A Review of Climate Change Attribution Studies

Abstract

This paper reviews recent progress in climate change attribution studies. The focus is on the attribution of observed long-term changes in surface temperature, precipitation, circulation, and extremes, as well as that of specific extreme weather and climate events. Based on new methods and better models and observations, the latest studies further verify the conclusions on climate change attribution in the IPCC AR5, and enrich the evidence for anthropogenic influences on weather and climate variables and extremes. The uncertainty of global temperature change attributable to anthropogenic forcings lies in the considerable uncertainty of estimated total radiative forcing due to aerosols, while the uncertainty of precipitation change attribution arises from the limitations of observation and model simulations along with influences from large internal variability. In terms of extreme weather and climate events, it is clear that attribution studies have provided important new insights into the changes in the intensity or frequency of some of these events caused by anthropogenic climate change. The framing of the research question, the methods selected, and the model and statistical methods used all have influences on the results and conclusions drawn in an event attribution study. Overall, attribution studies in China remain inadequate because of limited research focus and the complexity of the monsoon climate in East Asia. Attribution research in China has focused mainly on changes or events related to temperature, such as the attribution of changes in mean and extreme temperature and individual heat wave events. Some progress has also been made regarding the pattern of changes in precipitation and individual extreme rainfall events in China. Nonetheless, gaps remain with respect to the attribution of changes in extreme precipitation, circulation, and drought, as well as to the event attribution such as those related to drought and tropical cyclones. It can be expected that, with the continual development of climate models, ongoing improvements to data, and the introduction of new methods in the future, climate change attribution research will develop accordingly. Additionally, further improvement in climate change attribution will facilitate the development of operational attribution systems for extreme events, as well as attribution studies of climate change impacts.

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References

  1. Abram, N. J., R. Mulvaney, F. Vimeux, et al.,2014: Evolution of the Southern Annular Mode during the past millennium. Nat. Clim. Change, 4, 564–569, doi: 10.1038/nclimate2235.

    Google Scholar 

  2. Allen, M., 2003: Liability for climate change. Nature, 421, 891–892, doi: 10.1038/421891a.

    Google Scholar 

  3. Allen, M. R., and S. F. B. Tett, 1999: Checking for model consistency in optimal fingerprinting. Climate Dyn., 15, 419–434, doi: 10.1007/s003820050291.

    Google Scholar 

  4. Allen, M. R., and W. J. Ingram, 2002: Constraints on future changes in climate and the hydrologic cycle. Nature, 419, 224–232, doi: 10.1038/nature01092.

    Google Scholar 

  5. Allen, M. R., N. P. Gillett, J. A. Kettleborough, et al.,2006: Quantifying anthropogenic influence on recent near-surface temperature change. Surv. Geophys., 27, 491–544, doi: 10.1007/s10712-006-9011-6.

    Google Scholar 

  6. Allen, R. J., J. R. Norris, and M. Kovilakam, 2014: Influence of anthropogenic aerosols and the Pacific Decadal Oscillation on tropical belt width. Nature Geosci., 7, 270–274, doi: 10.1038/ngeo2091.

    Google Scholar 

  7. Barnett, T., F. Zwiers, G. Hengerl, et al.,2005: Detecting and attributing external influences on the climate system: A review of recent advances. J. Climate, 18, 1291–1314, doi: 10.1175/JCLI3329.1.

    Google Scholar 

  8. Bindoff, N. L., P. A. Stott, K. M. AchutaRao, et al., 2013: Detection and attribution of climate change: From global to regional. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T. F. Stocker, D. Qin, G. -K. Plattner, et al., Eds., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 867–952.

    Google Scholar 

  9. Burke, C., and P. A. Stott, 2017: Impact of anthropogenic climate change on the East Asian summer monsoon. J. Climate, 30, 5205–5220, doi: 10.1175/JCLI-D-16-0892.1.

    Google Scholar 

  10. Burke, C., P. Stott, A. Ciavarella, et al.,2016: Attribution of extreme rainfall in Southeast China during May 2015 [in “Explaining Extreme Events of 2015 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 97, S92–S96, doi: 10. 1175/BAMS-D-16-0144.1.

    Google Scholar 

  11. Canty, T., N. R. Mascioli, M. D. Smarte, et al.,2013: An empirical model of global climate. Part 1: A critical evaluation of volcanic cooling. Atmos. Chem. Phys., 13, 3997–4031, doi: 10.5194/acp-13-3997-2013.

    Google Scholar 

  12. Cattiaux, J., R. Vautard, and P. Yiou, 2009: Origins of the extremely warm European fall of 2006. Geophys. Res. Lett., 36, L06713, doi: 10.1029/2009GL037339.

    Google Scholar 

  13. Cattiaux, J., R. Vautard, C. Cassou, et al.,2010: Winter 2010 in Europe: A cold extreme in a warming climate. Geophys. Res. Lett., 37, L20704, doi: 10.1029/2010GL044613.

    Google Scholar 

  14. Cayan, D. R., T. Das, D. W. Pierce, et al.,2010: Future dryness in the southwest US and the hydrology of the early 21st century drought. Proc. Natl. Acad. Sci. USA, 107, 21271–21276, doi: 10.1073/pnas.0912391107.

    Google Scholar 

  15. Chen, H. P., and J. Q. Sun, 2017: Contribution of human influence to increased daily precipitation extremes over China. Geophys. Res. Lett., 44, 2436–2444, doi: 10.1002/2016GL 072439.

