Abstract
In this study, temperature extremes are analyzed for observed (1979–2005) and projected scenarios using three global climate models (GCMs) and their Representative Concentration Pathways (RCPs) based on Coupled Model Intercomparison Project Phase 5 (CMIP5) datasets, to investigate the spatio-temporal variations and possible changes in joint probability behavior of temperature extremes over North Sikkim Himalaya, India. Statistical downscaling model (SDSM) and copulas are applied to downscale the GCM outputs and to construct joint probability distribution of extremes, respectively. A set of ten climate extreme indices are selected to understand the inter-annual variability. Joint return period of extreme indices was calculated using six temperature extreme indices (based on days). Linear trends were estimated using Mann Kendall test with statistical significance and indicated widespread significant changes in temperature extremes. The significant changes in temperature extremes such as the temperature of warmest night and day have increased by 1.41 and 1.83 °C, and the temperature of coldest night and day has decreased by 3.61 and 4.83 °C, respectively, during 2006–2100 with the baseline period of 1979–2005. The spatial distribution of 5-year return periods and 10-year return periods is almost similar during 1979–2005. There is less co-occurrence of warm nights and days, but higher chance to co-occurrence of cool and warm nights in the same year during 2021–2100. The change in joint return periods under the RCP8.5 shows frequent co-occurrence of cool days and nights, ice and frost days, and cool and frost days than RCP2.6 and RCP4.5. This study implies that the warm days, cool days, warmer nights, and cool nights are decreased with increased warming intensity, which shows the overall warming trend over the North Sikkim Himalaya, India.
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References
Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723. https://doi.org/10.1109/TAC.1974.1100705
Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B, Klein Tank AMG, Haylock M, Collins D, Trewin B, Rahimzadeh F, Tagipour A, Rupa Kumar K, Revadekar J, Griffiths G, Vincent L, Stephenson DB, Burn J, Aguilar E, Brunet M, Taylor M, New M, Zhai P, Rusticucci M, Vazquez-Aguirre JL (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res Atmos 111:D05109. https://doi.org/10.1029/2005JD006290
Boo KO, Kwon WT, Baek HJ (2006) Change of extreme events of temperature and precipitation over Korea using regional projection of future climate change. Geophys Res Lett 33:L01701. https://doi.org/10.1029/2005GL023378
Chattopadhyay N (2011) Climate change and food security in India. Clim Chang Food Secur South Asia:129–251. https://doi.org/10.1007/978-90-481-9516-9_15
Chen YD, Zhang Q, Xiao M, Singh VP, Zhang S (2016) Probabilistic forecasting of seasonal droughts in the Pearl River basin. China Stoch Environ Res Risk Assess 30:2031–2040. https://doi.org/10.1007/s00477-015-1174-6
Colombo AF, Etkin D, Karney BW (1999) Climate variability and the frequency of extreme temperature events for nine sites across Canada: implications for power usage. J Clim 12:2490–2502. https://doi.org/10.1175/1520-0442(1999)
Dai A (2011) Drought under global warming: a review. Wiley Interdiscip Rev Clim Chang 2:45–65. https://doi.org/10.1002/wcc.81
De US, Dube RK, Rao GSP (2005) Extreme weather events over India in the last 100 years. J Indian Geophys Union 9:173–187
Dimri AP, Dash SK (2012) Wintertime climatic trends in the western Himalayas. Clim Chang 111:775–800. https://doi.org/10.1007/s10584-011-0201-y
Donat MG, Alexander LV, Yang H, Durre I, Vose R, Dunn RJH, Willett KM, Aguilar E, Brunet M, Caesar J, Hewitson B, Jack C, Klein Tank AMG, Kruger AC, Marengo J, Peterson TC, Renom M, Oria Rojas C, Rusticucci M, Salinger J, Elrayah AS, Sekele SS, Srivastava AK, Trewin B, Villarroel C, Vincent LA, Zhai P, Zhang X, Kitching S, Rojas CO, Rusticucci M, Salinger J, Oria Rojas C, Rusticucci M, Salinger J, Elrayah AS, Sekele SS, Srivastava AK, Trewin B, Villarroel C, Vincent LA, Zhai P, Zhang X, Kitching S (2013) Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: the HadEX2 dataset. J Geophys Res Atmos 118:2098–2118. https://doi.org/10.1002/jgrd.50150
