The Canadian Terrestrial Ecosystem Model (CTEM)

Development of the Canadian Terrestrial Ecosystem Model (CTEM) began in the early 2000’s at Environment Canada in response to the need for a land surface carbon cycle component for the CanGCM. CTEM, which was at version 2.0 (Melton and Arora, 2016)1 when incorporated into CLASSIC, couples to CLASS and calculates photosynthesis and stomatal conductance on the CLASS timestep (typically between 15 and 30 minutes). The carbon and vegetation dynamics are calculated on a daily timestep after receiving from CLASS daily mean soil moisture, soil temperature, and net radiation.

The principle processes simulated by CTEM include photosynthesis and canopy conductance (Arora, 2003)2; dynamic root distribution (Arora and Boer, 2003)3; maintenance, growth and heterotrophic respiration (Melton et al., 2015)4; tissue turnover, allocation of carbon, and phenology (Arora and Boer, 2005a)5; disturbance (fire) (Arora and Boer, 2005b6; Arora and Melton, 20187); competition for space between plant functional types (Arora and Boer, 20068; Melton and Arora, 20161) and land use change (Arora and Boer, 20109). Various studies have used observation-based datasets to validate CTEM, coupled to CLASS, at scales from site-level to global (e.g. Peng et al., 201410; Melton and Arora, 201411; Melton and Arora, 20161).

General overview of processes simulated by CTEM

CTEM tracks five carbon pools representing plant leaves, roots, and stems along with two detrital pools for litter and soil C. In it’s default configuration CTEM simulates nine plant functional types (PFTs) which relate directly to CLASS' four standard PFTs.

Needleleaf tree (NdlTr) Needleleaf deciduous (NdlEvgTr) Needleleaf evergreen (NdlDcdTr)
Broadleaf tree (BdlTr) Broadleaf cold deciduous (BdlDCoTr) Broadleaf drought/dry deciduous (BdlDDrTr) Broadleaf evergreen (BdlEvgTr)
Grass C$_3$ (GrassC3) C$_4$(GrassC4)
Crop C$_3$ (CropC3) C$_4$ (CropC4)

  1. Melton, J. R. and Arora, V. K.: Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0, Geoscientific Model Development, 9(1), 323–361, 2016. ↩︎

  2. Arora, V. K.: Simulating energy and carbon fluxes over winter wheat using coupled land surface and terrestrial ecosystem models, Agric. For. Meteorol., 118(1-2), 21–47, 2003. ↩︎

  3. Arora, V. K. and Boer, G. J.: A Representation of Variable Root Distribution in Dynamic Vegetation Models, Earth Interact., 7(6), 1–19, 2003. ↩︎

  4. Melton, J. R., Shrestha, R. K. and Arora, V. K.: The influence of soils on heterotrophic respiration exerts a strong control on net ecosystem productivity in seasonally dry Amazonian forests, Biogeosciences, 12(4), 1151–1168, 2015. ↩︎

  5. Arora, V. K. and Boer, G. J.: A parameterization of leaf phenology for the terrestrial ecosystem component of climate models, Glob. Chang. Biol., 11(1), 39–59, 2005. ↩︎

  6. Arora, V. K. and Boer, G. J.: Fire as an interactive component of dynamic vegetation models, J. Geophys. Res., 110(G2), G02008, 2005. ↩︎

  7. Arora, V. K. and Melton, J. R.: Reduction in global area burned and wildfire emissions since 1930s enhances carbon uptake by land, Nat. Commun., 9(1), 1326, 2018. ↩︎

  8. Arora, V. K. and Boer, G. J.: Simulating Competition and Coexistence between Plant Functional Types in a Dynamic Vegetation Model, Earth Interact., 10(10), 1–30, 2006. ↩︎

  9. Arora, V. K. and Boer, G. J.: Uncertainties in the 20th century carbon budget associated with land use change, Glob. Chang. Biol., 16(12), 3327–3348, 2010. ↩︎

  10. Peng, Y., Arora, V. K., Kurz, W. A., Hember, R. A., Hawkins, B. J., Fyfe, J. C. and Werner, A. T.: Climate and atmospheric drivers of historical terrestrial carbon uptake in the province of British Columbia, Canada, Biogeosciences, 11(3), 635–649, 2014. ↩︎

  11. Melton, J. R. and Arora, V. K.: Sub-grid scale representation of vegetation in global land surface schemes: implications for estimation of the terrestrial carbon sink, Biogeosciences, 11(4), 1021–1036, 2014. ↩︎