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REFERENCES

  • Anandhi A, Srivanas V, Kumar DN, Nanjundiah RS. 2009. Role of predictors in downscaling surface temperature to river basin for IPCC SRES scenarios using support vector machine. International Journal of Climatology 29: 583603.
  • Anandhi A, Srivanas V, Nanjundiah RS, Kumar DN. 2008. Downscaling precipitation to river basin in India for IPCC SRES scenarios using support vector machine. International Journal of Climatology 28: 401420.
  • Bhattacharya S. 2007. Lessons learnt for vulnerability and adaptation assessment from India's first national communication, vol 7, BASIC EU Project.
  • Cruz R, Harasawa M, Wu S, Anokhin Y, Punsalmaa B, Honda Y, Jafari M, Li C, Ninh NH. 2007. Asia Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment. Cambridge University Press: UK, 469506.
  • Darling D. 1957. The Kolmogorov-Smirnov, Cramer-von Mises tests. Annals of Mathematical Statistics 28: 823838.
  • Flato GM, Boer GJ, Lee WG, McFarlane NA, Ramsden D, Reader MC, Weaver AJ. 2000. The Canadian Centre for Climate Modeling and Analysis of Global Coupled Model and its climate, Climate Dynamics 16: 451467.
  • Furevik T, Bentsen M, Drange H, Kindem IKT, Kvamsto NG, Sorteberg A. 2003. Description and evaluation of the Bergen Climate Model: ARPEGE coupled with MICOM, Climate Dynamics 21: 2751.
  • Ghosh S, Mujumdar P. 2007. Nonparametric methods for modelling GCM scenario uncertainty in drought assessment. Water Research 43: W07405, 19 pp., DOI: 10.1029/2006WR005351.
  • Ghosh S, Mujumdar P. 2008. Statistical downscaling of GCM simulations to streamflow using relevance vector machine. Advances in Water Resources 31: 132146.
  • Hughes J, Guttorp P, Charles S. 1999. A non-homogeneous hidden Markov model for precipitation occurrence. Applied Statistics 48: 1530.
  • Jungclaus JH, Keenlyside N, Botzet M, Haak H, Luo JJ, Latif M, Marotzke J, Mikolajewicz U, Roeckner E. 2006. Ocean circulation and tropical variability in the coupled model ECHAM5/MPIOM, Journal of Climate, 19: 39523972.
  • Kripalani R, Oh J, Kulkarni A, Chaudhari H. 2007. South Asian summer monsoon precipitation variability: coupled climate model simulations and projections under IPCC AR4. Theoretical and Applied Climatology 90: 133159.
  • Kundzewicz Z, Mata L, Arnell N, D''ll P, Kabat P, Jim'nez B, Miller K, Oki T, Sen Z, Shiklomanov I. 2007. Freshwater Resources and their Management. Cambridge University Press: UK, 173210.
  • Michelangeli P, Vrac M, Loukos H. 2009. Probabilistic downscaling approaches: application to wind cumulative distribution functions. Geophysical Research Letters 36: L11708, 6 pp., DOI: 10.1029/2009GL038401.
  • Mujumdar P, Ghosh S. 2008. Modelling GCM and scenario uncertainties using a possibilistic approach: application to the Mahanadi River. Water Resources Research 44: W06407, 15 pp., DOI: 10.1029/2007WR006137.
  • Nakicenovic N, Davidson O, Davis G, Grbler A, Kram T, Rovere ELL, Metz B, Morita T, Pepper W, Pitcher H, Sankovski A, Shukla P, Swart R, Watson R, Dadi Z (eds). 2000. In Special Report on Emissions Scenarios: A Special Report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge University Press: 599.
  • Paeth H, Scholten A, Friederichs P, Hense A. 2008. Uncertainties in climate change prediction: El Nino-Southern Oscillation and monsoons. Global and Planetary Change 60: 265288.
  • Prudhomme C, Reynard N, Crooks S. 2002. Downscaling of global climate models for flood frequency analysis: where are we now? Hydrological Processes 16: 11371150.
  • Raje D, Mujumdar P. 2009. A conditional field-based downscaling method for assessment of climate change impact on multisite daily precipitation in the Mahanadi basin. Water Resources Research 45: W10404, 20 pp., DOI: 10.1029/2008WR007487.
  • Rajeevan M, Bhate J. 2008. A high resolution gridded rainfall dataset (1971–2005) for mesoscale meteorological studies. vol 9, NCC Research Report.
  • Rupa Kumar K, Sahai A, Kumar KK, Patwardhan S, Mishra P, Revadekar J, Kamala K, Pant G. 2006. High-resolution climate change scenarios for India for the 21st century. Current Science 90(3): 334345.
  • Salas-Melia D, Chauvin F, Deque M, Douville H, Gueremy JF, Marquet P, Planton S, Royer JF, Tyteca S. 2006. Description and validation of the CNRM-CM3 global coupled model, Climate Dynamics (in press).
  • Srivastava A, Rajeevan M, Kshirsagar S. 2008. Development of a high resolution daily gridded temperature dataset (1969–2005) for the Indian region. vol 8, NCC Research Report.
  • Tripathi S, Srinivas V, Nanjundiah SR. 2006. Downscaling of precipitation for climate change scenarios: a support vector machine approach. Journal of Hydrology 330: 621640.
  • Vrac M, Naveau P. 2007. Stochastic downscaling of precipitation: from dry events to heavy rainfalls. Water Resources Research 43: W07402, 13 pp., DOI: 10.1029/2006WR005308.
  • Vrac M, Stein M, Hayhoe K. 2007. Statistical downscaling of precipitation through non-homogeneous stochastic weather typing. Climate Research 34: 169184, DOI: 10.3354/cr00696.
  • Wilby R, Charles S, Zorita E, Timbal B, Whetton P, Mearns L. 2004. Guidelines for use of climate scenarios developed from statistical downscaling methods. Supporting Material of the IPCC, 127.
  • Wilks D, Wilby R. 1999. The weather generation game: a review of stochastic weather model. Progress in Physical Geography 23: 329357.
  • Wood A, Sridhar V, Lettenmaier D. 2004. Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Climate Change 62: 189216.