SpringerLink
Log in

Analysis of the change in temperature trends in Subansiri River basin for RCP scenarios using CMIP5 datasets

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

This study focuses on changes in the maximum and minimum temperature over the Subansiri River basin for different climate change scenarios. For the study, dataset from Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5) (i.e., coupled model intercomparison project phase five (CMIP5) dataset with representative concentration pathway (RCP) scenarios) were utilized. Long-term (2011–2100) maximum temperature (T max) and minimum temperature (Tmin) time series were generated using the statistical downscaling technique for low emission scenario (RCP2.6), moderate emission scenario (RCP6.0), and extreme emission scenario (RCP8.5). Trends and change of magnitude in T max, T min, and diurnal temperature range (DTR) were analyzed for different interdecadal time scales (2011–2100, 2011–2040, 2041–2070, 2070–2100) using Mann-Kendall non-parametric test and Sen’s slope estimator, respectively. The temperature data series for the observed duration (1981–2000) has been found to show increasing trends in T max and T min at both annual and monthly scale. Trend analysis of downscaled temperature for the period 2011–2100 shows increase in annual maximum temperature and annual minimum temperature for all the selected RCP scenarios; however, on the monthly scale, T max and T min have been seen to have decreasing trends in some months.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Beniston M (2003) Climate change in mountain regions: a review of possible impacts. Climate Change 59:5–31

    Article  Google Scholar 

  • Bhave AG, Mittal N, Mishra A, Raghuwanshi NS (2015) Integrated assessment of no-regret climate change adaptation options for reservoir catchment and command Areas. Water Resour Manag 30:1001–1018

  • Bhutiyani MR, Kale VS, Pawar NJ (2007) Long-term trends in maximum, minimum and mean annual air temperatures across the Northwestern Himalaya during the twentieth century. Clim Chang 85(1–2):159–177

    Article  Google Scholar 

  • Dettinger MD, Cayan DR, Meyer MK, Jeton AE (2004) Simulated hydrologic responses to climate variations and change in the Merced, Carson, and American River basins, Sierra Nevada, California, 1900–2099. Clim Chang 62(1–3):283–317

    Article  Google Scholar 

  • Duhan D, Pandey A, Gahalaut KPS, Pandey RP (2013) Spatial and temporal variability in maximum, minimum and mean air temperatures at Madhya Pradesh in central India. Compt Rendus Geosci 345(1):3–21

    Article  Google Scholar 

  • Duhan D, Pandey A (2015) Statistical downscaling of temperature using three techniques in the Tons River basin in Central India. Theor Appl Climatol 121(3–4):605–622

    Article  Google Scholar 

  • Dunne JP, John JG, Adcroft AJ, Griffies SM, Hallberg RW, Shevliakova E, et al. (2012) GFDL’s ESM2 global coupled climate-carbon earth system models. Part I: physical formulation and baseline simulation characteristics. J Clim 25(19):6646–6665

    Article  Google Scholar 

  • Dunne JP, John JG, Shevliakova E, Stouffer RJ, Krasting JP, Malyshev SL, et al. (2013) GFDL’s ESM2 global coupled climate–carbon earth system models. Part II: carbon system formulation and baseline simulation characteristics. J Clim 26(7):2247–2267

    Article  Google Scholar 

  • Easterling DR, Horton B, Jones PD, Peterson TC, Karl TR, Parker DE, et al. (1997) Maximum and minimum temperature trends for the globe. Science 277(5324):364–367

    Article  Google Scholar 

  • Frey-Buness F, Heimann D, Sausen R (1995) A statistical-dynamical downscaling procedure for global climate simulations. Theor Appl Climatol 50(3–4):117–131

    Article  Google Scholar 

  • Goyal MK, Ojha CSP (2012) Downscaling of surface temperature for lake catchment in an arid region in India using linear multiple regression and neural networks. Int J Climatol 32(4):552–566

    Article  Google Scholar 

  • Goyal MK, Ojha CSP, Burn DH (2011) Nonparametric statistical downscaling of temperature, precipitation, and evaporation in a semiarid region in India. J Hydrol Eng 17(5):615–627

    Article  Google Scholar 

  • Grotch SL, MacCracken MC (1991) The use of general circulation models to predict regional climatic change. J Clim 4(3):286–303

    Article  Google Scholar 

  • IPCC (2007) Impacts, adaptation, and vulnerability: working group II contribution to the intergovernmental panel on climate change fourth assessment report, summary for policymakers. IPCC Secretariat Geneva 22 p

  • IPCC (2014) Synthesis report. Contribution of working groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC Geneva Switzerland 151 pp

  • Kalma JD, McVicar TR, McCabe MF (2008) Estimating land surface evaporation: a review of methods using remotely sensed surface temperature data. Surv Geophys 29(4–5):421–469

