Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Western Pacific emergent constraint lowers projected increase in Indian summer monsoon rainfall

Nature Climate Change volume 7, pages 708–712 (2017)Cite this article

Subjects

Abstract

The agrarian-based socioeconomic livelihood of densely populated South Asian countries is vulnerable to modest changes in Indian summer monsoon (ISM) rainfall1,2,3. How the ISM rainfall will evolve is a question of broad scientific and socioeconomic importance3,4,5,6,7,8,9. In response to increased greenhouse gas (GHG) forcing, climate models commonly project an increase in ISM rainfall4,5,6,7,8,9. This wetter ISM projection, however, does not consider large model errors in both the mean state and ocean warming pattern9,10,11. Here we identify a relationship between biases in simulated present climate and future ISM projections in a multi-model ensemble: models with excessive present-day precipitation over the tropical western Pacific tend to project a larger increase in ISM rainfall under GHG forcing because of too strong a negative cloud–radiation feedback on sea surface temperature. The excessive negative feedback suppresses the local ocean surface warming, strengthening ISM rainfall projections via atmospheric circulation. We calibrate the ISM rainfall projections using this ‘present–future relationship’ and observed western Pacific precipitation. The correction reduces by about 50% of the projected rainfall increase over the broad ISM region. Our study identifies an improved simulation of western Pacific convection as a priority for reliable ISM projections.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Regional climate changes during the ISM season (May to September) and the relationship between ISM rainfall changes and mean precipitation.
Figure 2: Inter-model relationship between the present-day simulations and future projections and corrections of regional climate projections.
Figure 3: Inter-model regressions of projected changes under the RCP 8.5 scenario against the simulated present-day precipitation (mm d−1) averaged over the tropical western Pacific.
Figure 4: Atmospheric response to the tropical Pacific warming pattern related to the tropical western Pacific precipitation biases in the CAM4 experiment.

References

  1. Gadgil, S. & Gadgil, S. The Indian monsoon, GDP and agriculture. Econ. Polit. Weekly 41, 4887–4895 (2006).

    Google Scholar 

  2. Wahl, E. R. & Morrill, C. Toward understanding and predicting monsoon patterns. Science 328, 437–438 (2010).

    Article  CAS  Google Scholar 

  3. Douglas, I. Climate change, flooding and food security in south Asia. Food Secur. 1, 127–136 (2009).

    Article  Google Scholar 

  4. Christensen, J. H. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 1217–1308 (IPCC, Cambridge Univ. Press, 2014).

    Google Scholar 

  5. Meehl, G. A. & Washington, W. M. South Asian summer monsoon variability in a model with doubled atmospheric carbon dioxide concentration. Science 260, 1101–1104 (1993).

    Article  CAS  Google Scholar 

  6. Turner, A. G. & Annamalai, H. Climate change and the South Asian summer monsoon. Nat. Clim. Change 2, 587–595 (2012).

    Article  Google Scholar 

  7. May, W. Simulated changes of the Indian summer monsoon under enhanced greenhouse gas conditions in a global time-slice experiment. Geophys. Res. Lett. 29, 1118 (2002).

    Article  Google Scholar 

  8. Sooraj, K. P., Terray, P. & Mujumdar, M. Global warming and the weakening of the Asian summer monsoon circulation: assessments from the CMIP5 models. Clim. Dynam. 45, 233–252 (2015).

    Article  Google Scholar 

  9. Chen, X. & Zhou, T. 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, 9433–9439 (2015).

    Article  Google Scholar 

  10. Lin, J. L. The double-ITCZ problem in IPCC AR4 coupled GCMs: ocean-atmosphere feedback analysis. J. Clim. 20, 4497–4525 (2007).

    Article  Google Scholar 

  11. Li, G., Xie, S. P. & Du, Y. Monsoon-induced biases of climate models over the tropical Indian Ocean. J. Clim. 28, 3058–3072 (2015).

