Skip to main content
Log in

Changes in climate extremes by the use of CMIP5 coupled climate models over eastern Himalayas

  • Original Article
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

Abstract

A great deal of attention has been given to analyze the trends in Himalayan climate changes due to its reflection in local and global climate variability. To study the same, the two significant meteorological parameters such as temperature and precipitation have been downscaled at various locations over the Eastern Himalayas. For the downscaling, the latest Coupled Model Intercomparison Project 5 climate models with Representative Concentration Pathways experiments were utilized. In this article, we have basically emphasized on the temperature extremity in the historical/measured (1979–2005) and twenty-first century projected (2006–2100) time series durations. The precipitation extreme indices have been computed to correlate the effect of temperature extremes. The results showed that there were substantial variations in these two factors, in terms of their rates, intensities and frequencies in intra-decadal (1979–2005, 2006–2030, 2041–2065 and 2076–2100) time durations. A multi-model climatic projection showed a significant increment in the average annual temperature rate across all the climate stations. Analysis results showed that over the period of records: (1) a diurnal variation of temperature is decreasing due to increments in the minimum temperature, especially after the 2030s; (2) extreme indices-based results showed that the frequencies increase for the summer days and tropical nights but decrease for the frost days. Likewise the intensities of warmest nights also increase; (3) a significant geographical heterogeneity was observed in the temperature as per the results from the multi-model projected temperature datasets; and (4) indeed, there were noticeable areas where these datasets differed on both the sign and significance of precipitation and temperature trends.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+
from €39.99 /Month
  • Starting from 10 chapters or articles per month
  • Access and download chapters and articles from more than 300k books and 2,500 journals
  • Cancel anytime
View plans

Buy Now

Price includes VAT (Germany)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Ahmad NH, Deni SM (2013) Homogeneity test on daily rainfall series for Malaysia. Matematika 29(1c):141–150

    Google Scholar 

  • Ahmed KF, Wang G, Silander J, Wilson AM, Allen JM, Horton R, Anyah R (2013) Statistical downscaling and bias correction of climate model outputs for climate change impact assessment in the US northeast. Glob Planet Change 100:320–332

    Article  Google Scholar 

  • Alexandersson H (1986) A homogeneity test applied to precipitation data. J Climatol 6:661–675

    Article  Google Scholar 

  • Arora VK, Boer GJ, Friedlingstein P, Eby M, Jones CD, Christian JR, Wu T (2013) Carbon–concentration and carbon–climate feedbacks in CMIP5 Earth system models. J Clim 26(15):5289–5314

    Article  Google Scholar 

  • Bhutiyani MR (2015) Climate change in the Northwestern Himalayas. In: Joshi R, Kumar K, Lok Man PS (eds) Dynamics of climate change and water resources of Northwestern Himalaya. Springer International Publishing, Switzerland, pp 85–96

  • Buishand TA (1982) Some methods for testing the homogeneity of rainfall records. J Hydrol 58:11–27

    Article  Google Scholar 

  • Chaturvedi RK, Kulkarni A, Karyakarte Y, Joshi J, Bala G (2014) Glacial mass balance changes in the Karakoram and Himalaya based on CMIP5 multi-model climate projections. Clim Change 123(2):315–328

    Article  Google Scholar 

  • Choi W, Tareghian R, Choi J, Hwang CS (2014) Geographically heterogeneous temporal trends of extreme precipitation in Wisconsin, USA during 1950–2006. Int J Climatol 34:2841–2852. doi:10.1002/joc.3878

    Google Scholar 

  • Dickey DA, Fuller WA (1979) Distribution of the estimators for autoregressive time series with a unit root. J Am Stat Assoc 74:427–431

    Google Scholar 

  • Escurra JJ, Vazquez V, Cestti R, De Nys E, Srinivasan R (2014) Climate change impact on countrywide water balance in Bolivia. Reg Environ Change 14(2):727–742

    Article  Google Scholar 

  • Gardner AS, Sharp MJ, Koerner RM, Labine C, Boon S, Marshall SJ, Lewis D (2009) Near-surface temperature lapse rates over Arctic glaciers and their implications for temperature downscaling. J Clim 22:4281–4298