    Article  Google Scholar 

  • Karl TR, Knight RW, Gallo KP, Peterson TC, Jones PD, Kukla G, et al. (1993) A new perspective on recent global warming: asymmetric trends of daily maximum and minimum temperature. Bull Am Meteorol Soc 74(6):1007–1023

    Article  Google Scholar 

  • Kendall MG (1975) Rank correlation methods. Griffin, London

    Google Scholar 

  • Mahmood R, Babel MS (2013) 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(1–2):27–44

    Article  Google Scholar 

  • Mann HB (1945) Nonparametric tests against trend. Econometrica 13(3):245–259

    Article  Google Scholar 

  • Milly PC, Dunne KA, Vecchia AV (2005) Global pattern of trends in streamflow and water availability in a changing climate. Nature 438(7066):347–350

    Article  Google Scholar 

  • Mir RA, Jain SK, Saraf AK (2015) Analysis of current trends in climatic parameters and its effect on discharge of Satluj River basin, western Himalaya. Nat Hazards 79(1):587–619

    Article  Google Scholar 

  • Mondal A, Mujumdar PP (2012) On the basin-scale detection and attribution of human-induced climate change in monsoon precipitation and stream flow. Water Resour Res 48(10)

  • Mondal A, Khare D, Kundu S (2014) Spatial and temporal analysis of rainfall and temperature trend of India. Theor Appl Climatol 122(1–2):143–158

    Google Scholar 

  • Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, Van Vuuren DP, et al. (2010) The next generation of scenarios for climate change research and assessment. Nature 463(7282):747–756

    Article  Google Scholar 

  • Nash J, Sutcliffe JV (1970) River flow forecasting through conceptual models part I—a discussion of principles. J Hydrol 10(3):282–290

    Article  Google Scholar 

  • Prudhomme C, Jakob D, Svensson C (2003) Uncertainty and climate change impact on the flood regime of small UK catchments. J Hydrol 277(1):1–23

    Article  Google Scholar 

  • Robock A, Turco RP, Harwell MA, Ackerman TP, Andressen R, Chang HS, Sivakumar MVK (1993) Use of general circulation model output in the creation of climate change scenarios for impact analysis. Clim Chang 23(4):293–335

    Article  Google Scholar 

  • Roeckner E, Bäuml G, Bonaventura L, Brokopf R et al (2003) The atmospheric general circulation model ECHAM 5. PART I: model description, MPI-Report 349, Hamburg, Germany

  • Ryu D, Crow WT, Zhan X, Jackson TJ (2009) Correcting unintended perturbation biases in hydrologic data assimilation. J Hydrometeorol 10(3):734–750

    Article  Google Scholar 

  • Samadi S, Wilson CA, Moradkhani H (2013) Uncertainty analysis of statistical downscaling models using Hadley Centre Coupled Model. Theor Appl Climatol 114(3–4):673–690

    Article  Google Scholar 

  • Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 63(324):1379–1389

    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 H, Sinha T, Sankarasubramanian A (2014) Impacts of near-term climate change and population growth on within-year reservoir systems. J Water Resour Plan Manag 141(6):04014078

    Article  Google Scholar 

  • Singh V, Goyal MK (2016) Analysis and trends of precipitation lapse rate and extreme indices over north Sikkim eastern Himalayas under CMIP5ESM-2M RCPs experiments. Atmos Res 167:34–60

    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 

  • Sonali P, Kumar DN (2013) Review of trend detection methods and their application to detect temperature changes in India. J Hydrol 476:212–227

    Article  Google Scholar 

  • Stouffer RJ, Manabe S, Bryan K (1989) Interhemispheric asymmetry in climate response to a gradual increase of atmospheric C02. Nature 342:660–662

    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 

  • Watanabe S, Kanae S, Seto S, Yeh PJF, Hirabayashi Y, Oki T (2012) Inter-comparison of bias-correction methods for monthly temperature and precipitation simulated by multiple climate models. J Geophys Res Atmos 117(D23)

  • Wilby RL, Dawson CW, Barrow EM (2002) SDSM-a decision support tool for the assessment of regional climate change impacts. Environ Model Softw 17(2):145–157

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Civil Engineering, Indian Institute of Technology, Guwahati, Assam, 781039, India

    Shivam, Manish Kumar Goyal & Arup Kumar Sarma

Authors
  1. Shivam
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manish Kumar Goyal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Arup Kumar Sarma
    View author publications

    You can also search for this author in PubMed Google Scholar

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

Shivam, Goyal, M.K. & Sarma, A.K. Analysis of the change in temperature trends in Subansiri River basin for RCP scenarios using CMIP5 datasets. Theor Appl Climatol 129, 1175–1187 (2017). https://doi.org/10.1007/s00704-016-1842-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-016-1842-6

Keywords

Search

Navigation