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

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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, for 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, CLM-CASA0 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-CASA0 simulated 37% higher NPP than CABLE. On the other hand, τE, which was a function of the baseline carbon residence time (τE) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA0. This difference in τE was mainly caused by longer τE of woody biomass (23 vs. 14 years in CLM-CASA0), 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.

Figures

  • Figure 1. Determination of ecosystem carbon storage (kg C cm−2) capacity (grey contour lines) by carbon influx (Uss; x axis) and ecosystem residence time (τE; y axis) (at global and biome level) between CABLE and CLM-CASA′. The contour lines show the constant values of ecosystem carbon storage capacity. ENF – evergreen needleleaf forest, EBF – evergreen broadleaf forest, DNF – deciduous needleleaf forest, DBF – deciduous broadleaf forest, shrub – shrub land, C3G – C3 grassland, C4G – C4 grassland. Open squares in the circle show the global values.
  • Figure 2. Spatial distribution of ecosystem residence time (τE) and baseline carbon residence time (τ ′E) (at global and biome level) between CABLE and CLM-CASA′. Abbreviations of biomes are given in Fig. 1. Circles separate the biomes of CLM-CASA′ and CABLE. Open squares in the circle show the global values.
  • Table 1. Photosynthesis parameter values for different biomes in CLM-CASA′ and CABLE. Abbreviations of biomes are given in Fig. 1. The relative difference is calculated by CLM-CASA′ minus CABLE and then divided by CLM-CASA′.
  • Figure 3. Schematic diagram showing the carbon cycle in CABLE (a) and CLM-CASA′ (b). Carbon enters the system through photosynthesis and is partitioned among live pools. From live pools, carbon is transferred to litter pools, and from litter pools it is transferred to soil carbon pools. Values in boxes show the pools residence times. Values outside the boxes show the partitioning and transfer coefficients. The full names of the abbreviated carbon pools are coarse woody debris (CWD), structural litter (surface and soil), metabolic litter (surface and soil), surface microbial litter, soil microbial carbon, fast soil organic matter, slow, and passive soil organic matter.
  • Figure 4. Distribution of climate forcing data (at global and biome levels) used for CABLE and CLM-CASA′ simulations. Open square show the global values. Abbreviations of biomes are given in Fig. 1.
  • Figure 5. Determination of environmental scalars by the temperature and water scalars (at global and biome level) between CABLE and CLM-CASA′. Open squares show the global values. The contour lines show the constant value of environmental scalars. Abbreviations of biomes are given in Fig. 1.
  • Figure 6. Schematic diagram of the traceability framework along with the summary of the results obtained in this study. The numerical values show the percentage increase between two models. Xss – ecosystem carbon storage capacity; τE – ecosystem carbon residence time; τ ′E – baseline carbon residence time; ξ – environmental scalar; ξT – temperature scalar; ξW – water scalar.

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CITATION STYLE

APA

Rafique, R., Xia, J., Hararuk, O., Asrar, G. R., Leng, G., Wang, Y., & Luo, Y. (2016). Divergent predictions of carbon storage between two global land models: Attribution of the causes through traceability analysis. Earth System Dynamics, 7(3), 649–658. https://doi.org/10.5194/esd-7-649-2016

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