Articles | Volume 13, issue 6
https://doi.org/10.5194/gmd-13-2569-2020
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, Colette L. Heald, and Alex B. Guenther

Viewed

Total article views: 5,567 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
4,703 805 59 5,567 54 61
  • HTML: 4,703
  • PDF: 805
  • XML: 59
  • Total: 5,567
  • BibTeX: 54
  • EndNote: 61
Views and downloads (calculated since 28 Jan 2020)
Cumulative views and downloads (calculated since 28 Jan 2020)

Viewed (geographical distribution)

Total article views: 5,567 (including HTML, PDF, and XML) Thereof 4,619 with geography defined and 948 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Nov 2024
Download
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.