Advertisement

Assessment of present and future climate change over Kashmir Himalayas, India

  • Mifta ul Shafiq
  • Shazia Ramzan
  • Pervez AhmedEmail author
  • Rashid Mahmood
  • A. P. Dimri
Original Paper

Abstract

Climate change over mountainous basins necessitates thorough understanding of present and future temperature and precipitation regimes for better water resource management, cryospheric resources, hydropower generation, natural hazard risk assessment, and ecosystem response. Global and regional climate models (GCMs/RCMs) do not represent valley/ridge scale interactions well. There are inherent model biases due to coarser reorientation of model forcings. The present study is an attempt to use the statistical downscaling model (SDSM) to calibrate and validate Canadian Earth System Model (CanESM2) outputs. The outputs have been compared with corresponding in situ observations available at six meteorological stations within the Kashmir basin in western Himalayas. Daily temperatures and precipitation records during present and future time slices have been considered. The three Representative Concentration Pathways (RCPs) were divided into three future time slices of 2030s, 2060s, and 2090s. Downscaled climate data reveals increase of the mean maximum temperature in the range of 0.3–2.3 °C and the mean minimum temperature increase from 0.3–1.9 °C under different RCPs when compared with the baseline period of 1980–2010. An increasing trend from 2 to 17% at different meteorological stations under different RCPs has been observed in precipitation. Seasonally, autumn shows the highest variability both in temperature and precipitation followed by spring.

Notes

Acknowledgments

The acknowledgements are due to the Indian Meteorological Department (IMD), Srinagar, and National Data Centre, Pune, for necessary meteorological data. The authors would like to thank the developers of CanESM2 GCM and Canadian Centre for Climate Modelling and Analysis (CCCma) for keeping the model data in public domain. Thanks are also to the anonymous reviewers and editor of the journal for their valuable suggestions and insightful comments. The authors appreciate the help provided by Dr. Musavir Ahmad, Assistant Professor at the Department of Linguistics, University of Kashmir, for English language corrections.

Funding information

The first author received financial support from the University Grants Commission, New Delhi, in the form of UGC-NETJRF fellowship scheme. Pervez received financial support from the MOES & NCAOR under HiCOM initiative. AP Dimri received financial support from the MoEF&CC under NMHS.