    Google Scholar 

  16. Christidis, N., and P. A. Stott, 2015: Extreme rainfall in the United Kingdom during winter 2013/14: The role of atmospheric circulation and climate change. Bull. Amer. Meteor. Soc., 96, S46–S50, doi: 10.1175/BAMS-D-15-00094.1.

    Google Scholar 

  17. Christidis, N., P. A. Stott, and A. Ciavarella, 2014: The effect of anthropogenic climate change on the cold spring of 2013 in the United Kingdom. Bull. Amer. Meteor. Soc., 95, S79–S82.

    Google Scholar 

  18. Christidis, N., G. S. Jones, and P. A. Stott, 2015: Dramatically increasing chance of extremely hot summers since the 2003 European heatwave. Nat. Clim. Change, 5, 46–50, doi: 10. 1038/nclimate2468.

    Google Scholar 

  19. Dai, A., 2011: Drought under global warming: A review. WIREs Clim. Change, 2, 45–65, doi: 10.1002/wcc.81.

    Google Scholar 

  20. Dai, A., 2013: Increasing drought under global warming in observations and models. Nat. Clim. Change, 3, 52–58, doi: 10. 1038/nclimate1633.

    Google Scholar 

  21. Delworth, T. L., and F. R. Zeng, 2014: Regional rainfall decline in Australia attributed to anthropogenic greenhouse gases and ozone levels. Nat. Geosci., 7, 583–587, doi: 10.1038/ngeo2201.

    Google Scholar 

  22. Diffenbaugh, N. S., D. L. Swain, and D. Touma, 2015: Anthropogenic warming has increased drought risk in California. Proc. Natl. Acad. Sci. USA, 112, 3931–3936, doi: 10.1073/pnas. 1422385112.

    Google Scholar 

  23. Ding, Q. H., A. Schweiger, M. L’Heureux, et al.,2017: Influence of high-latitude atmospheric circulation changes on summertime Arctic sea ice. Nat. Clim. Change, 7, 289–295, doi: 10. 1038/nclimate3241.

    Google Scholar 

  24. Dong, S. Y., Y. Sun, E. Aguilar, et al.,2018: Observed changes in temperature extremes over Asia and their attribution. Climate Dyn., 51, 339–353, doi: 10.1007/s00382-017-3927-z.

    Google Scholar 

  25. Drost, F., and D. Karoly, 2012: Evaluating global climate responses to different forcings using simple indices. Geophys. Res. Lett., 39, L16701, doi: 10.1029/2012GL052667.

    Google Scholar 

  26. Eyring, V., S. Bony, G. A. Meehl, et al.,2016: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev., 9, 1937–1958, doi: 10.5194/gmd-9-1937-2016.

    Google Scholar 

  27. Fischer, E. M., and R. Knutti, 2015: Anthropogenic contribution to global occurrence of heavy-precipitation and high-temperature extremes. Nat. Clim. Change, 5, 560–564, doi: 10.1038/nclimate2617.

    Google Scholar 

  28. Gao, L., J. Huang, X. W. Chen, et al.,2018: Contributions of natural climate changes and human activities to the trend of extreme precipitation. Atmos. Res., 205, 60–69, doi: 10.1016/j.atmosres.2018.02.006.

    Google Scholar 

  29. Gillett, N. P., and P. A. Stott, 2009: Attribution of anthropogenic influence on seasonal sea level pressure. Geophys. Res. Lett., 36, L23709, doi: 10.1029/2009GL041269.

    Google Scholar 

  30. Gillett, N. P., and J. C. Fyfe, 2013: Annular mode changes in the CMIP5 simulations. Geophys. Res. Lett., 40, 1189–1193, doi: 10.1002/grl.50249.

    Google Scholar 

  31. Gillett, N. P., F. W. Zwiers, A. J. Weaver, et al.,2003: Detection of human influence on sea-level pressure. Nature, 422, 292–294, doi: 10.1038/nature01487.

    Google Scholar 

  32. Gillett, N. P., D. A. Stone, P. A. Stott, et al.,2008: Attribution of polar warming to human influence. Nat. Geosci., 1, 750–754, doi: 10.1038/ngeo338.

    Google Scholar 

  33. Gillett, N. P., J. C. Fyfe, and D. E. Parker, 2013: Attribution of observed sea level pressure trends to greenhouse gas, aerosol, and ozone changes. Geophys. Res. Lett., 40, 2302–2306, doi: 10.1002/grl.50500.

    Google Scholar 

  34. Granger, C. W. J., 1980: Testing for causality: A personal viewpoint. J. Econom. Dyn. Contr., 2, 329–352, doi: 10.1016/0165-1889(80)90069-X.

    Google Scholar 

  35. Harrington, L. J., P. B. Gibson, S. M. Dean, et al.,2016: Investigating event-specific drought attribution using self-organizing maps. J. Geophys. Res. Atmos., 121, 12,766–12,780, doi: 10.1002/2016JD025602.

    Google Scholar 

  36. Hasselmann, K., 1976: Stochastic climate models. Part. Theory. Tellus, 28, 473–485, doi: 10.3402/tellusa.v28i6.11316.

    Google Scholar 

  37. Hasselmann, K., 1997: Multi-pattern fingerprint method for detection and attribution of climate change. Climate Dyn., 13, 601–612, doi: 10.1007/s003820050185.

    Google Scholar 

  38. Haumann, F. A., D. Notz, and H. Schmidt, 2014: Anthropogenic influence on recent circulation-driven Antarctic sea ice changes. Geophys. Res. Lett., 41, 8429–8437, doi: 10.1002/2014GL061659.

