Divergent predictions of carbon storage between two global land models: attribution of the causes through traceability analysis
Abstract. Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models' performance. In this study, we applied a traceability analysis, which decomposes carbon cycle models into traceable components, to two global land models (CABLE and CLM-CASA') to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, the CLM-CASA' model predicted ~ 31 % larger carbon storage capacity than the CABLE model. Since ecosystem carbon storage capacity is a product of net primary productivity (NPP) and ecosystem residence time (τE), the predicted difference in the storage capacity between the two models results from differences in either NPP or τE or both. Our analysis showed that CLM-CASA' simulated 37 % higher NPP than CABLE due to higher rates of carboxylation (Vcmax) in CLM-CASA'. On the other hand, τE, which was a function the baseline carbon residence time (τ'E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA'. The difference in τE was mainly found to be caused by longer τ'E in CABLE than CLM-CASA'. This difference in τE was mainly caused by longer τ'E of woody biomass (23 vs. 14 years in CLM-CASA') and higher proportion of NPP allocated to woody biomass (23 vs. 16 %). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ'E. Overall; the traceability analysis is an effective method for identifying sources of variations between the two models.