Skip to main content

Advertisement

Log in

Assessing impact of climate change on season length in Karnataka for IPCC SRES scenarios

  • Published:
Journal of Earth System Science Aims and scope Submit manuscript

Abstract

Changes in seasons and season length are an indicator, as well as an effect, of climate change. Seasonal change profoundly affects the balance of life in ecosystems and impacts essential human activities such as agriculture and irrigation. This study investigates the uncertainty of season length in Karnataka state, India, due to the choice of scenarios, season type and number of seasons. Based on the type of season, the monthly sequences of variables (predictors) were selected from datasets of NCEP and Canadian General Circulation Model (CGCM3). Seasonal stratifications were carried out on the selected predictors using K-means clustering technique. The results of cluster analysis revealed increase in average, wet season length in A2, A1B and B1 scenarios towards the end of 21st century. The increase in season length was higher for A2 scenario whereas it was the least for B1 scenario. COMMIT scenario did not show any change in season length. However, no change in average warm and cold season length was observed across the four scenarios considered. The number of seasons was increased from 2 to 5. The results of the analysis revealed that no distinct cluster could be obtained when the number of seasons was increased beyond three.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Alley R, Berntsen T, Bindoff N L, Chen Z, Chidthaisong A, Friedlingstein P, Gregory J, Hegerl G, Heimann M, Hewitson B, Hoskins B, Joos F, Jouzel J, Kattsov V, Lohmann U, Manning M, Matsuno T, Molina M, Nicholls N, Overpeck J, Qin D, Raga G, Ramaswamy V, Ren J, Rusticucci M, Solomon S, Somerville R, Stocker T F, Stott P, Stouffer R J, Whetton P, Wood R A and Wratt D 2007 Climate Change 2007: The Physical Science Basis. Summary for Policy makers; Report of the Intergovernmental Panel on Climate Change, Geneva, CH.

  • Anandhi A 2007 Impact assessment of climate change on hydrometeorology of Indian river basin for IPCC SRES scenarios; PhD thesis, Indian Institute of Science, India.

    Google Scholar 

  • Anandhi A, Srinivas V V, Nanjundiah R S and Kumar D N 2008 Downscaling precipitation to river basin in India for IPCC SRES scenarios using support vector machine; Int. J. Climatol. 28(3) 401–420.

    Article  Google Scholar 

  • Argiriou A A, Kassomenos P A and Lykoudis S P 2004 On the methods for the delimitation of seasons: Water, Air, and Soil Pollution; Focus 4 65–74.

    Google Scholar 

  • Chakraborty S, Tiedemann A V and Teng P S 2000 Climate change: Potential impact on plant diseases; Environmental Pollution 108 317–326.

    Article  Google Scholar 

  • Christidis N, Stott P A, Brown S, Karoly D J and Caesar J 2007 Human contribution to the lengthening of the growing season during 1950–99; J. Climate 20 5441–5454.

    Article  Google Scholar 

  • Cleugh H A, Miller J M and Böhm M 1998 Direct mechanical effects of wind on crops; Agroforestry Systems 41(1) 85–112, 10.1023/A:1006067721039.

    Article  Google Scholar 

  • Doty B and Kinter J L III 1993 The grid analysis and display system (GrADS): A desktop tool for earth science visualization; American Geophysical Union 1993 Fall Meeting, San Fransico, CA, 6–10 December.

  • Fix E and Hodges J L 1951 Discriminatory analysis: Nonparametric discrimination: Consistency properties; USAF School of Aviation Medicine, Project 21-49-004, Report 4.

  • Jones G S, Jones A, Roberts D L, Stott P A and Williams K D 2005 Sensitivity of global scale climate change attribution results to inclusion of fossil fuel black carbon aerosol; Geophys. Res. Lett. 32 L14701, doi: 10.1029/2005GL023370.

    Article  Google Scholar 

  • Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo K C, Ropelewski C, Wang J, Leetmaa A, Reynolds R, Jenne R and Joseph D 1996 The NCEP/NCAR 40-year reanalysis project; Bull. Amer. Meteor. Soc. 77(3) 437–471.

    Article  Google Scholar 

  • Kendall M G 1951 Regression structure and functional relationship, Part I; Biometrika 38 11–25.

    Google Scholar 

  • Kripalani R H, Oh J H, Kulkarni A, Sabade S S and Chaudhari H S 2007 South Asian summer monsoon precipitation variability: Coupled climate model simulations and projections under IPCC AR4; Theoretical and Applied Climatology 90 133–159.

    Article  Google Scholar 

  • Lamb H H 1972 British Isles weather types and a register of daily sequence of circulation patterns, 1861–1971; Geophysical Memoir 116 HMSO, London, pp. 85.

    Google Scholar 

  • Leach C 1979 Introduction to statistics: A nonparametric approach for the social sciences (New York: Wiley).

    Google Scholar 

  • MacQueen J 1967 Some methods for classification and analysis of multivariate observation; In: Proceedings of the fifth Berkeley Symposium on mathematical statistics and probability, (eds) Le Cam L M and Neyman J (Berkeley: University of California Press) 1 281–297.