    Article  Google Scholar 

  • Goyal MK (2014) Statistical analysis of long term trends of rainfall during 1901–2002 at Assam, India. Water Resour Manag 28(6):1501–1515

    Article  Google Scholar 

  • Goyal MK, Ojha CSP (2011) Evaluation of linear regression methods as downscaling tool in temperature projections over Pichola Lake Basin in India. Hydrol Process 25(9):1453–1465

    Article  Google Scholar 

  • Guan Y, Zhang X, Zheng F, Wang B (2015) Trends and variability of daily temperature extremes during 1960–2012 in the Yangtze River Basin, China. Glob Planet Change 124:79–94

    Article  Google Scholar 

  • Hansel S, Dong W, Ren F, Huang J, Guo Y (2013) The atlas of climate change: based on SEAP-CMIP5. Environ Earth Sci 69(8):2799

    Article  Google Scholar 

  • Harpham C, Wilby RL (2005) Multi-site downscaling of heavy daily precipitation occurrence and amounts. J Hydrol 312:235–255

    Article  Google Scholar 

  • Hewitt K (2011) Glacier change, concentration, and elevation effects in the Karakoram Himalaya, Upper Indus Basin. Mt Res Dev 31:188–200. doi:10.1659/MRD-JOURNAL-D-11-00020.1

    Article  Google Scholar 

  • IPCC (2013) Climate change 2013: the physical science basis. In: Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and NY, USA, p 1535. doi:10.1017/CBO9781107415324

  • Jain SK, Kumar V (2012) Trend analysis of rainfall and temperature data for India. Curr Sci 102(1):37–49

    Google Scholar 

  • Jarosch AH, Anslow FS, Clarke GK (2012) High-resolution precipitation and temperature downscaling for glacier models. Clim Dyn 38(1–2):391–409

    Article  Google Scholar 

  • Kang HM, Fadhilah Y (2012) Homogeneity tests on daily rainfall series in Peninsular Malaysia. Int J Contemp Math Sci 7(1):9–22

    Google Scholar 

  • Kar KK, Yang SK, Lee JH (2015) Assessing unit hydrograph parameters and peak runoff responses from storm rainfall events: a case study in Hancheon Basin of Jeju Island. J Environ Sci Int 24(4):437–447

    Article  Google Scholar 

  • Kendall MG (1975) Rank correlation methods, 4th edn. Charles Griffin, London, p 202

    Google Scholar 

  • Kharin VV, Zwiers FW, Zhang X, Wehner M (2013) Changes in temperature and precipitation extremes in the CMIP5 ensemble. Clim Change 119(2):345–357

    Article  Google Scholar 

  • Kulkarni MA, Singh A, Mohanty U (2012) Effect of spatial correlation on regional trends in rain events over India. Theor Appl Climatol 109(3–4):497–505

    Article  Google Scholar 

  • Lu GY, Wong DW (2008) An adaptive inverse-distance weighting spatial interpolation technique. Comput Geosci 34:1044–1055

    Article  Google Scholar 

  • Mahmood R, Babel MS (2012) Evaluation of SDSM developed by annual and monthly sub-models for downscaling temperature and precipitation in the Jhelum basin, Pakistan and India. Theor Appl Climatol 113:27–44

    Article  Google Scholar 

  • Mann HB (1945) Non-parametric test against trend. Econometrica 13:245–259

    Article  Google Scholar 

  • Mondal A, Khare D, Kundu S (2014) Spatial and temporal analysis of rainfall and temperature trend of India. Theor Appl Climatol 122(1):143–158

    Google Scholar 

  • Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2011) SWAT theoretical documentation version 2011. Grassland, Soil and Water Research Laboratory, Agricultural Research Service, Temple, Texas, USA

    Google Scholar 

  • Oliveira PTS, Nearing MA, Moran MS, Goodrich DC, Wendland E, Gupta HV (2014) Trends in water balance components across the Brazilian Cerrado. Water Resour Res 50:7100–7114

