Climate Dynamics

, Volume 24, Issue 5, pp 435–448 | Cite as

Climate-related uncertainties in projections of the twenty-first century terrestrial carbon budget: off-line model experiments using IPCC greenhouse-gas scenarios and AOGCM climate projections

Article

Abstract

A terrestrial ecosystem model (Sim-CYCLE) was driven by multiple climate projections to investigate uncertainties in predicting the interactions between global environmental change and the terrestrial carbon cycle. Sim-CYCLE has a spatial resolution of 0.5°, and mechanistically evaluates photosynthetic and respiratory CO2 exchange. Six scenarios for atmospheric-CO2 concentrations in the twenty-first century, proposed by the Intergovernmental Panel on Climate Change, were considered. For each scenario, climate projections by a coupled atmosphere–ocean general circulation model (AOGCM) were used to assess the uncertainty due to socio-economic predictions. Under a single CO2 scenario, climate projections with seven AOGCMs were used to investigate the uncertainty stemming from uncertainty in the climate simulations. Increases in global photosynthesis and carbon storage differed considerably among scenarios, ranging from 23 to 37% and from 24 to 81 Pg C, respectively. Among the AOGCM projections, increases ranged from 26 to 33% and from 48 to 289 Pg C, respectively. There were regional heterogeneities in both climatic change and carbon budget response, and different carbon-cycle components often responded differently to a given environmental change. Photosynthetic CO2 fixation was more sensitive to atmospheric CO2, whereas soil carbon storage was more sensitive to temperature. Consequently, uncertainties in the CO2 scenarios and climatic projections may create additional uncertainties in projecting atmospheric-CO2 concentrations and climates through the interactive feedbacks between the atmosphere and the terrestrial ecosystem.