    Google Scholar 

  39. He, J., and B. J. Soden, 2015: Anthropogenic weakening of the tropical circulation: The relative roles of direct CO2 forcing and sea surface temperature change. J. Climate, 28, 8728–8742, doi: 10.1175/JCLI-D-15-0205.1.

    Google Scholar 

  40. Hegerl, G., and F. Zwiers, 2011: Use of models in detection and attribution of climate change. WIREs Clim. Change, 2, 570–591, doi: 10.1002/wcc.121.

    Google Scholar 

  41. Hegerl, G. C., F. W. Zwiers, P. Braconnot, et al.,2007: Understanding and attributing climate change. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, S. Solomon, D. Qin, M. Manning, et al., Eds., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 663–745.

    Google Scholar 

  42. Hegerl, G. C., O. Hoegh-Guldberg, G. Casassa, et al.,2010: Good practice guidance paper on detection and attribution related to anthropogenic climate change. Meeting Report of the Intergovernmental Panel on Climate Change Expert Meeting on Detection and Attribution of Anthropogenic Climate Change, T. F. Stocker, C. Field, D. Qin, et al., Eds., University of Bern, Bern, 1–8.

    Google Scholar 

  43. Hegerl, G., F. Zwiers, and C. Tebaldi, 2011: Patterns of change: Whose fingerprint is seen in global warming? Environ. Res. Lett., 6, 044025, doi: 10.1088/1748-9326/6/4/044025.

    Google Scholar 

  44. Herring, S. C., M. P. Hoerling, T. C. Peterson, et al.,2014: Ex-plaining extreme events of 2013 from a climate perspective. Bull. Amer. Meteor. Soc., 95, S1–S104, doi: 10.1175/1520-0477-95.9.S1.1.

    Google Scholar 

  45. Herring, S. C., M. P. Hoerling, J. P. Kossin, et al.,2015: Explaining extreme events of 2014 from a climate perspective. Bull. Amer. Meteor. Soc., 96, S1–S172, doi: 10.1175/BAMS-ExplainingExtremeEvents2014.1.

    Google Scholar 

  46. Herring, S. C., A. Hoell, M. P. Hoerling, et al.,2016: Explaining extreme events of 2015 from a climate perspective. Bull. Amer. Meteor. Soc., 97, S1–S145, doi: 10.1175/BAMS-ExplainingExtremeEvents2015.1.

    Google Scholar 

  47. Herring, S. C., N. Christidis, A. Hoell, et al.,2018: Explaining extreme events of 2016 from a climate perspective. Bull. Amer. Meteor. Soc., 99, S1–S157, doi: 10.1175/BAMS-ExplainingExtremeEvents2016.1.

    Google Scholar 

  48. Hu, Y. Y., and K. K. Tung, 2003: Possible ozone-induced longterm changes in planetary wave activity in late winter. J. Climate, 16, 3027–3038, doi: 10.1175/1520-0442(2003)016 <3027:POLCIP>2.0.CO;2.

    Google Scholar 

  49. Hu, Y. Y., C. Zhou, and J. P. Liu, 2011: Observational evidence for poleward expansion of the Hadley circulation. Adv. Atmos. Sci., 28, 33–44, doi: 10.1007/s00376-010-0032-1.

    Google Scholar 

  50. Imada, Y., H. Siogama, C. Takahashi, et al.,2018: Climate change increased the likelihood of the 2016 heat extremes in Asia [in “Explaining Extreme Events of 2016 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 98, S97–S101, doi: 10.1175/BAMS-D-17-0109.1.

    Google Scholar 

  51. IPCC, 2001: Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, J. T. Houghton, Y. Ding, D. J. Griggs, et al., Eds., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 881 pp.

    Google Scholar 

  52. IPCC, 2007: Climate change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, S. Solomon, D. Qin, M. Manning, et al., Eds., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996 pp.

    Google Scholar 

  53. IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T. F. Stocker, D. Qin, G. K. Plattner, et al., Eds., Cambridge University Press, Cambridge, United Kingdom and New York, NY, 1535 pp, doi: 10.1017/CBO9781107415324.

    Google Scholar 

  54. Jones, G. S., P. A. Stott, and N. Christidis, 2013: Attribution of observed historical near-surface temperature variations to anthropogenic and natural causes using CMIP5 simulations. J. Geophys. Res. Atmos., 118, 4001–4024, doi: 10.1002/jgrd. 50239.

    Google Scholar 

  55. Jones, P. D., and A. Moberg, 2003: Hemispheric and large-scale surface air temperature variations: An extensive revision and an update to 2001. J. Climate, 16, 206–213, doi: 10.1175/1520-0442(2003)016&lt;0206:HALSSA&gt;2.0.CO;2.

    Google Scholar 

  56. Kamae, Y., H. Shiogama, M. Watanabe, et al.,2014: Attributing the increase in Northern Hemisphere hot summers since the late 20th century. Geophys. Res. Lett., 41, 5192–5199, doi: 10.1002/2014GL061062.

    Google Scholar 

  57. Karoly, D. F., and Q. G. Wu, 2005: Detection of regional surface temperature trends. J. Climate, 18, 4337–4343, doi: 10.1175/JCLI3565.1.

    Google Scholar 

  58. Karoly, D. J., K. Braganza, P. A. Stott, et al.,2003: Detection of a human influence on North American climate. Science, 302, 1200–1203, doi: 10.1126/science.1089159.

    Google Scholar 

  59. Kim, Y.-H., S.-K. Min, X. B. Zhang, et al.,2015: Attribution of extreme temperature changes during 1951–2010. Climate Dyn., 46, 1769–1782, doi: 10.1007/s00382-015-2674-2.