    Article  Google Scholar 

  • Palazzi E, von Hardenberg J, Terzago S, Provenzale A (2014) Precipitation in the Karakoram-Himalaya: a CMIP5 view. Clim Dyn 45(1):21–45

    Google Scholar 

  • Pettitt AN (1979) A non-parametric approach to the change-point problem. Appl Stat 28(2):126–135

    Article  Google Scholar 

  • Racoviteanu AE, Arnaud Y, Baghuna IM, Bajracharya SR, Berthier E, Bhambri R, Sossna I (2014) Himalayan Glaciers (India, Bhutan, and Nepal): satellite observations of thinning and retreat. Global land ice measurements from space. Springer, Berlin, pp 549–582

    Google Scholar 

  • Rangwala I, Miller JR (2012) Climate change in mountains: a review of elevation-dependent warming and its possible causes. Clim Change 114(3–4):527–547

    Article  Google Scholar 

  • Rangwala I, Miller J, Xu M (2009) Warming in the Tibetan Plateau: possible influences of the changes in surface water vapor. Geophys Res Lett 36:L06703

    Article  Google Scholar 

  • Shrestha AB, Wake CP, Mayewski PA, Dibb JE (1999) Maximum temperature trends in the Himalaya and its vicinity: an analysis based on temperature records from Nepal for the period 1971–94. J Clim 12(9):2775–2786

    Article  Google Scholar 

  • Singh V, Goyal Manish Kumar (2016) Analysis and trends of precipitation lapse rate and extreme indices over north Sikkim eastern Himalayas under CMIP5ESM2-M RCPs experiments. Atmos Res 167:34–60

    Article  Google Scholar 

  • Snell SE (1998) Spatial interpolation of surface air temperatures using artificial neural networks: evaluating their use for downscaling GCMs. J Clim 13:886–895

    Article  Google Scholar 

  • Snell SE, Gopal S, Kaufmann RK (2000) Spatial interpolation of surface air temperatures using artificial neural networks: evaluating their use for downscaling GCMs. J Clim 13:886–895

    Article  Google Scholar 

  • Subash N, Sikka AK (2014) Trend analysis of rainfall and temperature and its relationship over India. Theor Appl Climatol 117(3–4):449–462

    Article  Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93(4):485–498

    Article  Google Scholar 

  • Vittal H, Karmakar S, Ghosh S (2013) Diametric changes in trends and patterns of extreme rainfall over India from pre-1950 to post-1950. Geophys Res Lett 40:3253–3258

    Article  Google Scholar 

  • Wagholikar NK, Ray KS, Sen PN, Kumar PP (2014) Trends in seasonal temperatures over the Indian region. J Earth Syst Sci 123(4):673–687

    Article  Google Scholar 

  • Wilby RL, Dawson CW (2013) Statistical downscaling model–decision centric (SDSM-DC) version 5.1 supplementary note. Loughborough University, Loughborough

  • Wilby RL, Dawson CW, Murphy C, O’Connor P, Hawkins E (2014) The Statistical DownScaling Model-Decision Centric (SDSM-DC): conceptual basis and applications. Clim Res 61:259–276

    Article  Google Scholar 

  • Zhang X, Tang Q, Zhang X, Lettenmaier DP (2014) Runoff sensitivity to global mean temperature change in the CMIP5 Models. Geophys Res Lett 41:5492–5498

    Article  Google Scholar 

Download references

Acknowledgments

This present research work has been carried out under DST research project entitled “An integrated approach for snowmelt hydrological modeling at downstream of Sikkim glaciers” No. SB/DGH-66/2013 and financial support is gratefully acknowledged. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP5, and we thank the Geophysical Fluid Dynamics Laboratory, NJ, USA, for providing the CMIP5 Climate Model datasets.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Manish Kumar Goyal.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Singh, V., Goyal, M.K. Changes in climate extremes by the use of CMIP5 coupled climate models over eastern Himalayas. Environ Earth Sci 75, 839 (2016). https://doi.org/10.1007/s12665-016-5651-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12665-016-5651-0

Keywords