References

  1. Akhtar M, Ahmad N, Booij MJ (2008) The impact of climate change on the water resources of Hindukush–Karakorum–Himalaya region under different glacier coverage scenarios. J Hydrol 355(1–4):148–163.  https://doi.org/10.1016/j.jhydrol.2008.03.015 Google Scholar
  2. Akhtar M, Ahmad N, Booij M.J. (2009) Use of regional climate model simulations as input for hydrological models for the Hindukush-Karakorum-Himalaya region. Hydrol Earth Syst Sci 13, 1075–1089Google Scholar
  3. Anandhi A, Srinivas VV, Nanjundiah RS, Nagesh Kumar D (2007) Downscaling precipitation to river basin in India for IPCC SRES scenarios using support vector machine. Int J Climatol 28:401–420.  https://doi.org/10.1002/joc.1529 Google Scholar
  4. Arora VK, Scinocca JF, Boer GJ, Christian JR, Denman KL, Flato GM, Kharin VV, Lee WG, Merryfield WJ (2011) Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases. Geophys Res Lett 38(5):3–8.  https://doi.org/10.1029/2010GL046270. Google Scholar
  5. Ashiq M, Zhao C, Ni J, Akhtar M (2010) GIS-based high-resolution spatial interpolation of precipitation in mountain–plain areas of Upper Pakistan for regional climate change impact studies. Theor Appl Climatol 99(3):239–253.  https://doi.org/10.1007/s00704-009-0140-y Google Scholar
  6. Beniston M (2003) Climatic change in mountainous regions: a review of possible impacts. Clim Chang 59:5–31Google Scholar
  7. Beniston M, Diaz FD, Bradley RS (1997) Climatic change at high elevation sites: an overview. Clim Chang 36:233–251Google Scholar
  8. Bhutiyani MR, Kale VS, Pawar NJ (2010) Climate change and the precipitation variations in the northwestern Himalaya: 1866–2006. Int J Climatol 30:535–548Google Scholar
  9. Chu J, Xia J, Xu CY, Singh V (2010) Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, China. Theor Appl Climatol 99(1):149–161.  https://doi.org/10.1007/s00704-009-0129-6 Google Scholar
  10. Costa AC, Soares A (2009) Homogenization of climate data: review and new perspectives using geostatistics. Math Geosci 41(3):291–305.  https://doi.org/10.1007/s11004-008-9203-3 Google Scholar
  11. Diaz-Nieto J, Wilby RL (2005) A comparison of statistical downscaling and climate change factor methods: impacts on low flows in the River Thames, United Kingdom. Clim Chang 69(2):245–268.  https://doi.org/10.1007/s10584-005-1157-6 Google Scholar
  12. Dimri AP, Dash SK (2012) Wintertime climatic trends in the western Himalayas. Clim Chang 111(3–4):775–800.  https://doi.org/10.1007/s10584-011-0201-y Google Scholar
  13. Dimri AP, Kumar D, Choudhary A, Maharana P (2018a) Future changes over the Himalayas: maximum and minimum temperature. Glob Planet Chang 162:212–234Google Scholar
  14. Dimri AP, Kumar D, Choudhary A, Maharana P (2018b) Future changes over the Himalayas: mean temperature. Glob Planet Chang 162(2018):235–251Google Scholar
  15. Dimri AP, Thayyen RJ, Kibler K, Stanton A, Tullos D, Singh VP (2016) A review of atmospheric and land surface processes with emphasis on flood generation along the southern rim of the Himalayas. Sci Total Environ 556:98–115Google Scholar
  16. Fowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int J Climatol 27(12):1547–1578.  https://doi.org/10.1002/joc.1556 Google Scholar
  17. Fyfe JC, Flato GM (1999) Enhanced climate change and its detection over the Rocky Mountains. J Clim 12(1):230–243Google Scholar
  18. Gagnon S, Singh B, Rousselle J, Roy L (2005) An application of the statistical downscaling model (SDSM) to simulate climatic data for streamflow modelling in Québec. Can Water Res J 30(4):297–314.  https://doi.org/10.4296/cwrj3004297 Google Scholar
  19. Gebremeskel S, Liu YB, deSmedt F, Hoffmann L, Pfister L (2005) Analysing the effect of climate changes on stream flow using statistically downscaled GCM scenarios. Int J River Basin Manag 2(4):271–280.  https://doi.org/10.1080/15715124.2004.9635237 Google Scholar
