Preprints
https://doi.org/10.5194/egusphere-2023-1167
https://doi.org/10.5194/egusphere-2023-1167
19 Jul 2023
 | 19 Jul 2023

Optimizing maximum carboxylation rate for North America’s boreal forests in the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) v.1.3

Bo Qu, Alexandre Roy, Joe R. Melton, Jennifer L. Baltzer, Youngryel Ryu, Matteo Detto, and Oliver Sonnentag

Abstract. The maximum carboxylation rate (Vcmax) is an important parameter for the coupled simulation of gross primary production (GPP) and evapotranspiration (ET) in terrestrial biosphere models (TBMs) such as the Canadian Land Surface Scheme Including biogeochemical Cycles (CLASSIC). Observations of Vcmax show it to vary both spatially and temporally, but it is often prescribed as constant in time and space for plant functional types (PFTs) in TBMs, which introduces large errors over North America’s boreal biome. To reduce this uncertainty, we used a Bayesian algorithm to optimize Vcmax25 (Vcmax at 25 °C) in CLASSIC against eddy covariance observations at eight mature boreal forest stands in North America for six representative PFTs (two trees, two shrubs, and two herbs). As expected, the simulated GPP and ET using the optimized parameters generally obtained reduced root mean square deviation values compared with eddy covariance observations and corresponding stand-level estimates obtained from gridded global data products. The optimized Vcmax25 values for each PFT compared reasonably well with reported estimates derived from leaf-level gas exchange measurements. However, a large spatial variability of Vcmax25 was identified, especially for the shrub and herb PFTs. We found that the site characteristics, particularly latitude for the shrub PFTs and air temperature for evergreen needleleaf tree, explained much of the spatial variability, providing a basis to improve Vcmax25 parameterizations in TBMs at regional scales.

Bo Qu, Alexandre Roy, Joe R. Melton, Jennifer L. Baltzer, Youngryel Ryu, Matteo Detto, and Oliver Sonnentag

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1167', Anonymous Referee #1, 22 Sep 2023
  • RC2: 'Comment on egusphere-2023-1167', Anonymous Referee #2, 06 Oct 2023
  • AC1: 'Author responses to anonymous referees #1 and #2', Bo Qu, 01 Feb 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1167', Anonymous Referee #1, 22 Sep 2023
  • RC2: 'Comment on egusphere-2023-1167', Anonymous Referee #2, 06 Oct 2023
  • AC1: 'Author responses to anonymous referees #1 and #2', Bo Qu, 01 Feb 2024
Bo Qu, Alexandre Roy, Joe R. Melton, Jennifer L. Baltzer, Youngryel Ryu, Matteo Detto, and Oliver Sonnentag

Data sets

A boreal forest model benchmarking dataset for North America: a case study with the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC) Bo Qu, Oliver Sonnentag, Alexandre Roy, Joe R. Melton, T. Andrew Black, Brian Amiro, Eugénie S. Euskirchen, Masahito Ueyama, Hideki Kobayashi, Christopher Schulze, Gabriel Hould Gosselin, and Alex J. Cannon https://doi.org/10.5281/zenodo.7266010

Model code and software

PFT-Vcmax25 optimization in CLASSIC (v.1.3) Bo Qu, Roy, Alexandre Roy, Joe R. Melton, Jennifer L. Baltzer, Youngryel Ryu, Matteo Detto, and Oliver Sonnentag https://doi.org/10.5281/zenodo.8136578

Bo Qu, Alexandre Roy, Joe R. Melton, Jennifer L. Baltzer, Youngryel Ryu, Matteo Detto, and Oliver Sonnentag

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Short summary
Accurately simulating photosynthesis and evapotranspiration challenges terrestrial biosphere models across North America’s boreal biome, in part due to uncertain representation of the maximum rate of photosynthetic carboxylation (Vcmax). This study used forest stand scale observations in an optimization framework to improve Vcmax values for representative vegetation types. Several stand characteristics well explained spatial Vcmax variability and were useful to improve boreal forest modelling.