Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Intercomparison of Terrestrial Carbon Fluxes and Carbon Use Efficiency Simulated by CMIP5 Earth System Models

  • 319 Accesses

Abstract

This study compares historical simulations of the terrestrial carbon cycle produced by 10 Earth System Models (ESMs) that participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Using MODIS satellite estimates, this study validates the simulation of gross primary production (GPP), net primary production (NPP), and carbon use efficiency (CUE), which depend on plant function types (PFTs). The models show noticeable deficiencies compared to the MODIS data in the simulation of the spatial patterns of GPP and NPP and large differences among the simulations, although the multi-model ensemble (MME) mean provides a realistic global mean value and spatial distributions. The larger model spreads in GPP and NPP compared to those of surface temperature and precipitation suggest that the differences among simulations in terms of the terrestrial carbon cycle are largely due to uncertainties in the parameterization of terrestrial carbon fluxes by vegetation. The models also exhibit large spatial differences in their simulated CUE values and at locations where the dominant PFT changes, primarily due to differences in the parameterizations. While the MME-simulated CUE values show a strong dependence on surface temperatures, the observed CUE values from MODIS show greater complexity, as well as non-linear sensitivity. This leads to the overall underestimation of CUE using most of the PFTs incorporated into current ESMs. The results of this comparison suggest that more careful and extensive validation is needed to improve the terrestrial carbon cycle in terms of ecosystem-level processes.

This is a preview of subscription content, log in to check access.

References

  1. Allen, C. D., and Coauthors, 2010: A global overview of drought and heatinduced tree mortality reveals emerging climate change risks for forests. Forest Ecol. Manag., 259, 660–684, doi:10.1016/j.foreco.2009.09.001.

  2. Amthor, J. S., 2000: The McCree-de Wit-Penning de Vries-Thornley respiration paradigms: 30 years later. Ann. Bot., 86, 1–20.

  3. Anav, A., and Coauthors, 2013: Evaluating the land and ocean components of the global carbon cycle in the CMIP5 Earth System Models. J. Climate, 26, 6801–6843, doi:10.1175/JCLI-D-12-00417.1.

  4. Andres, R. J., J. S. Gregg, L. Losey, G. Marland, and T. A. Boden, 2011: Monthly, global emissions of carbon dioxide from fossil fuel consumption. Tellus, 63, 309–327, doi:10.1111/j.1600-0889.2011.00530.x.

  5. Arnone III, J. A., and C. Körner, 1997: Temperature adaptation and acclimation potential of leaf dark respiration in two species of Ranunculus from warm and cold habitats. Arctic Alp. Res., 29, 122–125, doi:10. 2307/1551842.

  6. Arora, V. K., and Coauthors, 2009: The effect of terrestrial photosynthesis down-regulation on the twentieth-century carbon budget simulated with the CCCma Earth System Model. J. Climate, 22, 6066–6088.

  7. Arora, V. K., and Coauthors, 2013: Carbon-concentration and carbon-climate feedbacks in CMIP5 earth system models. J. Climate, 26, 5289–5314, doi:10.1175/JCLI-D-12-00494.1.

  8. Atkin, O. K., L. J. Atkinson, R. A. Fisher, C. D. Campbell, J. Zaragoza-Castells, J. W. Pitchford, F. I. Woodward, and V. Hurry, 2008: Using temperature-dependent changes in leaf scaling relationships to quantitatively account for thermal acclimation of respiration in a coupled global climate-vegetation model. Glob. Change Biol., 14, 2709–2726, doi:10.1111/j.1365-2486.2008.01664.x.

  9. Bond-Lamberty, B., and A. Thomson, 2010: Temperature-associated increases in the global soil respiration record. Nature, 464, 579–582, doi:10.1038/nature08930.

  10. Booth, B. B. B., and Coauthors, 2012: High sensitivity of future global warming to land carbon cycle processes. Environ. Res. Lett., 7, 024002, doi:10.1088/1748-9326/7/2/024002.

  11. Choudhury, B. J., 2000: Carbon use efficiency, and net primary productivity of terrestrial vegetation. Adv. Space Res., 26, 1105–1108.

  12. Collatz, G. J., M. Ribas-Carbo, and J. A. Berry, 1992: Coupled photosynthesis-stomatal conductance model for leaves of C4 plants. Funct. Plant Biol., 19, 519–538, doi:10.1071/PP9920519.