Easterling DR, Meehl GA, Parmesan C, Changnon SA, Karl TR, Mearns LO (2000) Climate extremes: observations, modeling, and impacts. Science 289:2068–2074. https://doi.org/10.1126/science.289.5487.2068
Favre AC (2004) Multivariate hydrological frequency analysis using copulas. Water Resour Res 40:1–12. https://doi.org/10.1029/2003WR002456
Frich P, Alexander LV, Della-Marta P, Gleason B, Haylock M, Tank Klein AMG, Peterson T (2002) Observed coherent changes in climatic extremes during the second half of the twentieth century. Clim Res 19:193–212. https://doi.org/10.3354/cr019193
Genest C, Favre AC, Béliveau J, Jacques C (2007) Metaelliptical copulas and their use in frequency analysis of multivariate hydrological data. Water Resour Res 43:1–12. https://doi.org/10.1029/2006WR005275
Grimaldi S, Serinaldi F (2006) Asymmetric copula in multivariate flood frequency analysis. Adv Water Resour 29:1155–1167. https://doi.org/10.1016/j.advwatres.2005.09.005
Grimaldi S, Petroselli A, Salvadori G, De Michele C (2016) Catchment compatibility via copulas: a non-parametric study of the dependence structures of hydrological responses. Adv Water Resour 90:116–133. https://doi.org/10.1016/j.advwatres.2016.02.003
IPCC (2014) Climate change 2014: synthesis report. In: Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change. R.K. Pachauri and L.A. Meyer, Core Writing Team. https://doi.org/10.1017/CBO9781107415324.004
Katz RW, Brown BG (1992) Extreme events in changing climate variability is more important than average. Clim Chang 21:289–302. https://doi.org/10.1007/BF00139728
Kendall MG (1975) Rank correlation methods. Griffin, London
Klein Tank AMG, Peterson TC, Quadir DA, Dorji S, Zou X, Tang H, Santhosh K, Joshi UR, Jaswal AK, Kolli RK, Sikder AB, Deshpande NR, Revadekar JV, Yeleuova K, Vandasheva S, Faleyeva M, Gomboluudev P, Budhathoki KP, Hussain A, Afzaal M, Chandrapala L, Anvar H, Amanmurad D, Asanova VS, Jones PD, New MG, Spektorman T (2006) Changes in daily temperature and precipitation extremes in central and south Asia. J Geophys Res 111:D16105. https://doi.org/10.1029/2005JD006316
Lesk C, Rowhani P, Ramankutty N (2016) Influence of extreme weather disasters on global crop production. Nature 529:84–87. https://doi.org/10.1038/nature16467
Li J, Zhang Q, Chen YD, Singh VP (2015) Future joint probability behaviors of precipitation extremes across China: spatiotemporal patterns and implications for flood and drought hazards. Glob Planet Change 124:107–122. https://doi.org/10.1016/j.gloplacha.2014.11.012
Manton MJ, Haylock MR, Hennessy KJ, Nicholls N, Chambers LE, Collins DA, Daw G, Finet A, Gunawan D, Inape K, Isobe H, Kestin TS, Lefale P, Leyu CH, Lwin T, Maitrepierre L, Ouprasitwong N, Page CM, Pahalad J, Plummer N, Salinger MJ, Suppiah R, Tran VL, Trewin B, Tibig I, Yee D (2001) Trends in extreme daily rainfall and temperature in Southeast Asia and the South Pacific : 1961–1998. Int J Climatol 21:269–284. https://doi.org/10.1002/joc.610
Marti G, Andler S, Nielsen F, Donnat P (2016) Optimal transport vs. fisher-Rao distance between copulas for clustering multivariate time series. IEEE work. Stat. Signal process. Proc. 2016–august, 2–6. doi:https://doi.org/10.1109/SSP.2016.7551770
Mearns LO, Katz RW, Schneider SH (1984) Extreme high-temperature events: changes in their probabilities with changes in mean temperature. J Clim Appl Meteorol 23:1601–1613. https://doi.org/10.1175/1520-0450(1984)023<1601:EHTECI>2.0.CO;2
Meetei LI, Pattanayak SK, Bhaskar A, Pandit MK, Tandon SK (2007) Climatic imprints in quaternary valley fill deposits of the middle Teesta valley, Sikkim Himalaya. Quat Int 159:32–49. https://doi.org/10.1016/j.quaint.2006.08.018
Moberg A, Jones PD, Lister D, Walther A, Brunet M, Jacobeit J, Alexander LV, Della-Marta PM, Luterbacher J, Yiou P, Chen D, Tank AMGK, Saladié O, Sigró J, Aguilar E, Alexandersson H, Almarza C, Auer I, Barriendos M, Begert M, Bergström H, Böhm R, Butler CJ, Caesar J, Drebs A, Founda D, Gerstengarbe FW, Micela G, Maugeri M, Österle H, Pandzic K, Petrakis M, Srnec L, Tolasz R, Tuomenvirta H, Werner PC, Linderholm H, Philipp A, Wanner H, Xoplaki E (2006) Indices for daily temperature and precipitation extremes in Europe analyzed for the period 1901–2000. J Geophys Res Atmos 111:D22106. https://doi.org/10.1029/2006JD007103
