 
03 Jun 2020
Development and technical paper |  | 03 Jun 2020

Development of a reduced-complexity plant canopy physics surrogate model for use in chemical transport models: a case study with GEOS-Chem v12.3.0

Sam J. Silva, Colette L. Heald, and Alex B. Guenther

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Latest update: 13 Dec 2024
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Short summary
Simulating the influence of the biosphere on atmospheric chemistry has traditionally been computationally intensive. We describe a surrogate canopy physics model parameterized using a statistical learning technique and specifically designed for use in large-scale chemical transport models. Our surrogate model reproduces a more detailed model to within 10 % without a large computational demand, improving the process representation of biosphere–atmosphere exchange.
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