  13. De Lucia, E. H., J. E. Drake, R. B. Thomas, and M. Gonzalez-Meler, 2007: Forest carbon use efficiency: Is respiration a constant fraction of gross primary production? Glob. Change Biol., 13, 1157–1167, doi:10.1111/j.1365-2486.2007.01365.x.

  14. Dewar, R. C., B. E. Medlyn, and R. E. McMurtrie, 1999: Acclimation of the respiration photosynthesis ratio to temperature: Insights from a model. Glob. Change Biol., 5, 615–622, doi:10.1046/j.1365-2486.1999. 00253.x.

  15. Dunne, J. P., and Coauthors, 2012: GFDL’s ESM2 global coupled climatecarbon Earth System Models Part II: Carbon system formulation and baseline simulation vharacteristics. J. Climate, 26, 2247–2267, doi:10. 1175/JCLI-D-12-00150.1.

  16. Enquist, B. J., A. J. Kerkhoff, S. C. Stark, N. G. Swenson, M. C. McCarthy, and C. A. Price, 2007: A general integrative model for scaling plant growth, carbon flux, and functional trait spectra. Nature, 449, 218–222, doi:10.1038/nature06061.

  17. Farquhar, G. D., S. von Caemmerer, and J. A. Berry, 1980: A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta, 149, 78–90, doi:10.1007/BF00386231.

  18. Foley, J. A., I. C. Prentice, N. Ramankutty, S. Levis, D. Pollard, S. Stich, and A. Haxeltine, 1996: An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics. GlobalBiogeochem. Cy., 10, 603–628.

  19. Friedlingstein, P., I. Fung, E. Holland, J. John, G. Brasseur, D. Erickson, and D. Schimel, 1995: On the contribution of CO2 fertilization to the missing biospheric sink. Global Biogeochem. Cy., 9, 541–556, doi:10. 1029/95GB02381.

  20. Friedlingstein, P., and Coauthors, 2006: Climate-carbon cycle feedback analysis: Results from the C4MIP model intercomparison. J. Climate, 19, 3337–3353, doi:10.1175/JCLI3800.1.

  21. Friedlingstein, P., M. Meinshausen, V. K. Arora, C. D. Jones, A. Anav, S. K. Liddicoat, and R. Knutti, 2014: Uncertainties in CMIP5 climate projections due to carbon cycle feedbacks. J. Climate, 27, 511–526, doi: 10.1175/JCLI-D-12-00579.1.

  22. Gifford, R. M., 1994: The global carbon-cycle -a viewpoint on the missing sink. Funct. Plant Biol., 21, 1–15, doi:10.1071/PP9940001.

  23. Giorgetta, M. A., and Coauthors, 2013: Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5. J. Adv. Model. Earth Sy., 5, 572–597, doi:10.1002/jame.20038.

  24. Harris, I., P. D. Jones, T. J. Osborn, and D. H. Lister, 2014: Updated highresolution grids of monthly climatic observations -the CRU TS3.10 Dataset. Int. J. Climatol., 34, 623–642, doi:10.1002/joc.3711.

  25. Heinsch, F. A., and Coauthors, 2006: Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. IEEE T. Geosci. Remote., 44, 1908–1925, doi:10. 1109/TGRS.2005.853936.

  26. Hoffman, F. M., and Coauthors, 2013: Causes and implications of persistent atmospheric carbon dioxide biases in Earth System Models. J. Geophys. Res., 119, 141–162, doi:10.1002/2013JG002381.

  27. Hurtt, G. C., and Coauthors, 2011: Harmonization of land-use scenarios for the period 1500-2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. Climatic Change, 109, 117–161, doi:10.1007/s10584-011-0153-2.

  28. Jung, M., and Coauthors, 2011: Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. J. Geophys. Res., 116, G00J07, doi:10.1029/2010JG001566.

  29. Knapp, A. K., J. T. Fahnestock, S. P. Hamburg, L. B. Statland, T. R. Seastedt, and D. S. Schimel, 1993: Landscape patterns in soil-plant water relations and primary production in tallgrass prairie. Ecology, 74, 549–560.

  30. King, A. W., 2006: Atmosphere: Plant respiration in a warmer world. Science, 312, 536, doi:10.1126/science.1114166.

  31. Larcher, W., and B. Mair, 1968: Das Kälteresistenzverhalten von Quercus pubescens, Ostrya carpinifolia und Fraxinus ornus auf drei thermisch unterschiedlichen Standorten. Oecolog. Plantar., 3, 255–270.

