A bias-corrected projection for the changes in East Asian summer monsoon rainfall under global warming

  • Shijie Zhou
  • Gang HuangEmail author
  • Ping HuangEmail author


Projecting regional rainfall changes in a warmer climate attracts ongoing attention. However, large uncertainty still exists in multi-model projection. In this study, we introduce a bias-corrected method to correct the multi-model projection of changes in East Asian summer monsoon (EASM) rainfall based on the historical and RCP8.5 runs of 25 models from phase 5 of Coupled Model Intercomparison Project. Firstly, the total rainfall changes are separated into the thermodynamic component due to increased specific humidity and the dynamic component due to circulation changes. The thermodynamic component is corrected using the observed present-day rainfall and the increase rate of specific humidity based on the wet-get-wetter mechanism. On the other hand, the dynamic component with the circulation changes is corrected based on a “spatial emergent constraint” method, which is further validated by the perfect model approach. Together, these corrections give an integrated projection for EASM rainfall changes under global warming. Such an approach can improve the signal-to-noise ratio of projection effectively, from the original 0.73 of the multimodel mean to around 1.9. The corrected projection of EASM rainfall changes shows a pronounced increase in southern China, the northwest Pacific and a belt from northern China to northeastern China, and a weak increase in other EASM regions.


East Asian summer monsoon Rainfall Bias correction CMIP5 Global warming 



This work is supported by the National Natural Science Foundation of China (41575088, 41722504, 41425019, 41721004 and 41661144016), the Strategic Priority Research Program of Chinese Academy of Sciences (XDA20060501), the Public Science and Technology Research Funds Projects of Ocean (201505013), and the Youth Innovation Promotion Association of CAS and the Fundamental Research Funds for the Central Universities. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP5, and the climate modeling groups (listed in Table 1) for producing and making available their model output. We also thank two anonymous reviewers for their constructive suggestions.

Supplementary material

382_2019_4980_MOESM1_ESM.docx (1.9 mb)
Supplementary material 1 (DOCX 1956 kb)


