The flying leap for carbon: Challenges for predicting the co-evolution of carbon-climate for the 21st century

Background/Question/Methods A new generation of global climate models predicts the co-evolution of CO2 and climate in response to scenarios of fossil fuel combustion.  The models all show a positive coupling between the carbon cycle and climate for the 21st century:  the capacities of the land and oceans to store carbon decrease with global warming, and the accelerating global warming leads to a greater airborne fraction of the fossil fuel CO2.   The results included in the 4th Assessment Report of the IPCC show a divergence in the degree of carbon-climate coupling, so that the modeled atmospheric CO2 abundance and global mean surface air temperature for the same fossil fuel emission scenario differ by as much as >250 ppmv and >3.5C, respectively at the end of the 21st century. While models continue to expand the comprehensiveness and complexity of their biogeochemistry processes, validating the model simulations, especially for a future climate with no previous analog, remains an open challenge.  This paper presents a review of the Carbon Land Model Intercomparison Project (C-LAMP), which is a first attempt at a systematic assessment of terrestrial biogeochemistry modules coupled to a single version of the NCAR Community Climate System Model (CCSM).  Nine different classes of observations are used.  The scoring system we developed attempts to weight the relevance of different observations for improving model performance with respect to at least three diverging classes of carbon-climate model objectives: 1) assessing the strength of the feedback between the carbon cycle and climate system (and thus the requirements on future CO2 emissions for stabilization scenarios), 2) improving our understanding of how regional climate is likely to be affected by land cover change, and 3) assessing climate change impacts on ecosystem function.

Results/Conclusions C-LAMP identifies a path forward for community contributions to the development and validation of coupled BGC-climate models