  32. Leith, C. E., 1975: Climate response and fluctuation dissipation. J. Atmos. Sci., 32, 2022–2026, doi:10.1175/1520-0469(1975)032<2022:CRAFD> 2.0.CO;2.

  33. Long, M. C., K. Lindsay, S. Peacock, J. K. Moore, and S. C. Doney, 2013: Twentieth-century oceanic carbon uptake and storage in CEMS1 (BGC). J. Climate, 26, 6775–6800, doi:10.1175/JCLI-D-12-00184.1.

  34. Mao, J., P. E. Thornton, X. Shi, M. Zhao, and W. M. Post, 2012: Remote sensing evaluation of CLM4 GPP for the period 2000-09. J. Climate, 25, 5327–5342, doi:10.1175/JCLI-D-11-00401.1.

  35. Monteith, J., 1972: Solar radiation and productivity in tropical ecosystems. J. Appl. Ecol., 9, 747–766, doi:10.2307/2401901.

  36. Nemani, R. R., C. D. Keeling, H. Hashimoto, W. M. Jolly, S. C. Piper, C. J. Tucker, R. B. Myneni, and S. W. Running, 2003: Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science, 300, 1560–1563, doi:10.1126/science.1082750.

  37. Obata, A., 2007: Climate-carbon cycle model response to freshwater discharge into the North Atlantic. J. Climate, 20, 5962–5976, doi:10. 1175/2007JCLI1808.1.

  38. Piao, S., P. Ciais, P. Friedlingstein, N. Noblet-Ducoudré, P. Cadule, N. Viovy, and T. Wang, 2009: Spatiotemporal patterns of terrestrial carbon cycle during the 20th century, Global Biogeochem. Cy., 23, GB4026, doi:10.1029/2008GB003339.

  39. Piao, S., S. Luyssaert, P. Ciais, I. A. Janssens, A. Chen, C. Cao, J. Fang, P. Friedlingstein, Y. Luo, and S. Wang, 2010: Forest annual carbon cost: A global-scale analysis of autotrophic respiration. Ecology, 91, 652–661, doi:10.1890/08-2176.1.

  40. Rahman, A. F., D. A. Sims, V. D. Cordova, and B. Z. El-Masri, 2005: Potential of MODIS EVI and surface temperature for directly estimating per-pixel ecosystem C fluxes. Geophys. Res. Lett., 32, L19404, doi:10.1029/2005GL024127.

  41. Running, S. W., and S. T. Gower, 1991: FOREST-BGC, a general model of forest ecosystem processes for regional applications. II. Dynamic carbon allocation and nitrogen budgets. Tree Physiol., 9, 147–160, doi: 10.1093/treephys/9.1-2.147.

  42. Ryan, M. G., 1991: Effects of climate change on plant respiration. Ecol. Appl., 1, 157–167, doi:10.2307/1941808.

  43. Shao, P., X. Zeng, K. Sakaguchi, R. K. Monson, and X. Zeng, 2013: Terrestrial carbon cycle: climate relations in eight CMIP5 earth system models. J. Climate, 26, 8744–8764, doi:10.1175/JCLI-D-12-00831.1.

  44. Taylor, K. E., 2001: Summarizing multiple aspects of model performance in a single diagram. J. Geophy. Res., 106, 7183–7192, doi:10.1029/2000JD900719.

  45. Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485–498, doi:10. 1175/BAMS-D-11-00094.1.

  46. Tjiputra, J. F., C. Roelandt, M. Bentsen, D. M. Lawrence, T. Lorentzen, J. Schwinger, Ø. Seland, and C. Heinze, 2013: Evaluation of the carbon cycle components in the Norwegian Earth System Model (NorESM). Geosci. Model Dev., 6, 301–325, doi:10.5194/gmd-6-301-2013.

  47. Tucker, C. L., J. Bell, E. Pendall, and K. Ogle, 2013: Does declining carbon-use efficiency explain thermal acclimation of soil respiration with warming? Glob. Change Biol., 19, 252–263, doi:10.1111/gcb.12036.

  48. Turner, P. D., W. D. Ritts, M. Zhao, S. A. Kurc, A. L. Dunn, S. C. Wofsy, E. E. Small, and S. W. Running, 2006: Assessing interannual variation in MODIS-based estimates of gross primary production. IEEE T.. Geosci. Remote, 44, 1899–1907.