  1. Abe M, Shiogama H, Nozawa T, Emori S (2011) Estimation of future surface temperature changes constrained using the future-present correlated modes in inter-model variability of CMIP3 multimodel simulations. J Geophys Res 116:D18104CrossRefGoogle Scholar
  2. Adler RF, Huffman GJ, Chang A, Ferraro R, Xie P-P, Janowiak J, Rudolf B, Schneider U, Curtis S, Bolvin D, Gruber A, Susskind J, Arkin P, Nelkin E (2003) The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present). J Hydrometeorol 4(6):1147–1167CrossRefGoogle Scholar
  3. Allen MR, Ingram WJ (2002) Constraints on future changes in climate and the hydrologic cycle. Nature 419(6903):224–232Google Scholar
  4. Bracegirdle TJ, Stephenson DB (2012) Higher precision estimates of regional polar warming by ensemble regression of climate model projections. Climate Dyn 39(12):2805–2821CrossRefGoogle Scholar
  5. Bracegirdle TJ, Stephenson DB (2013) On the robustness of emergent constraints used in multimodel climate change projections of arctic warming. J Climate 26(2):669–678CrossRefGoogle Scholar
  6. Brown JR, Moise AF, Colman R, Zhang H (2016) Will a warmer world mean a wetter or drier Australian monsoon? J Climate 29(12):4577–4596CrossRefGoogle Scholar
  7. Byrne MP, O’Gorman PA (2015) The response of precipitation minus evapotranspiration to climate warming: why the “wet-get-wetter, dry-get-drier” scaling does not hold over land. J Climate 28(20):8078–8092CrossRefGoogle Scholar
  8. Byrne MP, O’Gorman PA (2013) Link between land-ocean warming contrast and surface relative humidities in simulations with coupled climate models. Geophys Res Lett 40(19):5223–5227CrossRefGoogle Scholar
  9. Chen H, Sun J (2013) Projected change in East Asian summer monsoon precipitation under RCP scenario. Meteorol Atmos Phys 121(1–2):55–77CrossRefGoogle Scholar
  10. Chen X, Zhou T (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(21):9433–9439CrossRefGoogle Scholar
  11. Chou C, Neelin JD (2004) Mechanisms of global warming impacts on regional tropical precipitation. J Climate 17:2688–2701CrossRefGoogle Scholar
  12. Chou C, Neelin JD, Chen C-A, Tu J-Y (2009) Evaluating the “rich-get-richer” mechanism in tropical precipitation change under global warming. J Climate 22(8):1982–2005CrossRefGoogle Scholar
  13. Chou C, Chiang JCH, Lan C-W, Chung C-H, Liao Y-C, Lee C-J (2013) Increase in the range between wet and dry season precipitation. Nat Geosci 6(4):263–267CrossRefGoogle Scholar
  14. Collins M, Chandler RE, Cox PM, Huthnance JM, Rougier J, Stephenson DB (2012) Quantifying future climate change. Nat Climate Change 2(6):403–409CrossRefGoogle Scholar
  15. Cox PM, Pearson D, Booth BB, Friedlingstein P, Huntingford C, Jones CD, Luke CM (2013) Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability. Nature 494:341CrossRefGoogle Scholar
  16. de Carvalho LMV (2016) The monsoons and climate change. In: de Carvalho LMV, Jones C (eds) The monsoons and climate change: observations and modeling. Springer International Publishing, BerlinCrossRefGoogle Scholar
  17. Ding Y, Chan JCL (2005) The East Asian summer monsoon: an overview. Meteorol Atmos Phys 89:117–142CrossRefGoogle Scholar
  18. Endo H, Kitoh A (2014) Thermodynamic and dynamic effects on regional monsoon rainfall changes in a warmer climate. Geophys Res Lett 41(5):1704–1711CrossRefGoogle Scholar
  19. Gao Y, Wang H, Jiang D (2015) An intercomparison of CMIP5 and CMIP3 models for interannual variability of summer precipitation in Pan-Asian monsoon region. Int J Climatol 35(13):3770–3780CrossRefGoogle Scholar
  20. Gill AE (1980) Some simple solutions for heat-induced tropical circulation. Q J R Meteorol Soc 106(449):447–462CrossRefGoogle Scholar
  21. Hall A, Cox P, Huntingford C, Klein S (2019) Progressing emergent constraints on future climate change. Nat Climate Change 9(4):269–278CrossRefGoogle Scholar
  22. Ham Y-G, Kug J-S, Choi J-Y, Jin F-F, Watanabe M (2018) Inverse relationship between present-day tropical precipitation and its sensitivity to greenhouse warming. Nat Climate Change 8(1):64–69CrossRefGoogle Scholar
