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.

  • Letter
  • Published:

Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes

Abstract

Recent studies disagree on how rainfall extremes over India have changed in space and time over the past half century1,2,3,4, as well as on whether the changes observed are due to global warming5,6 or regional urbanization7. Although a uniform and consistent decrease in moderate rainfall has been reported1,3, a lack of agreement about trends in heavy rainfall may be due in part to differences in the characterization and spatial averaging of extremes. Here we use extreme value theory8,9,10,11,12,13,14,15 to examine trends in Indian rainfall over the past half century in the context of long-term, low-frequency variability. We show that when generalized extreme value theory8,16,17,18 is applied to annual maximum rainfall over India, no statistically significant spatially uniform trends are observed, in agreement with previous studies using different approaches2,3,4. Furthermore, our space–time regression analysis of the return levels points to increasing spatial variability of rainfall extremes over India. Our findings highlight the need for systematic examination of global versus regional drivers of trends in Indian rainfall extremes, and may help to inform flood hazard preparedness and water resource management in the region.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1: Spatiotemporal trends and variability in all-India monsoon rainfall (AIMR) with 30-year overlapping time windows.
Figure 2: Return periods and volatility of rainfall extremes in India and their 30-year moving trends.
Figure 3: Trends in spatial variance of rainfall extremes calculated with 30-year overlapping time windows.
Figure 4: Multi-metric examination of average and severe rainfall trends over Central India as defined in ref. 1 and over ‘all-India’.

Similar content being viewed by others

References

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

    Article  CAS  Google Scholar 

  2. Ghosh, S., Luniya, V. & Gupta, A. Trend analysis of Indian summer monsoon rainfall at different spatial scales. Atmos. Sci. Lett. 10, 285–290 (2009).

    Google Scholar 

  3. Dash, S. K., Kulkarni, M. A., Mohanty, U. C. & Prasad, K. Changes in the characteristics of rain events in India. J. Geophys. Res. 114, D10109 (2009).

    Article  Google Scholar 

  4. Krishnamurthy, C. K. B., Lall, U. & Kwon, H-H. Changing frequency and intensity of rainfall extremes over India from 1951 to 2003. J. Clim. 22, 4737–4746 (2009).

    Article  Google Scholar 

  5. Rajeevan, M., Bhate, J. & Jaswal, A. K. Analysis of variability and trends of extreme rainfall events over India using 104 years of gridded daily rainfall data. Geophys. Res. Lett. 35, L18707 (2008).

    Article  Google Scholar 

  6. Mani, N. J., Suhas, E. & Goswami, B. N. Can global warming make Indian monsoon weather less predictable? Geophys. Res. Lett. 36, L08811 (2009).

    Article  Google Scholar 

  7. Kishtawal, C. M., Niyogi, D., Tewari, M., Pielke, R. A. Sr. & Shepherd, J. M. Urbanization signature in the observed heavy rainfall climatology over India. Int. J. Clim. 30, 1908–1916 (2010).

    Article  Google Scholar 

  8. Coles, S. G. An Introduction to Statistical Modeling of Extreme Values (Springer, 2001).

    Book  Google Scholar 

  9. Katz, R. W. Stochastic modeling of hurricane damage. J. Appl. Meteorol. 41, 754–762 (2002).

    Article  Google Scholar 

  10. Khan, S., Kuhn, G., Ganguly, A. R., Erickson, D. J. III & Ostrouchov, G. Spatio-temporal variability of daily and weekly precipitation extremes in South America. Water Resour. Res 43, W11424 (2007).

    Article  Google Scholar 

  11. Katz, R. W. Extreme value theory for precipitation: Sensitivity analysis for climate change. Adv. Water Resour. 23, 133–139 (1999).

    Article  Google Scholar 

  12. Kuhn, G., Khan, S., Ganguly, A. R. & Branstetter, M. Geospatial-temporal dependence among weekly precipitation extremes with applications to observations and climate model simulations in South America. Adv. Water Resour. 30, 2401–2423 (2007).

    Google Scholar 

  13. Koutsoyiannis, D., Kozonis, D. & Manetas, A. A mathematical framework for studying rainfall intensity-duration-frequency relationships. J. Hydrol. 206, 118–135 (1998).

    Article  Google Scholar 

  14. Willems, P. Compound IDF-relationships of extreme precipitation for two seasons and two storm types. J. Hydrol. 233, 189–205 (2000).

    Article  Google Scholar 

  15. Sivapalan, M. & Bloschl, G. Transformation of point rainfall to areal rainfall: Intensity-duration-frequency curves. J. Hydrol. 204, 150–167 (1998).