References

  1. IPCC (1990) Climate change: the IPCC scientific assessment. Cambridge University Press, CambridgeGoogle Scholar
  2. IPCC (1994) Climate change 1994: radiative forcing of climate change and an evaluation of the IPCC IS92 emission scenarios. Cambridge University Press, CambridgeGoogle Scholar
  3. IPCC (2000) Special report on emissions scenarios. Cambridge University Press, CambridgeGoogle Scholar
  4. IPCC (2001) Climate change 2001: the scientific basis. Cambridge University Press, CambridgeGoogle Scholar
  5. Boer G, Flato G, Ramsden D (2000) A transient climate change simulation with greenhouse gas and aerosol forcing: projected to the twenty-first century. Clim Dyn 16:427–450CrossRefGoogle Scholar
  6. Bolin B, Kheshgi HS (2001) On strategies for reducing greenhouse gas emissions. Proc Natl Acad Sci USA 98:4850–4854Google Scholar
  7. Cao M, Woodward FI (1998) Dynamic responses of terrestrial ecosystem carbon cycling to global climate change. Nature 393:249–252Google Scholar
  8. Covey C, AchutaRao KM, Cubasch U, Jones P, Lambert SJ, Mann ME, Phillips TJ, Taylor KE (2003) An overview of results from the Coupled Model Intercomparison Project. Global Planet Change 37:103–133CrossRefGoogle Scholar
  9. Cox PM, Betts RA, Jones GD, Spall SA, Totterdell IJ (2000) Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408:184–187CrossRefPubMedGoogle Scholar
  10. Cox PM, Betts RA, Collins M, Harris P, Huntingford C, Jones CD (2003) Amazon dieback under climate-carbon cycle projections for the 21st century, HCTN-42. Hadley Centre, UK Meteorological Office, p 29Google Scholar
  11. Cramer W, Kicklighter DW, Bondeau A, Moore BI, Churkina G, Nemry B, Ruimy A, Schloss AL, Potsdam NPP model intercomparison participants (1999) Comparing global NPP models of terrestrial net primary productivity (NPP): overview and key results. Global Change Biol 5(Suppl 1):1–15CrossRefGoogle Scholar
  12. Cramer W, Bondeau A, Woodward FI, Prentice IC, Betts RA, Brovkin V, Cox PM, Fisher V, Foley JA, Friend AD, Kucharik C, Lomas MR, Ramankutty N, Sitch S, Smith B, White A, Young-Molling C (2001) Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models. Global Change Biol 7:357–373Google Scholar
  13. Delire C, Foley JA, Thompson S (2003) Evaluating the carbon cycle of a coupled atmosphere-biosphere model. Global Biogeochem Cycles 17:1012, doi 10.1029/2002GB001870Google Scholar
  14. Delworth TL, Stouffer RJ, Dixon KW, Spelman MJ, Knutson TR, Broccoli AJ, Kushner PJ, Wetherald RT (2002) Review of simulations of climate variability and change with the GFDL R30 coupled climate model. Clim Dyn 19:555–574CrossRefGoogle Scholar
  15. Dufresne J-L, Friedlingstein P, Berthelot M, Bopp L, Ciais P, Fairhead L, Le Treut H, Monfray P (2001) On the magnitude of positive feedback between future climate change and the carbon cycle. Geophys Res Lett 29:1405, doi 10.1029/2001GL013777Google Scholar
  16. Enting IG (1992) The incompatibility of ice-core CO2 data with reconstructions of biotic CO2 sources (II): the influence of CO2-fertilized growth. Tellus 44B:23–32Google Scholar
  17. Friedlingstein P, Bopp L, Ciais P, Dufresne J-L, Fairhead L, LeTreut H, Monfray P, Orr J (2001) Positive feedback between future climate change and the carbon cycle. Geophys Res Lett 28:1543–1546CrossRefGoogle Scholar
  18. Friedlingstein P, Dufresne J-L, Cox P, Rayner P (2003) How positive is the feedback between climate change and the carbon cycle. Tellus 55B:692–700Google Scholar
  19. Fujita D, Ishizawa M, Maksyutov S, Thornton PE, Saeki T, Nakazawa T (2003) Inter-annual variability of the atmospheric carbon dioxide concentrations as simulated with global terrestrial biosphere models and an atmospheric transport model. Tellus 55B:530–546Google Scholar
  20. Gordon HB, O’Farrell SP (1997) Transient climate change in the CSIRO coupled model with dynamic sea ice. Mon Wea Rev 125:875–907Google Scholar
  21. Gregory JM, Lowe JA (2000) Predictions of global and regional sea-level rise using AOGCMs with and without flux adjustment. Geophys Res Lett 27:3069–3072Google Scholar