  23. Hawkins E, Sutton R (2009) The potential to narrow uncertainty in regional climate predictions. Bull Am Meteorol Soc 90(8):1095–1107CrossRefGoogle Scholar
  24. Hawkins E, Sutton R (2011) The potential to narrow uncertainty in projections of regional precipitation change. Climate Dyn 37(1–2):407–418CrossRefGoogle Scholar
  25. He C, Zhou T (2015) Responses of the Western North Pacific subtropical high to global warming under RCP4.5 and RCP8.5 scenarios projected by 33 CMIP5 models: the dominance of tropical Indian Ocean–tropical Western Pacific SST gradient. J Climate 28(1):365–380CrossRefGoogle Scholar
  26. Held IM, Soden BJ (2006) Robust responses of the hydrological cycle to global warming. J Climate 19:5686–5699CrossRefGoogle Scholar
  27. Hsu P-c, Li T, Luo J-J, Murakami H, Kitoh A, Zhao M (2012) Increase of global monsoon area and precipitation under global warming: a robust signal? Geophys Res Lett 39(6):L06701Google Scholar
  28. Hu Z-Z, Yang S, Wu R (2003) Long-term climate variations in China and global warming signals. J Geophys Res 108(19):4614CrossRefGoogle Scholar
  29. Huang P (2014) Regional response of annual-mean tropical rainfall to global warming. Atmos Sci Lett 15(2):103–109CrossRefGoogle Scholar
  30. Huang P (2017) Time-varying response of ENSO-induced tropical pacific rainfall to global warming in CMIP5 models. Part II: intermodel uncertainty. J Climate 30(2):595–608CrossRefGoogle Scholar
  31. Huang P, Ying J (2015) A multimodel ensemble pattern regression method to correct the tropical Pacific SST change patterns under global warming. J Clim 28(12):4706–4723CrossRefGoogle Scholar
  32. Huang P, Xie S-P, Hu K, Huang G, Huang R (2013) Patterns of the seasonal response of tropical rainfall to global warming. Nat Geosci 6(5):357–361CrossRefGoogle Scholar
  33. Kanamitsu M, Ebisuzaki W, Woollen J, Yang S-K, Hnilo JJ, Fiorino M, Potter GL (2002) NCEP–DOE AMIP-II reanalysis (R-2). Bull Am Meteorol Soc 83(11):1631–1644CrossRefGoogle Scholar
  34. Kent C, Chadwick R, Rowell DP (2015) Understanding uncertainties in future projections of seasonal tropical precipitation. J Climate 28(11):4390–4413CrossRefGoogle Scholar
  35. Kimoto M (2005) Simulated change of the East Asian circulation under global warming scenario. Geophys Res Lett 32:L16701CrossRefGoogle Scholar
  36. Kitoh A, Endo H, Krishna Kumar K, Cavalcanti IFA, Goswami P, Zhou T (2013) Monsoons in a changing world: a regional perspective in a global context. J Geophys Res Atmos 118(8):3053–3065CrossRefGoogle Scholar
  37. Klein SA, Hall A (2015) Emergent constraints for cloud feedbacks. Curr Climate Change Rep 1(4):276–287CrossRefGoogle Scholar
  38. Knutti R (2010) The end of model democracy? Climate Change 102(3–4):395–404CrossRefGoogle Scholar
  39. Kusunoki S, Mizuta R (2013) Changes in precipitation intensity over East Asia during the 20th and 21st centuries simulated by a global atmospheric model with a 60 km grid size. J Geophys Res Atmos 118(19):11007–11016CrossRefGoogle Scholar
  40. Li X, Ting M (2017) Understanding the Asian summer monsoon response to greenhouse warming: the relative roles of direct radiative forcing and sea surface temperature change. Climate Dyn 49(7–8):2863–2880CrossRefGoogle Scholar
  41. Li G, Xie S-P (2014) Tropical biases in CMIP5 multimodel ensemble: the excessive Equatorial Pacific cold tongue and double ITCZ problems. J Climate 27(4):1765–1780CrossRefGoogle Scholar
  42. Li G, Xie S-P, He C, Chen Z (2017) Western Pacific emergent constraint lowers projected increase in Indian summer monsoon rainfall. Nat Climate Change 7(10):708–712CrossRefGoogle Scholar
  43. Long S-M, Xie S-P, Liu W (2016) Uncertainty in tropical rainfall projections: atmospheric circulation effect and the ocean coupling. J Climate 29(7):2671–2687CrossRefGoogle Scholar
  44. Mike H, Zhao Z-C, Jiang T (1994) Recent and future climate change in East Asia. Int J Climatol 14:637–658CrossRefGoogle Scholar