  20. Ghosh S, Mujumdar P (2008) Statistical downscaling of GCM simulations to stream flow using relevance vector machine. Water Res 31:132–146Google Scholar
  21. Giorgi F, Coppola E, Solmon F, Mariotti L, Sylla MB, Bi X, Elguindi N, Diro GT, Nair V, Giuliani G, Turuncoglu UU, Cozzini S, Güttler I, O’Brien TA, Tawfik AB, Shalaby A, Zakey AS, Steiner AL, Stordal F, Sloan LC, Brankovic C (2012) RegCM4: model description and preliminary tests over multipleCORDEX domains. Clim Res 52:7–29Google Scholar
  22. Goyal MK, Ojha CSP (2010) Robust weighted regression as a downscaling tool in temperature projections. Int J Glob Warm 2(3):234–251.  https://doi.org/10.1504/IJGW.2010.036135 Google Scholar
  23. Hashmi MZ, Shamseldin AY, Melville BW (2011) Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed. Stoch Env Res Risk A 25(4):475–484.  https://doi.org/10.1007/s00477-010-0416-x Google Scholar
  24. Hay LE, Wilby RL, Leavesley GH (2000) A comparison of delta change and downscaled GCM scenarios for three mountainous basins in the United States. J Am Water Resour Assoc 36(2):387–397.  https://doi.org/10.1111/j.1752-1688 Google Scholar
  25. Huang J, Zhang J, Zhang Z, Xu C, Wang B, Yao J (2011) Estimation of future precipitation change in the Yangtze River basin by using statistical downscaling method. Stoch Env Res Risk A 25(6):781–792.  https://doi.org/10.1007/s00477-010-0441-9 Google Scholar
  26. IPCC (2007) Climate change 2007: the physical science basis contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. In: Solomon S, Qin D, Manning M, Marquis M, Averyt K, Tignor MM, Miller HL (eds). Cambridge University Press, Cambridge and New York, p 996Google Scholar
  27. IPCC (2013) Climate change 2013: the physical science basis contribution of working group I to the fifth assessment report of the Intergovernmental Panel on Climate Change. In: Stocker TF, Qin D, Plattner GK, Tignor MM, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) . Cambridge University Press, Cambridge and New York, p 1535Google Scholar
  28. Jacobusse G (2005) WinMICE User’s manual. TNO Quality of Life. Available at https://www.ethologie.nl/gertjacobusse/. Accessed 15 Mar 2018
  29. Khadka D, Pathak D (2016) Climate change projection for the marsyangdi river basin, Nepal using statistical downscaling of GCM and its implications in geodisasters. Geo Disas 3:15.  https://doi.org/10.1186/s40677-016-0050-0 Google Scholar
  30. Lau WK, Kim MK, Kim KM, Lee WS (2010) Enhanced surface warming and accelerated snow melt in the Himalayas and Tibetan Plateau induced by absorbing aerosols. Environ Res Lett 5(2):025204Google Scholar
  31. Liu X, Cheng Z, Yan L, Yin ZY (2009a) Elevation dependency of recent and future minimum surface air temperature trends in the Tibetan Plateau and its surroundings. Glob Planet Chang 68(3):164–174Google Scholar
  32. Liu J, Williams JR, Wang X, Yang H (2009b) Using MODAWEC to generate daily weather data for the EPIC model. Environ Model Softw 24(5):655–664.  https://doi.org/10.1016/j.envsoft.2008.10.008 Google Scholar
  33. Lu A, Kang S, Li Z, Theakstone WH (2010) Altitude effects of climatic variation on Tibetan Plateau and its vicinities. J Earth Sci 21(2):189–198Google Scholar
  34. Mahmood R, Babel M (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 1–18.  https://doi.org/10.1007/s00704-012-07650
  35. 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):27–44Google Scholar
  36. Mahmood R, Babel MS, Jia S (2015) Assessment of temporal and spatial changes of future climate in the Jhelum river basin, Pakistan and India. Weather Clim Extrem 10:40–55.  https://doi.org/10.1016/j.wace.2015.07.002 Google Scholar
  37. Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, van Vuuren DP, Carter TR, Emori S, Kainuma M, Kram T, Meeh GA, Mitchel JFB, Nakicenovic N, Riahi K, Smith SJ, Stouffer RJ, Thomson AM, Weyant JP, Silbanks TJ (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–756.  https://doi.org/10.1038/nature08823 Google Scholar