    Google Scholar 

  60. Kim, Y.-H., S.-K. Min, S.-W. Son, et al.,2017: Attribution of the local Hadley cell widening in the Southern Hemisphere. Geophys. Res. Lett., 44, 1015–1024, doi: 10.1002/2016GL 072353.

    Google Scholar 

  61. King, A. D., S. C. Lewis, S. E. Perkins, et al.,2013: Limited evidence of anthropogenic influence on the 2011–12 extreme rainfall over Southeast Australia. Bull. Amer. Meteor. Soc., 94, S55–S58.

    Google Scholar 

  62. King, A. D., D. J. Karoly, M. G. Donat, et al.,2014: Climate change turns Australia’s 2013 big dry into a year of recordbreaking heat. Bull. Amer. Meteor. Soc., 95, S41–S45.

    Google Scholar 

  63. Knutson, T. R., and J. J. Ploshay, 2016: Detection of anthropogenic influence on a summertime heat stress index. Climatic Change, 138, 25–39, doi: 10.1007/s10584-016-1708-z.

    Google Scholar 

  64. Knutson, T. R., F. R. Zeng, and A. T. Wittenberg, 2013: Multimodel assessment of regional surface temperature trends: CMIP3 and CMIP5 twentieth-century simulations. J. Climate, 26, 8709–8743, doi: 10.1175/JCLI-D-12-00567.1.

    Google Scholar 

  65. Knutson, T. R., J. P. Kossin, C. Mears, et al.,2017: Detection and attribution of climate change. Climate Science Special Report: Fourth National Climate Assessment, Volume I, D. J. Wuebbles, D. W. Fahey, K. A. Hibbard, et al., Eds., U. S. Global Change Research Program, Washington, DC, USA, 114–132, doi: 10.7930/J01834ND.

    Google Scholar 

  66. Knutson, T. R., J. Kam, F. R. Zeng, et al.,2018: CMIP5 modelbased assessment of anthropogenic influence on record global warmth during 2016 [in “Explaining Extreme Events of 2016 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 98, S11–S15, doi: 10.1175/BAMS-D-17-0104.1.

    Google Scholar 

  67. Lee, S., and S. B. Feldstein, 2013: Detecting ozone-and greenhouse gas-driven wind trends with observational data. Science, 339, 563–567, doi: 10.1126/science.1225154.

    Google Scholar 

  68. Li, C., X. B. Zhang, F. Zwiers, et al.,2017: Recent very hot summers in Northern Hemispheric land areas measured by wet bulb globe temperature will be the norm within 20 years. Earth’s Future, 5, 1203–1216, doi: 10.1002/2017EF000639.

    Google Scholar 

  69. Li, C. X., Q. H. Tian, R. Yu, et al.,2017: Attribution of extreme precipitation in the lower reaches of the Yangtze River during May 2016. Environ. Res. Lett., 13, 014015, doi: 10. 1088/1748-9326/aa9691.

    Google Scholar 

  70. Li, K., H. Liao, W. J. Cai, et al.,2018: Attribution of anthropogenic influence on atmospheric patterns conducive to recent most severe haze over eastern China. Geophys. Res. Lett., 45, 2027–2081, doi: 10.1002/2017GL076570.

    Google Scholar 

  71. Li, Y., Y. H. Ding, and W. J. Li, 2017: Observed trends in various aspects of compound heat waves across China from 1961 to 2015. J. Meteor. Res., 31, 455–467, doi: 10.1007/s13351-017-6150-2.

    Google Scholar 

  72. Liu, R., S. C. Liu, R. J. Cicerone, et al.,2015: Trends of extreme precipitation in eastern China and their possible causes. Adv. Atmos. Sci., 32, 1027–1037, doi: 10.1007/s00376-015-5002-1.

    Google Scholar 

  73. Lu, C. H., Y. Sun, H. Wan, et al.,2016: Anthropogenic influence on the frequency of extreme temperatures in China. Geophys. Res. Lett., 43, 6511–6518, doi: 10.1002/2016GL069296.

    Google Scholar 

  74. Ma, S. M., T. J. Zhou, D. A. Stone, et al.,2017: Detectable anthropogenic shift toward heavy precipitation over eastern China. J. Climate, 30, 1381–1396, doi: 10.1175/JCLI-D-16-0311.1.

    Google Scholar 

  75. Mahlstein, I., G. Hegerl, and S. Solomon, 2012: Emerging local warming signals in observational data. Geophys. Res. Lett., 39, L21711, doi: 10.1029/2012GL053952.

    Google Scholar 

  76. Marvel, K., and C. Bonfils, 2013: Identifying external influences on global precipitation. Proc. Natl. Acad. Sci. USA, 110, 19,301–19,306, doi: 10.1073/pnas.1314382110.

    Google Scholar 

  77. Min, S. K., X. B. Zhang, and F. Zwiers, 2008: Human-induced Arctic moistening. Science, 320, 518–520, doi: 10.1126/science. 1153468.

    Google Scholar 

  78. Min, S. K., X. B. Zhang, F. W. Zwiers, et al.,2011: Human contribution to more-intense precipitation extremes. Nature, 470, 378–381, doi: 10.1038/nature09763.

    Google Scholar 

  79. Min, S. K., Y. H. Kim, M. K. Kim, et al.,2014: Assessing human contribution to the summer 2013 Korean heat wave. Bull. Amer. Meteor. Soc., 95, S48–S51.

