Advertisement

Science Bulletin

, Volume 61, Issue 18, pp 1451–1459 | Cite as

Uncertainty in crossing time of 2 °C warming threshold over China

  • Xiaolong ChenEmail author
  • Tianjun Zhou
Article Earth Sciences

Abstract

The 2 °C warming target has been used widely in global and regional climate change research. Previous studies have shown large uncertainties in the time when surface air temperature (SAT) change over China will reach 2 °C relative to the pre-industrial era. To understand the uncertainties, we analyzed the projected SAT in the twenty-first century using 40 state-of-the-art climate models under two Representative Concentration Pathways (RCP4.5 and RCP8.5) from the Coupled Model Intercomparison Project Phase 5. The 2 °C threshold-crossing time (TCT) of SAT averaged across China was around 2033 and 2029 for RCP4.5 and RCP8.5, respectively. Considering a ±1σ range of intermodel SAT change, the upper and lower bounds of the 2 °C TCT could differ by about 25 years or even more. Uncertainty in the projected SAT and the warming rate around the TCT are the two main factors responsible for the TCT uncertainty. The former is determined by the climate sensitivity represented by the global mean surface temperature response. About 45 % of the intermodel variance of the projected 2 °C TCT for averaged SAT over China can be explained by climate sensitivity across the models, which is contributed mainly by central and southern China. In a climate more sensitive to CO2 forcing, stronger greenhouse effect, less stratus cloud over the East Asian monsoon region, and less snow cover on the Tibetan Plateau result in increased downward longwave radiation, increased shortwave radiation, and decreased shortwave radiation reflected by the surface, respectively, all of which may advance the TCT.

Keywords

2 °C threshold Projection uncertainty China region CMIP5 Climate sensitivity 

中国地区2°C升温阈值到达时间的不确定性

摘要

本研究利用第五次耦合模式比较计划(CMIP5)40个气候模式在两种未来典型浓度路径下(RCP4.5和RCP8.5)的预估结果,分析了中国地区2°C阈值到达时间的不确定性。结果表明地表气温预估的不确定性和到达阈值附近的升温速率是影响阈值到达时间不确定性的两个主要因素,前者与模式气候敏感度有关。高气候敏感度下,温室效应更强、层云更少、高原积雪覆盖率更低,增加了入射的长波、短波通量,减小地表反射的短波通量,使得局地气温到达2°C的时间提前。

关键字

2°C阈值 预估不确定性 中国地区 耦合模式比较计划 气候敏感度 

Notes

Acknowledgments

We thank three anonymous reviewers for their constructive suggestions for improving this study. This work was supported jointly by the “Strategic Priority Research Program–Climate Change: Carbon Budget and Related Issues” of the Chinese Academy of Sciences (XDA05110300), the Research Fund for Commonwealth Trades (Meteorology) (GYHY201506012), the National Natural Science Foundation of China (41420104006), and the China Postdoctoral Science Foundation (2015M581152). We acknowledge the climate modeling groups for making available their model output (http://cmip-pcmdi.llnl.gov/cmip5/availability.html) and the World Climate Research Program’s (WCRP’s) Working Group on Coupled Modeling (WGCM) which coordinates the CMIP5 project.