    Google Scholar 

  • Nakicenovic N, Alcamo J, Davis G, de Vries B, Fenhann J, Gaffin S, Gregory K, Grübler A, Jung T Y, Kram T, La Rovere E L, Michaelis L, Mori S, Morita T, Pepper W, Pitcher H, Price L, Raihi K, Roehrl A, Rogner H H, Sankovski A, Schlesinger M, Shukla P, Smith S, Swart R, van Rooijen S, Victor N and Dadi Z 2000 IPCC Special report on emissions scenarios, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 599.

    Google Scholar 

  • Patterson D T, Westbrook J K, Joyce R J V, Lingren P D and Rogasik J 1999 Weeds, insects and diseases; Climatic Change 43 711–727.

    Article  Google Scholar 

  • Pearson K 1896 Mathematical contributions to the Theory of Evolution III Regression Heredity and Panmixia; Philosophical Transactions of the Royal Society of London Series 187 253–318.

    Article  Google Scholar 

  • Peng S, Huang J, Sheeshy J E, Laza R C, Visperas R M, Zhong X, Centeno G S, Khush G S and Cassman K G 2004 Rice yields decline with higher night temperature from global warming; Proceedings of National Academy of Science, USA 101 9971–9975.

    Article  Google Scholar 

  • Press W H, Teukolsky S A, Vetterling W T and Flannery B P 1992 Numerical recipes in Fortran 77: The art of scientific computing (New York: Cambridge University Press).

    Google Scholar 

  • Rajeevan M, Bhate J, Kale J D and Lal B 2005 Development of a high resolution daily gridded rainfall data for the Indian Region (version 2), Meteorol. Monogr. Climatol. 22/2005, India Meteorol. Dept., New Delhi.

    Google Scholar 

  • Rajeevan M, Bhate J, Kale J D and Lal B 2006 High resolution daily gridded rainfall data for the Indian region: Analysis of break and active monsoon spells; Curr. Sci. 91(3) 296–306.

    Google Scholar 

  • Rupa Kumar K, Sahai A K, Krishna Kumar K, Patwardhan S K, Mishra P K, Revadekar J V, Kamala K and Pant G B 2006 High-resolution climate change scenarios for India for the 21st century; Curr. Sci. 90 334–344.

    Google Scholar 

  • Sailor D J, Smith M and Hart M 2008 Climate change implications for wind power resources in the Northwest United States; Renewable Energy 33 2393–2406.

    Article  Google Scholar 

  • Spearman C E 1904a ’General intelligence’ objectively determined and measured; Am. J. Psychol. 5 201–293.

    Article  Google Scholar 

  • Spearman C E 1904b Proof and measurement of association between two things; Am. J. Psychol. 15 72–101.

    Article  Google Scholar 

  • Tripathi S, Srinivas V V and Nanjundiah R S 2006 Downscaling of precipitation for climate change scenarios: A support vector machine approach; J. Hydrol. 330 621–640, doi: 10.1016/j.jhydrol.2006.04.030.

    Article  Google Scholar 

  • Tuller S E 1990 Standard seasons; Int. J. Biomet. 34 181–188.

    Article  Google Scholar 

  • Winkler J A, Palutikof J P, Andresen J A and Goodess C M 1997 The simulation of daily temperature time series from GCM output Part II: Sensitivity analysis of an empirical transfer function methodology; J. Climate 10(10) 2514–2532.

    Article  Google Scholar 

  • Yadav R K, Rupa Kumar K and Rajeevan M 2007 Role of Indian Ocean sea surface temperatures in modulating northwest Indian winter precipitation variability; Theoretical and Applied Climatology 87 73–83, doi: 10.1007/s00704005-0221.

    Article  Google Scholar 

  • Yadav R K, Rupa Kumar K and Rajeevan M 2009a Increasing influence of ENSO and decreasing influence of AO/NAO in the recent decades over northwest India winter precipitation; J. Geophys. Res.-Atmos. 114 D12112, doi: 10.1029/2008JD011318.

    Article  Google Scholar 

  • Yadav R K, Rupa Kumar K and Rajeevan M 2009b Out-ofphase relationships between convection over north-west India and warm-pool region during winter season; Int. J. Climatol. 29 1330–1338, doi: 10.1002/joc.1783.

    Article  Google Scholar 

  • Yadav R K, Rupa Kumar K and Rajeevan M 2010a Climate change scenarios for northwest India winter season; Quaternary International 213 12–19.

    Article  Google Scholar 

  • Yadav R K, Yoo J H, Kucharski F and Abid M A 2010b Why is ENSO influencing northwest India winter precipitation in recent decades?; J. Climate (in press).

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Anandhi, A. Assessing impact of climate change on season length in Karnataka for IPCC SRES scenarios. J Earth Syst Sci 119, 447–460 (2010). https://doi.org/10.1007/s12040-010-0034-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12040-010-0034-5

Keywords

Navigation