  22. Gregory JM, Church JA, Boer GJ, Dixon KW, Flato GM, Jackett DR, Lowe JA, O’Farrell SP, Roeckner E, Russell GL, Stouffer RJ, Winton M (2001) Comparison of results from several AOGCMs for global and regional sea-level change 1900–2100. Clim Dyn 18:225–240Google Scholar
  23. Hazarika MK (2003) Integration of remote sensing with terrestrial ecosystem model to estimate the net primary productivity. PhD Thesis, University of TokyoGoogle Scholar
  24. Ito A (2003) A global-scale simulation of the CO2 exchange between the atmosphere and the terrestrial biosphere with a mechanistic model including stable carbon isotopes, 1953–1999. Tellus 55B:596–612Google Scholar
  25. Ito A (2004) Global mapping of terrestrial primary productivity and light-use efficiency with a process-based model. In: Proceedings of the global mapping workshop, TERRAPUB, Tokyo, pp 343–358Google Scholar
  26. Ito A, Oikawa T (2000) A model analysis of the relationship between climate perturbations and carbon budget anomalies in global terrestrial ecosystems: 1970–1997. Clim Res 15:161–183Google Scholar
  27. Ito A, Oikawa T (2002) A simulation model of the carbon cycle in land ecosystems (Sim-CYCLE): a description based on dry-matter production theory and plot-scale validation. Ecol Model 151:147–179Google Scholar
  28. Jones CD, Cox P, Huntingford C (2003) Uncertainty in climate-carbon-cycle projections asociated with the sensitivity of soil respiration to temperature. Tellus 55B:642–648Google Scholar
  29. Joos F, Prentice IC, Sitch S, Meyer R, Hooss G, Plattner G-K, Gerber S, Hasselmann K (2001) Global warming feedbacks on terrestrial carbon uptake under the Intergovernmental Panel on Climate Change (IPCC) emission scenarios. Global Biogeochem Cycles 15:891–907Google Scholar
  30. Keeling CD, Whorf TP (2003) Atmospheric CO2 concentrations—Mauna Loa Observatory, Hawaii, 1958–2002. Oak Ridge National Laboratory, Oak RidgeGoogle Scholar
  31. Kheshgi HS, Jain AK (2003) Projecting future climate change: implications of carbon cycle model intercomparisons. Global Biogeochem Cycles 17:1047, doi 10.1029/2001GB001842Google Scholar
  32. Kicklighter DW, Bruno M, Donges S, Esser G, Heimann M, Helfrich J, Ift F, Joos F, Kaduk J, Kohlmaier GH, McGuire AD, Melillo JM, Meyer R, Moore BI, Nadler A, Prentice IC, Sauf W, Schloss AL, Sitch S, Wittenberg U, Wurth G (1999) A first-order analysis of the potential role of CO2 fertilization to affect the global carbon budget: a comparison of four terrestrial biosphere models. Tellus 51B:343–366Google Scholar
  33. Kirschbaum MUF (2000) Will changes in soil organic carbon act as a positive or negative feedback on global warming? Biogeochemistry 48:21–51CrossRefGoogle Scholar
  34. Knorr W, Heimann M (2001) Uncertainties in global terrestrial biosphere modeling 1. A comprehensive sensitivity analysis with a new photosynthesis and energy balance scheme. Global Biogeochem Cycles 15:207–225Google Scholar
  35. Larcher W (2001) Physiological plant ecology: ecophysiology and stress physiology of functional groups, 4th edition. Springer-Verlag, Berlin Heidelberg New YorkGoogle Scholar
  36. Leuning R (1995) A critical appraisal of a combined stomatal-photosynthesis model for C3 plants. Plant Cell Environ 18:339–355Google Scholar
  37. Lloyd J, Taylor JA (1994) On the temperature dependence of soil respiration. Func Ecol 8:315–323Google Scholar
  38. McGuire AD, Sitch S, Clein JS, Dargaville R, Esser G, Foley J, Heimann M, Joos F, Kaplan J, Kicklighter DW, Meier RA, Melillo JM, Moore BI, Williams LJ, Wittenberg U (2001) Carbon balance of the terrestrial biosphere in the twentieth century: analysis of CO2, climate and land use effects with four process-based ecosystem models. Global Biogeochem Cycles 15:183–206Google Scholar
  39. Melillo JM, McGuire AD, Kicklighter DW, Moore III B, Vörösmarty CJ, Schloss AL (1993) Global climate change and terrestrial net primary production. Nature 363:234–240CrossRefGoogle Scholar