    Google Scholar 

  80. Mitchell, J. F. B., D. J. Karoly, G. C. Hegerl, et al.,2001: Detection of climate change and attribution of causes. Climate Change 2001: The Scientific Basis, J. T. Houghton, Y. Ding, D. J. Griggs, et al., Eds., Cambridge University Press, Cambridge, UK, 695–738.

    Google Scholar 

  81. Mitchell, D., P. Davini, B. Harvey, et al.,2017: Assessing mid-latitude dynamics in extreme event attribution systems. Climate Dyn., 48, 3889–3901, doi: 10.1007/s00382-016-3308-z.

    Google Scholar 

  82. Mondal, A., and P. P. Mujumdar, 2015: On the detection of human influence in extreme precipitation over India. J. Hydrol., 529, 1161–1172, doi: 10.1016/j.jhydrol.2015.09.030.

    Google Scholar 

  83. Najafi, M. R., F. W. Zwiers, and N. P. Gillett, 2015: Attribution of Arctic temperature change to greenhouse-gas and aerosol influences. Nat. Clim. Change, 5, 246–249, doi: 10.1038/nclimate2524.

    Google Scholar 

  84. National Academies of Sciences, Engineering, and Medicine (NAS), 2016: Attribution of Extreme Weather Events in the Context of Climate Change. The National Academies Press, Washington, DC, 186 pp, doi: 10.17226/21852.

    Google Scholar 

  85. Noake, K., D. Polson, G. Hegerl, et al.,2012: Changes in seasonal land precipitation during the latter twentieth-century. Geophy. Res. Lett., 39, L03706, doi: 10.1029/2011GL050405.

    Google Scholar 

  86. Otto, F. E., R. G. Jones, K. Halladay, et al.,2013: Attribution of changes in precipitation patterns in African rainforests. Philos. Trans. Roy. Soc. B: Biol. Sci., 368, 20120299, doi: 10.1098/rstb.2012.0299.

    Google Scholar 

  87. Otto, F. E., E. Boyd, R. G. Jones, et al.,2015: Attribution of extreme weather events in Africa: A preliminary exploration of the science and policy implications. Climatic Change, 132, 532–543, doi: 10.1007/s10584-015-1432-0.

    Google Scholar 

  88. Perkins, S. E., and P. B. Gibson, 2014: Increased risk of the 2014 Australian May heatwave due to anthropogenic activity. Bull. Amer. Meteor. Soc., 96, S154–S157, doi: 10.1175/BAMSEEE_2014_ch31.1.

    Google Scholar 

  89. Peterson, T. C., P. A. Stott, and S. Herring, 2012: Explaining extreme events of 2011 from a climate perspective. Bull. Amer. Meteor. Soc., 93, 1041–1067, doi: 10.1175/BAMS-D-12-00021.1.

    Google Scholar 

  90. Peterson, T. C., M. P. Hoerling, P. A. Stott, et al.,2013: Explaining extreme events of 2012 from a climate perspective. Bull. Amer. Meteor. Soc., 94, S1–S74, doi: 10.1175/BAMS-D-13-00085.1.

    Google Scholar 

  91. Polson, D., G. C. Hegerl, X. B. Zhang, et al.,2013: Causes of robust seasonal land precipitation changes. J. Climate, 26, 6679–6697, doi: 10.1175/JCLI-D-12-00474.1.

    Google Scholar 

  92. Polson, D., M. Bollasina, G. C. Hegerl, et al.,2014: Decreased monsoon precipitation in the Northern Hemisphere due to anthropogenic aerosols. Geophys. Res. Lett., 41, 6023–6029, doi: 10.1002/2014GL060811.

    Google Scholar 

  93. Qian, C., 2016a: Disentangling the urbanization effect, multidecadal variability, and secular trend in temperature in eastern China during 1909–2010. Atmos. Sci. Lett., 17, 177–182, doi: 10.1002/asl.640.

    Google Scholar 

  94. Qian, C., 2016b: On trend estimation and significance testing for non-Gaussian and serially dependent data: Quantifying the urbanization effect on trends in hot extremes in the megacity of Shanghai. Climate Dyn., 47, 329–344, doi: 10.1007/s00382-015-2838-0.

    Google Scholar 

  95. Qian, C., and T. J. Zhou, 2014: Multidecadal variability of North China aridity and its relationship to PDO during 1900–2010. J. Climate, 27, 1210–1222, doi: 10.1175/JCLI-D-13-00235.1.

    Google Scholar 

  96. Qian, C., and X. B. Zhang, 2015: Human influences on changes in the temperature seasonality in mid-to high-latitude land areas. J. Climate, 28, 5928–5921, doi: 10.1175/JCLI-D-14-00821.1.

    Google Scholar 

  97. Qian, C., J. Wang, S. Y. Dong, et al.,2018: Human influence on the record-breaking cold event in January of 2016 in eastern China [in “Explaining Extreme Events of 2016 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 99, S118–S122, doi: 10.1175/BAMS-D-17-0095.1.

    Google Scholar 

  98. Rayner, N. A., D. E. Parker, E. B. Horton, et al.,2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108, 4407, doi: 10.1029/2002JD002670.

    Google Scholar 

  99. Ren, G. Y., and Y. Q. Zhou, 2014: Urbanization effect on trends of extreme temperature indices of national stations over mainland China, 1961–2008. J. Climate, 27, 2340–2360, doi: 10.1175/JCLI-D-13-00393.1.

    Google Scholar 

  100. Ribes, A., and L. Terray, 2013: Application of regularised optimal fingerprinting to attribution. Part: Application to global near-surface temperature. Climate Dyn., 41, 2837–2853, doi: 10.1007/s00382-013-1736-6.