    Article  Google Scholar 

  16. Mannshardt-Shamseldin, E. C., Smith, R. L., Sain, S. R., Mearns, L. O. & Cooley, D. Downscaling extremes: A comparison of extreme value distributions in point-source and gridded precipitation data. Ann. Appl. Stat. 4, 484–502 (2010).

    Article  Google Scholar 

  17. Kharin, V. V., Zwiers, F. W., Zhang, X. & Hegerl, G. C. Changes of extremes in IPCC simulations. J. Clim. 20, 1419–1444 (2007).

    Article  Google Scholar 

  18. Wehner, M. Sources of uncertainty in the extreme value statistics of climate data. Extremes 13, 205–217 (2010).

    Article  Google Scholar 

  19. Satyanarayana, P. & Srinivas, V. V. Regional frequency analysis of precipitation using large-scale atmospheric variables. J. Geophys. Res. 113, D24110 (2008).

    Article  Google Scholar 

  20. Min, S-K., Zhang, X., Zwiers, F. W. & Hegerl, G. C. Human contribution to more-intense precipitation extremes. Nature 470, 378–381 (2011).

    Article  CAS  Google Scholar 

  21. Kao, S-C. & Ganguly, A. R. Intensity, duration, and frequency of precipitation extremes under 21st-century warming scenarios. J. Geophys. Res. 116, D16119 (2011).

    Article  Google Scholar 

  22. Rajeevan, M., Bhate, J., Kale, J. D. & Lal, B. High resolution daily gridded rainfall data for the Indian region: Analysis of break and active monsoon spells. Curr. Sci. 91, 296–306 (2006).

    Google Scholar 

  23. Kucharski, F. et al. The CLIVAR C20C project: Skill of simulating Indian monsoon rainfall on interannual to decadal timescales. Does GHG forcing play a role? Clim. Dynam. 33, 615–627 (2009).

    Article  Google Scholar 

  24. Kharin, V. V. & Zwiers, F. W. Estimating extremes in transient climate change simulations. J. Clim. 18, 1156–1173 (2005).

    Article  Google Scholar 

  25. O’Gorman, P. A. & Schneider, T. The physical basis for increases in precipitation extremes in simulations of 21st-century climate change. Proc. Natl Acad. Sci. USA 106, 14773–14777 (2009).

    Article  Google Scholar 

  26. Sugiyama, M., Shiogama, H. & Emori, S. Precipitation extreme changes exceeding moisture content increases in MIROC and IPCC climate models. Proc. Natl Acad. Sci. USA 107, 571–575 (2010).

    Article  CAS  Google Scholar 

  27. Rajagopalan, B. et al. Water supply risk on the Colorado River: Can management mitigate? Water Resour. Res. 45, W08201 (2009).

    Article  Google Scholar 

  28. Shepherd, J. M. A review of current investigations of urban-induced rainfall and recommendations for the future. Earth Interact. 9, 1–27 (2005).

    Article  Google Scholar 

  29. Ntelekos, A. A. et al. Extreme hydrometeorological events and the urban environment: Dissecting the 7 July 2004 thunderstorm over the Baltimore MD Metropolitan Region. Water Resour. Res. 44, W08446 (2008).

    Article  Google Scholar 

  30. Ntelekos, A. A., Oppenheimer, M., Smith, J. A. & Miller, A. J. Urbanization, climate change and flood policy in the United States. Climatic Change 103, 597–616 (2010).

    Article  Google Scholar 

Download references

Acknowledgements

The research was mostly completed when all authors were at Oak Ridge National Laboratory (ORNL) and financially supported by the ORNL (managed by UT-Battelle for US Department of Energy) Laboratory Directed Research and Development programme, National Science Foundation award 1029166, and BOYCAST fellowship of DST-India. E. Kodra and J. Tolen provided helpful comments.

Author information

Authors and Affiliations

Authors

Contributions

S.G. developed codes and performed the analysis, apart from EVT. D.D. performed the EVT analysis and S-C.K. and D.D. developed the EVT codes. S.G. and A.R.G. designed the problem and interpreted the analysis results. A.R.G. wrote the paper, primarily with inputs from S.G., as well as with comments from D.D. and S-C.K.

Corresponding author

Correspondence to Auroop R. Ganguly.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Information (PDF 1946 kb)

Supplementary Information

Supplementary Information (ZIP 731 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ghosh, S., Das, D., Kao, SC. et al. Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes. Nature Clim Change 2, 86–91 (2012). https://doi.org/10.1038/nclimate1327

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nclimate1327

This article is cited by

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