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Abstract:
Ecosystem responses to rising CO2 concentrations are a major source of uncertainty in climate change projections. Data from
ecosystem-scale Free-Air CO2 Enrichment (FACE) experiments provide a unique opportunity to reduce this uncertainty. The
recent FACE Model–Data Synthesis project aimed to use the information gathered in two forest FACE experiments to assess
and improve land ecosystem models. A new ‘assumption-centred’ model intercomparison approach was used, in which participating
models were evaluated against experimental data based on the ways in which they represent key ecological processes.
By identifying and evaluating the main assumptions causing differences among models, the assumption-centred approach produced
a clear roadmap for reducing model uncertainty. Here, we explain this approach and summarize the resulting research
agenda. We encourage the application of this approach in other model intercomparison projects to fundamentally improve predictive understanding of the Earth system.