  38. MoSTE (2014) Nepal climate change program (CCP) results management framework (RMF) 2013–2020 ministry of science, technology and environment. Available at http://ppcr3mis.moste.gov.np/file/RMF%20Doc.pdf. Accessed 21 Apr 2018
  39. Mujumdar P, Ghosh S (2008) Modeling GCM and scenario uncertainty using a possibilistic approach: application to the Mahanadi River, India. Water Resour Res 44:W06407–W06401Google Scholar
  40. Naud CM, Miller JR, Landry C (2012) Using satellites to investigate the sensitivity of longwave downward radiation to water vapor at high elevations. J Geophys Res Atmos 117(D5) D05101.  https://doi.org/10.1029/2011JD016917
  41. Nguyen V (2005) Downscaling methods for evaluating the impacts of climate change and variability on hydrological regime at basin scale. In: Proceedings of the International Symposium on Role of Water Sciences in Transboundary River Basin Management. Thailand, pp 1–8Google Scholar
  42. Opitz-Stapleton S, Gangopadhyay S (2010) A non-parametric, statistical downscaling algorithm applied to the Rohini River Basin, Nepal. Theor Appl Climatol 103(3–4):375–386.  https://doi.org/10.1007/s00704-010-0301-z Google Scholar
  43. Pepin N, Losleben M (2002) Climate change in the Colorado Rocky Mountains: free air versus surface temperature trends. Int J Climatol 22(3):311–329Google Scholar
  44. Peterson TC, Easterling DR, Karl TR, Groisman PY, Nicholis N, Plummer N, Torok S, Auer I, Boehm R, Gullett D, Vincent L, Heino R, Tuomenvirta H, Mestre O, Szentimrey T, Salinger J, Førland E, Hanssen-Bauer I, Alexandersson H, Jones P, Parker D (1998) Homogeneity adjustments of in situ atmospheric climate data: a review. Int J Climatol 18(13):1493–1517.  https://doi.org/10.1002/(SICI)1097-0088(19981115)18:13<1493:AID-JOC329>3.0.CO;2-T
  45. Qin J, Yang K, Liang S, Guo X (2009) The altitudinal dependence of recent rapid warming over the Tibetan Plateau. Clim Chang 97(1):321–327Google Scholar
  46. Rangwala I, Miller JR, Russell GL, Xu M (2010) Using a global climate model to evaluate the influences of water vapor, snow cover and atmospheric aerosol on warming in the Tibetan Plateau during the twenty-first century. Clim Dyn 34(6):859–872Google Scholar
  47. Rangwala I, Sinsky E, Miller JR (2013) Amplified warming projections for high altitude regions of the northern hemisphere mid-latitudes from CMIP5 models. Environ Res Lett 8(2):024040Google Scholar
  48. Rashid I, Romshoo SA, Chaturvedi RK, Ravindranath NH, Sukumar R, Jayaraman M, Lakshmi TV, Sharma J (2015) Projected climate change impacts on vegetation distribution over Kashmir Himalayas. Clim Chang 132:601–613.  https://doi.org/10.1007/s10584-015-1456-5 Google Scholar
  49. Rees HG, Collins DN (2006) Regional differences in response of flow in glacier-fid Himalayan rivers to climatic warming. Hydrol Process 20(10):2157–2169Google Scholar
  50. Salzen KV, Scinocca JF, McFarlane NA, Li J, Cole JN, Plummer D, Verseghy D, Reader MC, Ma X, Lazare M, Solheim L et al (2013) The Canadian fourth generation atmospheric global climate model (CanAM4) part I: representation of physical processes. Atmosphere-Ocean 51(1):104–125.  https://doi.org/10.1080/07055900.2012.755610
  51. Shafiq MU, Bhat MS, Rasool R, Ahmed P, Singh H, Hassan H (2016) Variability of Precipitation regime in Ladakh region of India from 1901-2000. J Climatol Weather Forecast 4:2.  https://doi.org/10.4172/2332-2594.1000165 Google Scholar
  52. Shafiq MU, Ahmed P, Ahmad AM, Hassan H (2018a) Trend analysis of winter precipitation over Kashmir valley from 1980 – 2016. IJARSE 07(04). Available at http://www.ijarse.com/images/fullpdf/1524850486_Jk1786IJARSE.pdf. Accessed 8 May 2018
  53. Shafiq MU, Ahmed P, Islam ZU, Joshi PK, Bhat WA (2018b) Snow cover area change and its relations with climatic variability in Kashmir Himalayas, India. Geocarto Int 1–15.  https://doi.org/10.1080/10106049.2018.1469675