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Hartmann DL, Klein Tank AMG, Rusticucci M et al (2013) Observations: atmosphere and surface. In: Stocker TF, Qin DH, Plattner GK et al (eds) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate changes. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USAGoogle Scholar
  2. 2.
    Mann ME (2009) Defining dangerous anthropogenic interference. Proc Natl Acad Sci USA 106:4065–4066ADSCrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Drijfhout S, Bathiany S, Beaulieu C et al (2015) Catalogue of abrupt shifts in intergovernmental panel on climate change climate models. Proc Natl Acad Sci USA 112:E5777–E5786ADSCrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Field CB, Barros VR, Mach KJ et al (2014) Technical summary. In: Field CB, Barros VR, Dokken DJ et al (eds) Climate change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USAGoogle Scholar
  5. 5.
    Knutti R, Rogelj J, Sedláček J et al (2016) A scientific critique of the two-degree climate change target. Nat Clim Change 9:13–18Google Scholar
  6. 6.
    Meinshausen M, Meinshausen N, Hare W et al (2009) Greenhouse-gas emission targets for limiting global warming to 2°C. Nature 458:1158–1162ADSCrossRefPubMedGoogle Scholar
  7. 7.
    Joshi M, Hawkins E, Sutton R et al (2011) Projections of when temperature change will exceed 2°C above pre-industrial levels. Nat Clim Change 1:407–412ADSCrossRefGoogle Scholar
  8. 8.
    Jiang DB, Fu YH (2012) Climate change over China with a 2°C global warming. Chin J Atmos Sci 36:234–246 (in Chinese)Google Scholar
  9. 9.
    Lang XM, Sui Y (2013) Changes in mean and extreme climates over China with a 2°C global warming. Chin Sci Bull 58:734–742CrossRefGoogle Scholar
  10. 10.
    Mann ME (2014) False hope. Sci Am 310:78–81CrossRefPubMedGoogle Scholar
  11. 11.
    Meehl GA, Stocker TF, Collins WD et al (2007) Global climate projections. In: Solomon S, Qin DH, Manning M et al (eds) Climate change 2007: The physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate changes. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USAGoogle Scholar
  12. 12.
    Zhou TJ, Chen XL (2015) Uncertainty in the 2°C warming threshold related to climate sensitivity and climate feedback. J Meteor Res 29:884–895CrossRefGoogle Scholar
  13. 13.
    Stocker TF, Qin DH, Plattner GK et al (2013) Technical summary. In: Stocker TF, Qin DH, Plattner GK et al (eds) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate changes. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USAGoogle Scholar
  14. 14.
    Vial J, Dufresne JL, Bony S (2013) On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates. Clim Dyn 41:3339–3362CrossRefGoogle Scholar
  15. 15.
    Chen XL, Zhou TJ (2015) Distinct effects of global mean warming and regional sea surface warming pattern on projected uncertainty in the South Asian summer monsoon. Geophys Res Lett 42:9433–9439ADSCrossRefGoogle Scholar
  16. 16.
    Grise KM, Polvani LM (2014) Is climate sensitivity related to dynamical sensitivity? A Southern Hemisphere perspective. Geophys Res Lett 41:534–540ADSCrossRefGoogle Scholar
  17. 17.
    Bony S, Bellon G, Klocke D et al (2013) Robust direct effect of carbon dioxide on tropical circulation and regional precipitation. Nat Geosci 6:447–451ADSCrossRefGoogle Scholar
  18. 18.
    Jiang DB, Zhang Y, Sun JQ (2009) Ensemble projection of 1–3°C warming in China. Chin Sci Bull 54:3326–3334CrossRefGoogle Scholar
  19. 19.
    Zhang L (2012) Projections of 2.0°C warming over the globe and China under RCP4.5. Atmos Ocean Sci Lett 5:514–520Google Scholar
  20. 20.
    Zhang L, Ding YH, Wu TW et al (2013) The 21st century annual mean surface air temperature change and the 2°C warming threshold over the globe and China as projected by the CMIP5 models. Acta Meteor Sin 71:1047–1060 (in Chinese)Google Scholar
  21. 21.
    Moss RH, Edmonds JA, Hibbard KA et al (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–756ADSCrossRefPubMedGoogle Scholar
  22. 22.
    Chen XL, Zhou TJ, Guo Z (2014) Climate sensitivities of two versions of FGOALS model to idealized radiative forcing. Sci China Earth Sci 57:1363–1373CrossRefGoogle Scholar
  23. 23.
    Held IM, Soden BJ (2000) Water vapor feedback and global warming. Annu Rev Energy Environ 25:441–475CrossRefGoogle Scholar
  24. 24.
    Du ZC (2011) Analysis and simulation of the characteristics of precipitation and cloud system in the Asian monsoon region and projection of their change trend. Dissertation. Beijing: Graduate School of Chinese Academy of Sciences (in Chinese)Google Scholar
  25. 25.
    Xia K, Wang B (2015) Evaluation and projection of snow cover fraction over Eurasia. Clim Environ Res 20:41–52 (in Chinese)Google Scholar
  26. 26.
    Tschakert P (2015) 1.5°C or 2°C: a conduit’s view from the science-policy interface at COP20 in Lima, Peru. Clim Change Responses 2:3CrossRefGoogle Scholar
  27. 27.
    Schleussner CF, Lissner TK, Fischer EM et al (2016) Differential climate impacts for policy-relevant limits to global warming: the case of 1.5°C and 2°C. Earth Syst Dyn 7:327–351ADSCrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina

Personalised recommendations