    Google Scholar 

  101. Ribes, A., F. W. Zwiers, J. M. Azaïs, et al.,2017: A new statistical approach to climate change detection and attribution. Climate Dyn., 48, 367–386, doi: 10.1007/s00382-016-3079-6.

    Google Scholar 

  102. Rosenzweig, C., G. Casassa, D. J. Karoly, et al.,2007: Assessment of observed changes and responses in natural and managed systems. Climate Change 2007: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, M. L. Parry, O. F. Canziani, J. P. Palutikof, et al., Eds., Cambridge University Press, Cambridge, UK, 79–131.

    Google Scholar 

  103. Santer, B. D., K. E. Taylor, T. M. L. Wigley, et al.,1996: A search for human influences on the thermal structure of the atmosphere. Nature, 382, 39–46, doi: 10.1038/382039a0.

    Google Scholar 

  104. Sarojini, B. B., P. A. Stott, E. Black, et al.,2012: Fingerprints of changes in annual and seasonal precipitation from CMIP5 models over land and ocean. Geophys. Res. Lett., 39, L21706, doi: 10.1029/2012GL053373.

    Google Scholar 

  105. Sarojini, B. B., P. A. Stott, and E. Black, 2016: Detection and attribution of human influence on regional precipitation. Nat. Clim. Change, 6, 669–675, doi: 10.1038/nclimate2976.

    Google Scholar 

  106. Schaller, N., A. L. Kay, R. Lamb, et al.,2016: Human influence on climate in the 2014 southern England winter floods and their impacts. Nat. Clim. Change, 6, 627–364, doi: 10.1038/nclimate2927.

    Google Scholar 

  107. Schneider, T., and I. M. Held, 2001: Discriminants of twentiethcentury changes in earth surface temperatures. J. Climate, 14, 249–254, doi: 10.1175/1520-0442(2001)014<0249:LDOTC C>2.0.CO;2.

    Google Scholar 

  108. Seager, R., N. Naik, and G. A. Vecchi, 2010: Thermodynamic and dynamic mechanisms for large-scale changes in the hydrological cycle in response to global warming. J. Climate, 23, 4651–4668, doi: 10.1175/2010JCLI3655.1.

    Google Scholar 

  109. Seneviratne, S. I., N. Nicholls, D. Easterling, et al.,2012: Changes in climate extremes and their impacts on the natural physical environment. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC), C. B. Field, V. Barros, T. F. Stocker, et al., Eds., Cambridge University Press, Cambridge, United Kingdom, and New York, NY, USA, 109–230.

    Google Scholar 

  110. Shepherd, T. G., 2014: Atmospheric circulation as a source of uncertainty in climate change projections. Nat. Geosci., 7, 703–708, doi: 10.1038/ngeo2253.

    Google Scholar 

  111. Sheffield, J., E. F. Wood, and M. L. Roderick, 2012: Little change in global drought over the past 60 years. Nature, 491, 435–438, doi: 10.1038/nature11575.

    Google Scholar 

  112. Singh, D., D. E. Horton, M. Tsiang, et al.,2014: Severe precipitation in northern India in June 2013. Bull. Amer. Meteor. Soc., 95, S58–S61.

    Google Scholar 

  113. Sippel, S., J. Zscheischler, M. D. Mahecha, et al.,2017: Refining multi-model projections of temperature extremes by evaluation against land–atmosphere coupling diagnostics. Earth Syst. Dyn., 8, 387–403, doi: 10.5194/esd-8-387-2017.

    Google Scholar 

  114. Smirnov, D. A., and I. I. Mokhov, 2009: From Granger causality to long-term causality: Application to climatic data. Phys. Rev. E, 80, 016208, doi: 10.1103/PhysRevE.80.016208.

    Google Scholar 

  115. Smith, J. B., H. J. Schellnhuber, M. M. Qader Mirza, et al.,2001: Vulnerability to climate change and reasons for concern: A synthesis. Climate Change 2001. Impacts, Adaptation, and Vulnerability, J. J. McCarthy, O. F. Canziani, N. A. Leary, et al., Eds., Cambridge University Press, Cambridge, UK, 913–967.

    Google Scholar 

  116. Song, L. C., S. Y. Dong, Y. Sun, et al.,2015: Role of anthropogenic forcing in 2014 hot spring in northern China [in “Explaining Extreme Events of 2014 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 96, S111–S115, doi: 10.1175/BAMS-D-15-00111.1.

    Google Scholar 

  117. Stern, D. I., and R. K. Kaufmann, 2014: Anthropogenic and natural causes of climate change. Climatic Change, 122, 257–269, doi: 10.1007/s10584-013-1007-x.

    Google Scholar 

  118. Stone, D., M. Auffhammer, M. Carrey, et al.,2013: The challenge to detect and attribute effects of climate change on human and natural systems. Climatic Change, 121, 381–395, doi: 10. 1007/s10584-013-0873-6.

    Google Scholar 

  119. Stott, P. A., 2003: Attribution of regional-scale temperature changes to anthropogenic and natural causes. Geophys. Res. Lett., 30, 1728, doi: 10.1029/2003GL017324.

    Google Scholar 

  120. Stott, P. A., D. A. Stone, and M. R. Allen, 2004: Human contribution to the European heatwave of 2003. Nature, 432, 610–614, doi: 10.1038/nature03089.

    Google Scholar 

  121. Stott, P. A., N. P. Gillett, G. C. Hegerl, et al.,2010: Detection and attribution of climate change: A regional perspective. WIREs Clim. Change, 1, 192–211, doi: 10.1002/wcc.34.