  49. Todd-Brown, K. E. O., J. T. Randerson, W. M. Post, F. M. Hoffman, C. Tarnocai, E. A. G. Schuur, and S. D. Allison, 2013: Causes of variation in soil carbon simulations from CMIP5 earth system models and comparison with observations. Biogeosci., 10, 1717–1736, doi:10.5194/bg-10-1717-2013.

  50. Watanabe, S., and Coauthors, 2011: MIROC-ESM 2010: Model description and basic results of CMIP5-20c3m experiments. Geosci. Model Dev., 4, 845–872, doi:10.5194/gmd-4-845-2011

  51. Williams, D. N., B. N. Lawrence, M. Lautenschlager, D. Middleton, and V. Balaji, 2011: The earth system grid federation: Delivering globally accessible petascale data for CMIP5. Proc. Asia-Pac. Adv. Network, 32, 121–130, doi:10.7125/APAN.32.15.

  52. Woodwell, G. M., 1990: The effects of global warming. In Global Warming: The Greenpeace Report, J. Leggett Ed., Oxford University Press, 116-132.

  53. Wu, T., and Coauthors, 2013: Global carbon budgets simulated by the Beijing Climate Center Climate System Model for the last century. J. Geophy. Res., 118, 4326–4347, doi:10.1002/jgrd.50320.

  54. Yang, W., N. V. Shabanov, D. Huang, W. Wang, R. E. Dickinson, R. R. Nemani, Y. Knyazikhin, and R. B. Myneni, 2006: Myneni Analysis of leaf area index products from combination of MODIS Terra and Aqua data. Remote Sens. Environ., 104, 297–312, doi:10.1016/j.rse.2006. 04.016.

  55. Yukimoto, S., and Coauthors, 2011: Meteorological Research Institute-Earth System Model Version 1 (MRI-ESM1): Model description. Technical Reports of the Meteorological Research Institute No.64, 88 pp, doi:10.11483/mritechrepo.64.

  56. Zaehle, S., and Coauthors, 2014: Evaluation of 11 terrestrial carbonnitrogen cycle models against observations from two temperate Free-Air CO2 Enrichment studies. New phytol., 202, 803–822, doi:10.1111/nph.12697.

  57. Zha, T. S., and Coauthors, 2013: Gross and aboveground net primary production at Canadian forest carbon flux sites. Agricul. Forest Meteorol., 174, 54–64, doi:10.1016/j.agrformet.2013.02.004.

  58. Zhang, Y., M. Xu, H. Chen, and J. Adams, 2009: Global pattern of NPP to GPP ratio derived from MODIS data: Effects of ecosystem type, geographical location and climate. Glob. Ecol. Biogeogr., 18, 280–290, doi:10.1111/j.1466-8238.2008.00442.x.

  59. Zhang, Y., G. Yu, J. Yang, M. C. Wimberly, X. Zhang, J. Tao, Y. Jiang, and J. Zhu, 2014: Climate-driven global changes in carbon use efficiency. Glob. Ecol. Biogeogr., 23, 144–155, doi:10.1111/geb.12086.

  60. Zhao, F., and N. Zeng, 2014: Continued increase in atmospheric CO2 seasonal amplitude in the 21st century projected by the CMIP5 Earth System Models. Earth Syst. Dynam., 5, 423–439, doi:10.5194/esd-5-423-2014.

  61. Zhao, M. S., F. A. Heinsch, R. R. Nemani, and S. W. Running, 2005: Improvements of the MODIS terrestrial gross and net primary production global data set. Remote Sens. Environ., 95, 164–176, doi:10.1016/j.rse.2004.12.011.

  62. Zhu, Q., and Q. Zhuang, 2015: Ecosystem biogeochemistry model parameterization: Do more flux data result in a better model in predicting carbon flux? Ecosphere, 6, 1–20, doi:10.1890/ES15-00259.1.

Download references

Author information

Correspondence to Myong-In Lee.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kim, D., Lee, M., Jeong, S. et al. Intercomparison of Terrestrial Carbon Fluxes and Carbon Use Efficiency Simulated by CMIP5 Earth System Models. Asia-Pacific J Atmos Sci 54, 145–163 (2018). https://doi.org/10.1007/s13143-017-0066-8

Download citation

Key words

  • Earth system models
  • carbon use efficiency
  • CMIP5
  • MODIS
  • gross primary production
  • net primary production