Getting Forest Carbon Right in Climate Models

New method predicts how climates will move as temperatures rise.

Image courtesy of Wikimedia Commons, peupleloup
A new modeling approach suggests that boreal forests, such as this one in Quebec, Canada, will shift north with warming and lose more carbon than previously expected.

The Science

The extreme complexity of Earth System Models (ESMs) is necessary to represent the many processes underlying terrestrial carbon cycling. However, simple models may be useful to qualitatively understand projected dynamic responses to warming and identify processes missing in the models.

The Impact

Results from a climate modeling study suggest that potential carbon losses known to be missing in ESMs (e.g., from forest disturbance and mortality), must be better represented to robustly predict the carbon response to rising temperatures southern boreal forests.


A Department of Energy (DOE) scientist at Lawrence Berkeley National Laboratory developed a simple model for vegetation carbon response that predicts where a given climate for a region is going in the future and where a given climate will come from. His “climate analogue” method tracks the movement of the most statistically similar climate at every location in an ESM over an interval of time and recalculates the carbon flux within the ESMs participating in the Coupled Model Intercomparison Project 5. The most important area of disagreement between this simple method and the full ESM calculations involves southern boreal forests, where ESMs predict carbon gains, while the simplified approach projects losses.


Charles D. Koven
Earth Sciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd., Berkeley, CA, 94720


This research was supported by the Office of Biological and Environmental Research within DOE’s Office of Science under contract no. DEAC02- 05CH11231 as part of the Climate and Earth System Modeling program.


Koven, C. “Boreal carbon loss due to poleward shift in low-carbon ecosystems.” Nature Geoscience 6, 452–456 (2013). [DOI: 10.1038/ngeo1801].

Highlight Categories

Program: BER , CESD

Performer: DOE Laboratory