    Google Scholar 

  122. Stott, P. A., N. Christidis, F. E. L. Otto, et al.,2016: Attribution of extreme weather and climate-related events. WIREs Clim. Change, 7, 23–41, doi: 10.1002/wcc.380.

    Google Scholar 

  123. Sun, Q. H., and C. Y. Miao, 2018: Extreme rainfall (R20mm, RX5day) in Yangtze–Huai, China, in June–July 2016: The role of ENSO and anthropogenic climate change [in “Explaining Extreme Events of 2016 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 99, S102–S106, doi: 10.1175/BAMS-D-17-0091.1.

    Google Scholar 

  124. Sun, Y., H. Yin, Q. H. Tian, et al.,2013: Recent progress in studies of climate change detection and attribution in the globe and China in the past 50 years. Progressue Inquisitiones de Mutatione Climatis, 9, 235–245, doi: 10.3969/j.issn.1673-1719.2013.04.001. (in Chinese)

    Google Scholar 

  125. Sun, Y., X. B. Zhang, F. W. Zwiers, et al.,2014: Rapid increase in the risk of extreme summer heat in eastern China. Nat. Clim. Change, 4, 1082–1085, doi: 10.1038/nclimate2410.

    Google Scholar 

  126. Sun, Y., X. B. Zhang, G. Y. Ren, et al.,2016a: Contribution of urbanization to warming in China. Nat. Clim. Change, 6, 706–709, doi: 10.1038/nclimate2956.

    Google Scholar 

  127. Sun, Y., L. C. Song, H. Yin, et al.,2016b: Human influence on the 2015 extreme high temperature events in western China [in “Explaining Extreme Events of 2015 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 97, S102–S106, doi: 10.1175/BAMS-D-16-0158.1.

    Google Scholar 

  128. Sun, Y., T. Hu, X. B. Zhang, et al.,2018: Anthropogenic influence on the eastern China 2016 super cold surge [in “Explaining Extreme Events of 2016 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 99, S123–S127, doi: 10.1175/BAMS-D-17-0092.1.

    Google Scholar 

  129. Tao, L. J., Y. Y. Hu, and J. P. Liu, 2016: Anthropogenic forcing on the Hadley circulation in CMIP5 simulations. Climate Dyn., 46, 3337–3350, doi: 10.1007/s00382-015-2772-1.

    Google Scholar 

  130. 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.

    Google Scholar 

  131. Terray, L., L. Corre, S. Cravatte, et al.,2012: Near-surface salinity as nature’s rain gauge to detect human influence on the tropical water cycle. J. Climate, 25, 958–977, doi: 10.1175/JCLID-10-05025.1.

    Google Scholar 

  132. Trenberth, K. E., 2012: Framing the way to relate climate extremes to climate change. Climatic Change, 115, 283–290, doi: 10.1007/s10584-012-0441-5.

    Google Scholar 

  133. Trenberth, K. E., J. T. Fasullo, and T. G. Shepherd, 2015: Attribution of climate extreme events. Nat. Clim. Change, 5, 725–730, doi: 10.1038/nclimate2657.

    Google Scholar 

  134. Uhe, P., F. E. L. Otto, K. Haustein, et al.,2016: Comparison of methods: Attributing the 2014 record European temperatures to human influences. Geophys. Res. Lett., 43, 8685–8693, doi: 10.1002/2016GL069568.

    Google Scholar 

  135. van der Wiel, K., S. B. Kapnick, G. J. van Oldenborgh, et al.,2016: Rapid attribution of the August 2016 flood-inducing extreme precipitation in south Louisiana to climate change. Hydrol. Earth Syst. Sci., 21, 897–921, doi: 10.5194/hess-21-897-2017.

    Google Scholar 

  136. Vautard, R., P. Yiou, F. Otto, et al.,2016: Attribution of humaninduced dynamical and thermodynamical contributions in extreme weather events. Environ. Res. Lett., 11, 114009, doi: 10.1088/1748-9326/11/11/114009.

    Google Scholar 

  137. Vogel, M. M., R. Orth, F. Cheruy, et al.,2017: Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture–temperature feedbacks. Geophys. Res. Lett., 44, 1511–1519, doi: 10.1002/2016GL071235.

    Google Scholar 

  138. Walsh, J. E., R. L. Thoman, U. S. Bhatt, et al.,2018: The high latitude marine heat wave of 2016 and its impacts on Alaska [in “Explaining Extreme Events of 2016 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 98, S39–S43, doi: 10.1175/BAMS-D-17-0105.1.

    Google Scholar 

  139. Walters, D., I. Boutle, M. Brooks, et al.,2017: The Met Office unified model global atmosphere 6.0/6.1 and JULES global land 6.0/6.1 configurations. Geosci. Model Dev., 10, 1487–1520, doi: 10.5194/gmd-10-1487-2017.

    Google Scholar 

  140. Wan, H., X. B. Zhang, F. W. Zwiers, et al.,2013: Effect of data coverage on the estimation of mean and variability of precipitation at global and regional scales. J. Geophys. Res. Atmos., 118, 534–546, doi: 10.1002/jgrd.50118.

    Google Scholar 

  141. Wan, H., X. B. Zhang, Z. Francis, et al.,2014: Attributing northern high-latitude precipitation change over the period 1966–2005 to human influence. Climate Dyn., 45, 1713–1726, doi: 10.1007/s00382-014-2423-y.

    Google Scholar 

  142. Wan, H., X. B. Zhang, and F. W. Zwiers, 2018: Human influence on Canadian temperatures. Climate Dyn., doi: 10.1007/s00 382-018-4145-z.