  54. Shafiq MU, Rasool R, Ahmed P, Dimri AP (2018c) Temperature and Precipitation trends in Kashmir valley, North Western Himalayas. Theor Appl Climatol 1–12.  https://doi.org/10.1007/s00704-018-2377-9
  55. Souvignet M, Heinrich J (2011) Statistical downscaling in the arid central Andes: uncertainty analysis of multi-model simulated temperature and precipitation. Theor Appl Climatol 106(1–2):229–244.  https://doi.org/10.1007/s00704-011-0430-z Google Scholar
  56. Sun B, Groisman PY, Bradley RS, Keimig FT (2000) Temporal changes in the observed relationship between cloud cover and surface air temperature. J Clim 13(24):4341–4357Google Scholar
  57. Tabari H, Somee BS, Zadeh MR (2011) Testing for long-term trends in climatic variables in Iran. Atmos Res 100(1):132–140.  https://doi.org/10.1016/j.atmosres.2011.01.005 Google Scholar
  58. Teutschbein C, Seibert J (2012) Bias correction of regional climate model simulations for hydrological climate-change impact studies: review and evaluation of different methods. J Hydrol 456–457:12–29.  https://doi.org/10.1016/j.jhydrol.2012.05.052 Google Scholar
  59. Tripathi S, Srinivas VV, Nanjundiah RS (2006) Downscaling of precipitation for climate change scenarios: a support vector machine approach. J Hydrol 330(3–4):621–640.  https://doi.org/10.1016/j.jhydrol.2006.04.030 Google Scholar
  60. UNEP (2007) Global outlook for ice and snow. United Nations Environment ProgrammeGoogle Scholar
  61. van Vuuren DP, Edmonds J, Kainuma M, Riahi K, Thomson A, Hibbard K, Hurtt GC, Kram T, Krey V, Jean-Francois L, Masui T, Meinshausen M, Nakicenovic N, Smith SJ, Rose SK (2011) The representative concentration pathways: an overview. Climate Change 109:5–31.  https://doi.org/10.1007/s10584-011-0148-z Google Scholar
  62. Vuille M, Bradley RS (2000) Mean annual temperature trends and their vertical structure in the tropical Andes. Geophys Res Lett 27(23):3885–3888Google Scholar
  63. Wetterhall F, Bárdossy A, Chen D, Halldin S, Xu C-Y (2006) Daily precipitation- downscaling techniques in three Chinese regions. Water Resour Res 42:W11423.  https://doi.org/10.1029/2005WR004573 Google Scholar
  64. Wilby RL et al (2006) Integrated modeling of climate change impacts on water resources and quality in a low land catchment: River Kennet, UK. J Hydrol 330(1–2):204–220.  https://doi.org/10.1016/j.jhydrol.2006.04.033 Google Scholar
  65. Wilby RL, Dawson CW (2007) SDSM 4.2 - a decision support tool for the assessment of regional climate change impacts, Version 4.2 User Manual. Lancaster University, Lancaster/Environment Agency of England and Wales, Lancaster, 1–94.Google Scholar
  66. Wilby RL, Hay LE, Gutowski WJ Jr, Arritt RW, Takle ES, Pan Z, Leavesley GH, Clark MP (2000) Hydrological responses to dynamically and statistically downscaled climate model output. Geophys Res Lett 27(8):1199–1202.  https://doi.org/10.1029/1999GL006078 Google Scholar
  67. 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.  https://doi.org/10.1016/s1364-8152(01)00060-3 Google Scholar
  68. Xu CY (1999) Climate change and hydrologic models: a review of existing gaps and recent research developments. Water Resour Manag 13(5):369–382.  https://doi.org/10.1023/a:1008190900459 Google Scholar
  69. Zhang XC, Liu WZ, Li Z, Chen J (2011) Trend and uncertainty analysis of simulated climate change impacts with multiple GCMs and emission scenarios. Agric For Meteorol 151(10):1297–1304.  https://doi.org/10.1016/j.agrformet.2011.05.010 Google Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Climate and Cryosphere Group, Department of Geography and Regional DevelopmentUniversity of KashmirSrinagarIndia
  2. 2.Institute of Geographic Science and Natural Resources Research/Key Laboratory of Water Cycle and Related Land Surface Processes, Chinese Academy of SciencesBeijingChina
  3. 3.School of Environmental SciencesJawaharlal Nehru UniversityNew DelhiIndia

Personalised recommendations