    Article  Google Scholar 

  12. Webster, P. J. & Yang, S. Monsoon and ENSO: selectively interactive systems. Q. J. R. Meteorol. Soc. 118, 877–926 (1992).

    Article  Google Scholar 

  13. Goswami, B. N., Krishnamurthy, V. & Annamalai, H. A broad-scale circulation index for the interannual variability of the Indian summer monsoon. Q. J. R. Meteorol. Soc. 125, 611–633 (1999).

    Article  Google Scholar 

  14. Annamalai, H., Hafner, J., Sooraj, K. P. & Pillai, P. Global warming shifts the monsoon circulation, drying South Asia. J. Clim. 26, 2701–2718 (2013).

    Article  Google Scholar 

  15. Kumar, K. K., Rajagopalan, B., Hoerling, M. P., Bates, G. & Cane, M. Unraveling the mystery of Indian monsoon failure during El Niño. Science 314, 115–119 (2006).

    Article  CAS  Google Scholar 

  16. Bollassina, M. A., Ming, Y. & Ramaswamy, V. Anthropogenic aerosols and the weakening of the South Asian summer monsoon. Science 224, 502–505 (2011).

    Article  Google Scholar 

  17. Goswami, B. N., Venugopal, V., Sengupta, D., Madhusoodanan, M. & Xavier, P. K. Increasing trend of extreme rain events over India in a warming environment. Science 314, 1442–1445 (2006).

    Article  CAS  Google Scholar 

  18. Boos, W. R. & Kuang, Z. Dominant control of the South Asian monsoon by orographic insulation versus plateau heating. Nature 463, 218–222 (2010).

    Article  CAS  Google Scholar 

  19. Roxy, M. K. et al. Drying of Indian subcontinent by rapid Indian Ocean warming and a weakening land–sea thermal gradient. Nat. Commun. 6, 7423 (2015).

    Article  Google Scholar 

  20. Bollasina, M. A. Hydrology: probing the monsoon pulse. Nat. Clim. Change 4, 422–423 (2014).

    Article  Google Scholar 

  21. Jain, S. K. & Kumar, V. Trend analysis of rainfall and temperature data for India. Curr. Sci. 102, 37–49 (2012).

    Google Scholar 

  22. Gadgil, S., Vinayachandran, P. N., Francis, P. A. & Gadgil, S. Extremes of the Indian summer monsoon rainfall, ENSO and equatorial Indian Ocean oscillation. Geophys. Res. Lett. 31, L12213 (2004).

    Article  Google Scholar 

  23. Taylor, K. E., Ronald, J. S. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).

    Article  Google Scholar 

  24. Held, I. M. & Soden, B. J. Robust responses of the hydrological cycle to global warming. J. Clim. 19, 5686–5699 (2006).

    Article  Google Scholar 

  25. Brown, J. R., Moise, A. F., Colman, R. & Zhang, H. Will a warmer world mean a wetter or drier Australian monsoon? J. Clim. 29, 4577–4596 (2016).

    Article  Google Scholar 

  26. Meehl, G. A. & Washington, W. M. El Niño-like climate change in a model with increased atmospheric CO2 concentrations. Nature 382, 56–60 (1996).

    Article  CAS  Google Scholar 

  27. Gill, A. E. Some simple solutions for heat-induced tropical circulation. Q. J. R. Meteorol. Soc. 106, 447–462 (1980).

    Article  Google Scholar 

  28. Shaman, J. & Tziperman, E. The effect of ENSO on Tibetan Plateau snow depth: a stationary wave teleconnection mechanism and implications for the South Asian monsoons. J. Clim. 18, 2067–2079 (2005).

    Article  Google Scholar 

  29. Boe, J. L., Hall, A. & Qu, X. September sea-ice cover in the Arctic Ocean projected to vanish by 2100. Nat. Geosci. 2, 341–343 (2009).

    Article  CAS  Google Scholar 

  30. Cox, P. M. et al. Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability. Nature 494, 341–344 (2013).

    Article  CAS  Google Scholar 

  31. Adler, R. F. et al. The version 2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979-present). J. Hydrometeorol. 4, 1147–1167 (2003).