    Google Scholar 

  143. Wang, J., S. F. B. Tett, Z. W. Yan, et al.,2018: Have human activities changed the frequencies of absolute extreme temperatures in eastern China? Environ. Res. Lett., 13, 014012, doi: 10.1088/1748-9326/aa9404.

    Google Scholar 

  144. Wang, S. W., Y. Luo, Z. C. Zhao, et al.,2012: Attribution of climate warming to the causes. Progressus Inquisitiones de Mutatione Climatis, 8, 308–312, doi: 10.3969/j.issn.1673-1719.2012.04.000. (in Chinese)

    Google Scholar 

  145. Wang, Y. J., Y. Sun, T. Hu, et al.,2018: Attribution of temperature changes in western China. Int. J. Climatol., 38, 742–750, doi: 10.1002/joc.5206.

    Google Scholar 

  146. Wang, Z., Y. J. Jiang, H. Wan, et al.,2017: Detection and attribution of changes in extreme temperatures at regional scale. J. Climate, 30, 7035–7047, doi: 10.1175/JCLI-D-15-0835.1.

    Google Scholar 

  147. Williams, A. P., R. Seager, J. T. Abatzoglou, et al.,2015: Contribution of anthropogenic warming to California drought during 2012–2014. Geophys. Res. Lett., 42, 6819–6828, doi: 10.1002/2015GL064924.

    Google Scholar 

  148. Wu, Q. G., and D. J. Karoly, 2007: Implications of changes in the atmospheric circulation on the detection of regional surface air temperature trends. Geophys. Res. Lett., 34, L08703, doi: 10.1029/2006GL028502.

    Google Scholar 

  149. Yin, H., Y. Sun, H. Wan, et al.,2017: Detection of anthropogenic influence on the intensity of extreme temperatures in China. Int. J. Climatol., 37, 1229–1237, doi: 10.1002/joc.4771.

    Google Scholar 

  150. Yiou, P., and J. Cattiaux, 2014: Contribution of atmospheric circulation to wet southern European winter of 2013 [in "Explaining Extremes of 2013 from a Climate Perspective"]. Bull. Amer. Meteor. Soc., 95, S66–S69, doi: 10.1175/1520-0477-95.9.S1.1.

    Google Scholar 

  151. Yiou, P., R. Vautard, P. Naveau, et al.,2007: Inconsistency between atmospheric dynamics and temperatures during the exceptional 2006/2007 fall/winter and recent warming in Europe. Geophys. Res. Lett., 34, L21808, doi: 10.1029/2007 GL031981.

    Google Scholar 

  152. Yuan, X., S. S. Wang, and Z. Z. Hu, 2018: Do climate change and El Niño increase likelihood of Yangtze River extreme rainfall? [in “Explaining Extreme Events of 2016 from a Climate Perspective”] Bull. Amer. Meteor. Soc., 99, S113–S117, doi: 10.1175/BAMS-D-17-0089.1.

    Google Scholar 

  153. Zhang, R. H., 2015: Changes in East Asian summer monsoon and summer rainfall over eastern China during recent decades. Sci. Bull., 60, 1222–1224, doi: 10.1007/s11434-015-0824-x.

    Google Scholar 

  154. Zhang, X. B., F. W. Zwiers, and P. A. Stott, 2006: Multimodel multisignal climate change detection at regional scale. J. Climate, 19, 4294–4307, doi: 10.1175/JCLI3851.1.

    Google Scholar 

  155. Zhang, X. B., F. W. Zwiers, G. C. Hegerl, et al.,2007: Detection of human influence on twentieth-century precipitation trends. Nature, 448, 461–465, doi: 10.1038/nature06025.

    Google Scholar 

  156. Zhang, X. B., H. Wan, F. W. Zwiers, et al.,2013: Attributing intensification of precipitation extremes to human influence. Geophys. Res. Lett., 40, 5252–5257, doi: 10.1002/grl.51010.

    Google Scholar 

  157. Zhou, C. L., K. C. Wang, and D. Qi, 2018: Attribution of the July 2016 extreme precipitation event over China’s Wuhan [in “Explaining Extreme Events of 2016 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 99, S107–S112, doi: 10.1175/BAMS-D-17-0090.1.

    Google Scholar 

  158. Zhou, T. J., L. J. Li, H. M. Li, et al.,2008: Progress in climate change attribution and projection studies. Chinese J. Atmos. Sci., 32, 906–922. (in Chinese)

    Google Scholar 

  159. Zwiers, F. W., and X. B. Zhang, 2003: Toward regional-scale climate change detection. J. Climate, 16, 793–797, doi: 10.1175/1520-0442(2003)016<0793:TRSCCD>2.0.CO;2.

    Google Scholar 

  160. Zwiers, F. W., X. B. Zhang, and Y. Feng, 2011: Anthropogenic influence on long return period daily temperature extremes at regional scales. J. Climate, 24, 881–892, doi: 10.1175/2010JCLI3908.1.

    Google Scholar 

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Correspondence to Panmao Zhai.

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Supported by the National Key Research and Development Program of China (2017YFA0603501), National Natural Science Foundation of China (41575094), and Basic Research to Operation Funds of the Chinese Academy of Meteorological Sciences (2017Y006).

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Zhai, P., Zhou, B. & Chen, Y. A Review of Climate Change Attribution Studies. J Meteorol Res 32, 671–692 (2018). https://doi.org/10.1007/s13351-018-8041-6

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Key words

  • climate change
  • detection and attribution
  • climate extremes
  • event attribution
  • optimal fingerprinting