Articles | Volume 13, issue 6
Geosci. Model Dev., 13, 2569–2585, 2020
https://doi.org/10.5194/gmd-13-2569-2020
Geosci. Model Dev., 13, 2569–2585, 2020
https://doi.org/10.5194/gmd-13-2569-2020

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 et al.

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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Sam Silva on behalf of the Authors (15 Apr 2020)  Author's response    Manuscript
ED: Publish as is (17 Apr 2020) by Christoph Knote
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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.