Nelson RB (2006) An introduction to copulas. Springer Sci Bus Media 137:2143–2150. https://doi.org/10.1016/j.jspi.2006.06.045
Renard B, Lang M (2007) Use of a Gaussian copula for multivariate extreme value analysis: some case studies in hydrology. Adv Water Resour 30:897–912. https://doi.org/10.1016/j.advwatres.2006.08.001
Rosegrant MW, Cline SA (2003) Global food security: challenges and policies. Am Assoc Adv Sci 302:1917–1919. https://doi.org/10.1126/science.1092958
Salvadori G, De Michele C (2004) Frequency analysis via copulas: theoretical aspects and applications to hydrological events. Water Resour Res 40:1–17. https://doi.org/10.1029/2004WR003133
Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 63:1379–1389. https://doi.org/10.2307/2285891
Sheffield J, Wood EF, Roderick ML (2012) Little change in global drought over the past 60 years. Nature 491:435–438. https://doi.org/10.1038/nature11575
Sillmann J, Roeckner E (2008) Indices for extreme events in projections of anthropogenic climate change. Clim Chang 86:83–104. https://doi.org/10.1007/s10584-007-9308-6
Sillmann J, Kharin VV, Zwiers FW, Zhang X, Bronaugh D (2013) Climate extremes indices in the CMIP5 multimodel ensemble: part 2. Future climate projections. J Geophys Res Atmos 118:2473–2493. https://doi.org/10.1002/jgrd.50188
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. https://doi.org/10.1016/j.atmosres.2015.07.005
Skalr A (1959) Fonctions de reprtition a n dimensions et leursmarges. Publ Inst Stat Univ Paris 8:229–231
Snyder WM (1962) Some possibilities for multivariate analysis in hydrologic studies. J Geophys Res 67:721–729. https://doi.org/10.1029/JZ067i002p00721
Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498. https://doi.org/10.1175/BAMS-D-11-00094.1
Trenberth KE, Dai A, van der Schrier G, Jones PD, Barichivich J, Briffa KR, Sheffield J (2014) Global warming and changes in drought. Nat Clim Chang 4:17–22. https://doi.org/10.1038/NCLIMATE2067
Wang X, Gebremichael M, Yan J (2010) Weighted likelihood copula modeling of extreme rainfall events in Connecticut. J Hydrol 390:108–115. https://doi.org/10.1016/j.jhydrol.2010.06.039
Wang B, Zhang M, Wei J, Wang S, Li S, Ma Q, Li X, Pan S (2013) Changes in extreme events of temperature and precipitation over Xinjiang, northwest China, during 1960–2009. Quat Int 298:141–151. https://doi.org/10.1016/j.quaint.2012.09.010
Westra S, Brown C, Lall U, Sharma A (2007) Modeling multivariable hydrological series: principal component analysis or independent component analysis? Water Resour Res 43:1–11. https://doi.org/10.1029/2006WR005617
Wilby RL, Dawson CW, Barrow EM (2002) SDSM—a decision support tool for the assessment of regional climate change impacts. Environ Model Softw 17:147–159. https://doi.org/10.1016/S1364-8152(01)00060-3
Yue S, Rasmussen P (2002) Bivariate frequency analysis: discussion of some useful concepts in hydrological application. Hydrol Process 16:2881–2898. https://doi.org/10.1002/hyp.1185
Zhang L, Singh VP (2006) Bivariate flood frequency analysis using the copula method. J Hydrol Eng 11:150–164. https://doi.org/10.1061/(ASCE)1084-0699(2006)11:2(150)
Zhang L, Singh VP (2007) Bivariate rainfall frequency distributions using Archimedean copulas. J Hydrol 332:93–109. https://doi.org/10.1016/j.jhydrol.2006.06.033
Zhang Q, Singh VP, Li J, Jiang F, Bai Y (2012) Spatio-temporal variations of precipitation extremes in Xinjiang, China. J Hydrol 434–435:7–18. https://doi.org/10.1016/j.jhydrol.2012.02.038
Zhang Q, Li J, Singh VP, Xu CY (2013) Copula-based spatio-temporal patterns of precipitation extremes in China. Int J Climatol 33:1140–1152. https://doi.org/10.1002/joc.3499
Acknowledgement
This research work has been carried out under DST research project No. SB/DGH-66/2013 and financial support is gratefully acknowledged.
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Goswami, U.P., Bhargav, K., Hazra, B. et al. Spatiotemporal and joint probability behavior of temperature extremes over the Himalayan region under changing climate. Theor Appl Climatol 134, 477–498 (2018). https://doi.org/10.1007/s00704-017-2288-1
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DOI: https://doi.org/10.1007/s00704-017-2288-1