Articles | Volume 13, issue 6
Geosci. Model Dev., 13, 2569–2585, 2020
Geosci. Model Dev., 13, 2569–2585, 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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Cited articles

Ashworth, K., Chung, S. H., Griffin, R. J., Chen, J., Forkel, R., Bryan, A. M., and Steiner, A. L.: FORest Canopy Atmosphere Transfer (FORCAsT) 1.0: a 1-D model of biosphere–atmosphere chemical exchange, Geosci. Model Dev., 8, 3765–3784,, 2015. 
Ashworth, K., Chung, S. H., McKinney, K. A., Liu, Y., Munger, J. W., Martin, S. T., and Steiner, A. L.: Modelling bidirectional fluxes of methanol and acetaldehyde with the FORCAsT canopy exchange model, Atmos. Chem. Phys., 16, 15461–15484,, 2016. 
Baldocchi, D. D., Hicks, B. B., and Camara, P.: A canopy stomatal resistance model for gaseous deposition to vegetated surfaces, Atmos. Environ., 21, 91–101,, 1987. 
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q., Liu, H. Y., Mickley, L. J., and Schultz, M. G.: Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, J. Geophys. Res., 106, 23073–23095,, 2001. 
Chen W. H., Guenther A. B., Wang X. M., Chen Y. H., Gu D. S., Chang M., Zhou S. Z., Wu L. L., and Zhang Y. Q.: Regional to Global Biogenic Isoprene Emission Responses to Changes in Vegetation From 2000 to 2015, J. Geophys. Res.-Atmos., 123, 3757–3771,, 2018. 
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.