  45. Räisänen J, Ruokolainen L, Ylhäisi J (2010) Weighting of model results for improving best estimates of climate change. Climate Dyn 35(2–3):407–422CrossRefGoogle Scholar
  46. Roderick ML, Sun F, Lim WH, Farquhar GD (2014) A general framework for understanding the response of the water cycle to global warming over land and ocean. Hydrol Earth Syst Sci 18(5):1575–1589CrossRefGoogle Scholar
  47. Seager R, Naik N, Vecchi GA (2010) Thermodynamic and dynamic mechanisms for large-scale changes in the hydrological cycle in response to global warming. J Climate 23(17):4651–4668CrossRefGoogle Scholar
  48. Seo KH, Ok J, Son JH, Cha DH (2013) Assessing future changes in the East Asian Summer Monsoon using CMIP5 coupled models. J Climate 26(19):7662–7675CrossRefGoogle Scholar
  49. Song F, Zhou T (2014) The climatology and interannual variability of East Asian Summer Monsoon in CMIP5 coupled models: does air-sea coupling improve the simulations? J Climate 27(23):8761–8777CrossRefGoogle Scholar
  50. Sperber KR, Annamalai H, Kang IS, Kitoh A, Moise A, Turner A, Wang B, Zhou T (2013) The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century. Climate Dyn 41(9–10):2711–2744CrossRefGoogle Scholar
  51. Thomson MC, Doblas-Reyes FJ, Mason SJ, Hagedorn R, Connor SJ, Phindela T, Morse AP, Palmer TN (2006) Malaria early warnings based on seasonal climate forecasts from multi-model ensembles. Nature 439(7076):576–579CrossRefGoogle Scholar
  52. Ueda H, Iwai A, Kuwako K, Hori ME (2006) Impact of anthropogenic forcing on the Asian summer monsoon as simulated by eight GCMs. Geophys Res Lett 33(6):L06703CrossRefGoogle Scholar
  53. Vecchi GA, Soden BJ, Wittenberg AT, Held IM, Leetmaa A, Harrison MJ (2006) Weakening of tropical Pacific atmospheric circulation due to anthropogenic forcing. Nature 441(7089):73–76CrossRefGoogle Scholar
  54. Wang B, Yim S-Y, Lee J-Y, Liu J, Ha K-J (2014) Future change of Asian-Australian monsoon under RCP 4.5 anthropogenic warming scenario. Climate Dyn 42(1–2):83–100CrossRefGoogle Scholar
  55. Wu P, Christidis N, Stott P (2013) Anthropogenic impact on Earth’s hydrological cycle. Nat Climate Change 3(9):807–810CrossRefGoogle Scholar
  56. Xie P, Arkin PA (1997) Global precipitation: a 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull Am Meteorol Soc 78(11):2539–2558CrossRefGoogle Scholar
  57. Xie S-P, Deser C, Vecchi GA, Ma J, Teng H, Wittenberg AT (2010) Global warming pattern formation: sea surface temperature and rainfall. J Climate 23(4):966–986CrossRefGoogle Scholar
  58. Xie S-P, Deser C, Vecchi GA, Collins M, Delworth TL, Hall A, Hawkins E, Johnson NC, Cassou C, Giannini A, Watanabe M (2015) Towards predictive understanding of regional climate change. Nat Climate Change 5(10):921–930CrossRefGoogle Scholar
  59. Ying J, Huang P (2016) Cloud-radiation feedback as a leading source of uncertainty in the tropical pacific SST warming pattern in CMIP5 models. J Climate 29(10):3867–3881CrossRefGoogle Scholar
  60. Zheng Y, Shinoda T, Lin J-L, Kiladis GN (2011) Sea surface temperature biases under the stratus cloud deck in the Southeast Pacific Ocean in 19 IPCC AR4 coupled general circulation models. J Climate 24(15):4139–4164CrossRefGoogle Scholar
  61. Zhou Z-Q, Xie S-P (2015) Effects of climatological model biases on the projection of tropical climate change. J Climate 28(24):9909–9917CrossRefGoogle Scholar
  62. Zhou S, Huang G, Huang P (2018) Changes in the East Asian summer monsoon rainfall under global warming: moisture budget decompositions and the sources of uncertainty. Climate Dyn 51(4):1363–1373CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

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
  2. 2.Laboratory for Regional Oceanography and Numerical ModelingQingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  3. 3.University of Chinese Academy of SciencesBeijingChina
  4. 4.Center for Monsoon System Research, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  5. 5.Joint Center for Global Change Studies (JCGCS)BeijingChina

Personalised recommendations