  40. Monsi M, Saeki T (1953) Über den Lichtfaktor in den Pflanzengesellschaften und seine Bedeutung für die Stoffproduktion (in German). Jpn J Bot 14:22–52Google Scholar
  41. Myneni R, Hoffman S, Knyazikhin Y, Privette JL, Glassy J, Tian Y, Wang Y, Song X, Zhang Y, Smith GS, Lotsch A, Friedl M, Morisette JT, Votava P, Nemani RR, Running SW (2002) Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Rem Sens Environ 83:214–231Google Scholar
  42. Neftel A, Moore E, Oeschger H, Stauffer B (1985) Evidence from polar ice cores for the increase in atmospheric CO2 in the past two centuries. Nature 315:45–47Google Scholar
  43. New M, Lister D, Hulme M, Makin I (2002) A high-resolution data set of surface climate over global land areas. Clim Res 21:1–25Google Scholar
  44. Nozawa T, Emori S, Numaguti A, Tsushima Y, Takemura T, Nakajima T, Abe-Ouchi A, Komoto M (2001) Projections of future climate change in the 21st century simulated by the CCSR/NIES CGCM under the IPCC SRES scenarios. In: Matsuno T, Kida H (eds) Present and future of modeling global environmental change: towards integrated modeling. TERRAPUB, Tokyo, pp 15–28Google Scholar
  45. Olson JS, Watts JA, Allison LJ (1983) Carbon in live vegetation of major world ecosystems. ORNL-5862, Oak Ridge National Laboratory, Oak RidgeGoogle Scholar
  46. Pan Y, Melillo JM, McGuire AD, Kicklighter DW, Pitelka LF, Hibbard K, Pierce LL, Running SW, Ojima DS, Parton WJ, Schimel DS, members of VEMAP (1998) Modeled responses of terrestrial ecosystems to elevated atmospheric CO2: a comparison of simulations by the biogeochemistry models of the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP). Oecologia 114: 389–404CrossRefGoogle Scholar
  47. Raich JW, Rastetter EB, Melillo JM, Kicklighter DW, Grace AL, Moore III B, Vörösmarty CJ (1991) Potential net primary productivity in South America: application of a global model. Ecol Appl 1:399–429Google Scholar
  48. Rayner P (2001) ‘Flying Leap’ becomes C4MIP. Res GAIM 4:8–12Google Scholar
  49. Ruimy A, Kergoat L, Bondeau A, Potsdam NPP model intercomparison participants (1999) Comparing global NPP models of terrestrial net primary productivity (NPP): analysis of differences in light absorption and light-use efficiency. Global Change Biol 5 (Suppl1):56–64Google Scholar
  50. Schimel DS, Braswell BH, Holland EA, McKeown R, Ojima DS, Painter TH, Parton WJ, Townsend AR (1994) Climatic, edaphic, and biotic controls over storage and turnover of carbon in soils. Global Biogeochem Cycles 8:279–293Google Scholar
  51. Schlesinger WH (1997) Biogeochemistry: an analysis of global change. Academic Press, San DiegoGoogle Scholar
  52. Stendel M, Christensen JH (2002) Impact of global warming on permafrost conditions in a coupled GCM. Geophys Res Lett 29:1632, doi 10.1029/2001GL014345Google Scholar
  53. VEMAP (1995) Vegetation/ecosystem modeling and analysis project: comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling. Global Biogeochem Cycles 9:407–437CrossRefGoogle Scholar
  54. Washington WM, Weatherly JW, Meehl GA, Semtner AJJ, Bettge TW, Craig AP, Strand WGJ, Arblaster J, Wayland VB, James R, Zhang Y (2000) Parallel climate model (PCM) control and transient simulations. Clim Dyn 16:755–774CrossRefGoogle Scholar
  55. Webb RS, Rosenzweig CE, Levine ER (1993) Specifying land surface characteristics in general circulation models: soil profile data set and derived water-holding capacities. Global Biogeochem Cycles 7:97–108Google Scholar
  56. Xiao X, Melillo JM, Kicklighter DW, McGuire AD, Prinn RG, Wang C, Stone PH, Sokolov A (1998) Transient climate change and net ecosystem production of the terrestrial biosphere. Global Biogeochem Cycles 12:345–360Google Scholar
  57. Zheng D, Prince S, Wright R (2003) Terrestrial net primary production estimates for 0.5° grid cells from field observations—a contribution to global biogeochemical modeling. Global Change Biol 9:46–64CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  1. 1.Frontier Research Center for Global ChangeJapan Agency for Marine-Earth Science and TechnologyYokohamaJapan

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