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Representations of the terrestrial carbon cycle in land modelsare becoming increasingly complex. It is crucial to develop approaches forcritical assessment of the complex model properties in order to understandkey factors contributing to models' performance. In this study, we applied atraceability analysis which decomposes carbon cycle models into traceablecomponents, for two global land models (CABLE and CLM-CASA′) to diagnose thecauses of their differences in simulating ecosystem carbon storage capacity.Driven with similar forcing data, CLM-CASA′ predicted  ∼ 31 % larger carbon storage capacity than CABLE. 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. On the other hand, τE, which was a function of 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′. 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 showed that the major causes of different carbon storage estimations were found to be parameters setting related to carbon input and baseline carbon residence times between two models

Divergent predictions of carbon storage between two global land models: attribution of the causes through traceability analysis