Abstract
AbstractWith representation of the global carbon cycle becoming increasingly complex in climate models, it is important to develop ways to quantitatively evaluate model performance against in situ and remote sensing observations. Here we present a systematic framework, the Carbon‐LAnd Model Intercomparison Project (C‐LAMP), for assessing terrestrial biogeochemistry models coupled to climate models using observations that span a wide range of temporal and spatial scales. As an example of the value of such comparisons, we used this framework to evaluate two biogeochemistry models that are integrated within the Community Climate System Model (CCSM) – Carnegie‐Ames‐Stanford Approach′ (CASA′) and carbon–nitrogen (CN). Both models underestimated the magnitude of net carbon uptake during the growing season in temperate and boreal forest ecosystems, based on comparison with atmospheric CO2 measurements and eddy covariance measurements of net ecosystem exchange. Comparison with MODerate Resolution Imaging Spectroradiometer (MODIS) measurements show that this low bias in model fluxes was caused, at least in part, by 1–3 month delays in the timing of maximum leaf area. In the tropics, the models overestimated carbon storage in woody biomass based on comparison with datasets from the Amazon. Reducing this model bias will probably weaken the sensitivity of terrestrial carbon fluxes to both atmospheric CO2 and climate. Global carbon sinks during the 1990s differed by a factor of two (2.4 Pg C yr−1 for CASA′ vs. 1.2 Pg C yr−1 for CN), with fluxes from both models compatible with the atmospheric budget given uncertainties in other terms. The models captured some of the timing of interannual global terrestrial carbon exchange during 1988–2004 based on comparison with atmospheric inversion results from TRANSCOM (r=0.66 for CASA′ and r=0.73 for CN). Adding (CASA′) or improving (CN) the representation of deforestation fires may further increase agreement with the atmospheric record. Information from C‐LAMP has enhanced model performance within CCSM and serves as a benchmark for future development. We propose that an open source, community‐wide platform for model‐data intercomparison is needed to speed model development and to strengthen ties between modeling and measurement communities. Important next steps include the design and analysis of land use change simulations (in both uncoupled and coupled modes), and the entrainment of additional ecological and earth system observations. Model results from C‐LAMP are publicly available on the Earth System Grid.
Highlights
A robust finding of coupled climate–carbon models is that the capacities of the ocean and the terrestrial biosphere to store anthropogenic carbon will weaken in the 21st century from climate warming (Cox et al, 2000; Friedlingstein et al, 2001; Fung et al, 2005; Denman et al, 2007)
We describe the model simulation protocols and the observations that we used to evaluate model performance. In this first phase of the Carbon-LAnd Model Intercomparison Project (C-LAMP), we forced the models in an uncoupled mode with atmospheric reanalysis observations and atmospheric CO2 and N-deposition trajectories during the 20th century to allow for direct comparison with several different sets of interannually varying observations
Comparison with MODerate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) showed that for both models, the timing of maximum leaf area lagged behind the observations by 1–2 months (Fig. 1)
Summary
A robust finding of coupled climate–carbon models is that the capacities of the ocean and the terrestrial biosphere to store anthropogenic carbon will weaken in the 21st century from climate warming (Cox et al, 2000; Friedlingstein et al, 2001; Fung et al, 2005; Denman et al, 2007) This positive feedback whereby warming further increases atmospheric CO2 has important implications for climate mitigation policies designed to stabilize greenhouse gas levels. Models that store large amounts of carbon on land in response to elevated levels of atmospheric CO2, for example, have a smaller positive climate–carbon feedback than models with a lower CO2 storage sensitivity (Friedlingstein et al, 2003; Matthews, 2007) This is because greater terrestrial carbon storage causes CO2 to accumulate more slowly in the atmosphere, and as a consequence, there is less warming for a given trajectory of anthropogenic emissions. Deforestation and land use are coupled with climate in other ways, including land manager responses to drought (e.g., van der Werf et al, 2008), but parameterizations of this have not been developed yet for global models
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