PS 48-47
Parameter differences cause diverse predictions of carbon sequestration between two global land models
The land atmospheric carbon exchange is one of the major factors controlling climate. Representation of the terrestrial carbon cycle in land models is becoming increasingly complex and thus understanding key factors driving model behavior has become a great challenge. Therefore, it is crucial to promote methods for quantitative and critical assessment of the models. In this study, we apply a systematic computational traceability framework to global land models (NCAR’s Community Land Model (version CLM3.5) and Australian Community Atmosphere Biosphere Land Exchange (CABLE)) for better understanding of ecosystem C dynamics. This study also examines the contribution of different plant functional types (PFT) in determining the total carbon storage capacity. The traceability framework decomposes a complex land model into components based on fundamental properties of biogeochemical processes. The framework defines ecosystem carbon storage capacity as a product of net primary productivity (NPP) and ecosystem residence time. The ecosystem residence time is further defined by baseline carbon residence times, environmental scalars, and environmental forcings.
Results/Conclusions
Under the prescribed forcing data, the modeled results showed that the total C storage capacity in CLM-CASA is ~28% higher compared to CABLE. The difference between models is largely due to the combined effect of higher NPP and lower ecosystem residence time in CLM-CASA. However, the baseline carbon residence time is higher in CABLE model, highlighting the strong influence of environmental effects. At PFT level, tundra and deciduous needle leaf forest in CLM-CASA showed 50% higher C storage capacity compared to CABLE. Similarly, evergreen boreal forest showed ~35% higher C storage capacity in CLM-CASA as compared to respective components in CABLE. However, C3 and C4 grasses showed much closer agreement in both models. These PFT differences are attributed to climate forcing driving the models which are considerably different across PFT in both models. Overall, our results demonstrate that the baseline carbon residence time has stronger influence over carbon storage capacity compared to environmental effects.