    Article  Google Scholar 

  32. Dai, A. et al. The relative roles of upper and lower tropospheric thermal contrasts and tropical influences in driving Asian summer monsoons. J. Geophys. Res. 118, 7024–7045 (2013).

    Article  Google Scholar 

  33. Sandeep, S. & Ajayamohan, R. S. Poleward shift in Indian summer monsoon low level Jetstream under global warming. Clim. Dynam. 45, 337–351 (2015).

    Article  Google Scholar 

  34. Gent, P. R. et al. The Community Climate System Model version 4. J. Clim. 24, 4973–4991 (2011).

    Article  Google Scholar 

  35. Hurrell, J., Hack, J., Shea, D., Caron, J. & Rosinski, J. A new sea surface temperature and sea ice boundary data set for the Community Atmosphere Model. J. Clim. 21, 5145–5153 (2008).

    Article  Google Scholar 

  36. Li, G. & Xie, S. P. Origins of tropical-wide SST biases in CMIP multi-model ensembles. Geophys. Res. Lett. 39, L22703 (2012).

    Google Scholar 

  37. Shiogama, H. et al. Observational constraints indicate risk of drying in the Amazon basin. Nat. Commun. 2, 253 (2011).

    Article  Google Scholar 

  38. Collins, M. et al. Quantifying future climate change. Nat. Clim. Change 2, 403–409 (2012).

    Article  Google Scholar 

  39. Bracegirdle, T. J. & Stephenson, D. B. On the robustness of emergent constraints used in multimodel climate change projections of Arctic warming. J. Clim. 26, 669–678 (2013).

    Article  Google Scholar 

  40. Li, G., Xie, S. P. & Du, Y. A robust but spurious pattern of climate change in model projections over the tropical Indian Ocean. J. Clim. 29, 5589–5608 (2016).

    Article  Google Scholar 

Download references

Acknowledgements

We are grateful for helpful comments from L. Sun and R. Lu. This work was supported by the Natural Science Foundation of China (41521005 and 41406026), the National Basic Research Program of China (2012CB955603), the Guangdong Natural Science Funds for Distinguished Young Scholar (2015A030306008), the Youth Innovation Promotion Association CAS, and the Pearl River S&T Nova Program of Guangzhou (201506010094). S.-P.X. was supported by the US National Science Foundation (1637450). Z.C. was supported by the Open Project Program of State Key Laboratory of Tropical Oceanography (LTOZZ1603). We acknowledge the climate modelling groups for producing and making available their model output, the WCRP’s Working Group on Coupled Modeling (WGCM) for organizing the CMIP5 analysis activity, the Program for Climate Model Diagnostics and Intercomparison (PCMDI) for collecting and archiving the CMIP5 multi-model data, and the Office of Science, US Department of Energy for supporting these datasets in partnership with the Global Organization for Earth System Science Portals.

Author information

Authors and Affiliations

  1. State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, Guangdong, 510301, China

    Gen Li & Zesheng Chen

  2. Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, 92093-0206, USA

    Shang-Ping Xie

  3. Physical Oceanography Laboratory/CIMST, Ocean University of China, and Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong, 266100, China

    Shang-Ping Xie

  4. Institute of Tropical and Marine Meteorology (ITMM), China Meteorological Administration (CMA), Guangzhou, Guangdong, 510640, China

    Chao He

Authors
  1. Gen Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shang-Ping Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chao He
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zesheng Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

G.L. designed the study and performed the analysis with feedback from S.-P.X. G.L. and S.-P.X. wrote the paper. C.H. and Z.C. carried out the CAM4 experiments.

Corresponding author

Correspondence to Gen Li.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Information (PDF 903 kb)

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, G., Xie, SP., He, C. et al. Western Pacific emergent constraint lowers projected increase in Indian summer monsoon rainfall. Nature Clim Change 7, 708–712 (2017). https://doi.org/10.1038/nclimate3387

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nclimate3387

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing