Evaluation of SDSM developed by annual and monthly sub-models for downscaling temperature and precipitation in the Jhelum basin, Pakistan and India

The study evaluates statistical downscaling model (SDSM) developed by annual and monthly sub-models for downscaling maximum temperature, minimum temperature, and precipitation, and assesses future changes in climate in the Jhelum River basin, Pakistan and India. Additionally, bias correction is applied on downscaled climate variables. The mean explained variances of 66, 76, and 11 % for max temperature, min temperature, and precipitation, respectively, are obtained during calibration of SDSM with NCEP predictors, which are selected through a quantitative procedure. During validation, average R2 values by the annual sub-model (SDSM-A)—followed by bias correction using NCEP, H3A2, and H3B2—lie between 98.4 and 99.1 % for both max and min temperature, and 77 to 85 % for precipitation. As for the monthly sub-model (SDSM-M), followed by bias correction, average R2 values lie between 98.5 and 99.5 % for both max and min temperature and 75 to 83 % for precipitation. These results indicate a good applicability of SDSM-A and SDSM-M for downscaling max temperature, min temperature, and precipitation under H3A2 and H3B2 scenarios for future periods of the 2020s, 2050s, and 2080s in this basin. Both sub-models show a mean annual increase in max temperature, min temperature, and precipitation. Under H3A2, and according to both sub-models, changes in max temperature, min temperature, and precipitation are projected as 0.91–3.15 °C, 0.93–2.63 °C, and 6–12 %, and under H3B2, the values of change are 0.69–1.92 °C, 0.56–1.63 °C, and 8–14 % in 2020s, 2050s, and 2080s. These results show that the climate of the basin will be warmer and wetter relative to the baseline period. SDSM-A, most of the time, projects higher changes in climate than SDSM-M. It can also be concluded that although SDSM-A performed well in predicting mean annual values, it cannot be used with regard to monthly and seasonal variations, especially in the case of precipitation unless correction is applied.

[1]  B. Hewitson,et al.  Climate downscaling: techniques and application , 1996 .

[2]  Pier Luigi Vidale,et al.  The application of Regional Climate Model output for the simulation of high-mountain permafrost scenarios , 2007 .

[3]  Subhrendu Gangopadhyay,et al.  A non-parametric, statistical downscaling algorithm applied to the Rohini River Basin, Nepal , 2011 .

[4]  R. Huth.  Statistical Downscaling of Daily Temperature in Central Europe , 2002 .

[5]  T. Wigley,et al.  Downscaling general circulation model output: a review of methods and limitations , 1997 .

[6]  J. Ni,et al.  GIS-based high-resolution spatial interpolation of precipitation in mountain–plain areas of Upper Pakistan for regional climate change impact studies , 2009 .

[7]  Vijay P. Singh,et al.  Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, China , 2009 .

[8]  Muhammad Zaffar Hashmi,et al.  Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed , 2011 .

[9]  J. Rousselle,et al.  An Application of the Statistical DownScaling Model (SDSM) to Simulate Climatic Data for Streamflow Modelling in Québec , 2005 .

[10]  S. Pryor,et al.  Downscaling temperature and precipitation: a comparison of regression‐based methods and artificial neural networks , 2001 .

[11]  Z. Qiang,et al.  Stochastic modeling of daily precipitation in China , 2004 .

[12]  M. J. Booij,et al.  The impact of climate change on the water resources of Hindukush Karakorum Himalaya region under different glacier coverage scenarios , 2008 .

[13]  L. Hay,et al.  A comparison of downscaled and raw GCM output: implications for climate change scenarios in the San Juan River basin, Colorado , 1999 .

[14]  Deliang L. Chen,et al.  Empirical-Statistical Downscaling , 2008 .

[15]  A. Gustard,et al.  Spatial and temporal variations in the occurrence of low flow events in the UK , 2000 .

[16]  T. D. Mitchell,et al.  An improved method of constructing a database of monthly climate observations and associated high‐resolution grids , 2005 .

[17]  András Bárdossy,et al.  Downscaling daily precipitation time series using a combined circulation- and regression-based approach , 2010 .

[18]  Subimal Ghosh,et al.  Prediction of daily rainfall state in a river basin using statistical downscaling from GCM output , 2011 .

[19]  Hong Yang,et al.  Using MODAWEC to generate daily weather data for the EPIC model , 2009, Environ. Model. Softw..

[20]  C. Ojha,et al.  Robust weighted regression as a downscaling tool in temperature projections , 2010 .

[21]  Hayley J. Fowler,et al.  Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling , 2007 .

[22]  I. Seierstad,et al.  Impacts of climate change on Blue Nile flows using bias-corrected GCM scenarios , 2008 .

[23]  Hayley J. Fowler,et al.  Using meteorological data to forecast seasonal runoff on the River Jhelum, Pakistan , 2008 .

[24]  Martyn P. Clark,et al.  Use of statistically and dynamically downscaled atmospheric model output for hydrologic simulations in three mountainous basins in the western United States , 2003 .

[25]  Ravi S. Nanjundiah,et al.  Downscaling precipitation to river basin in India for IPCC SRES scenarios using support vector machine , 2008 .

[26]  Christian W. Dawson,et al.  SDSM - a decision support tool for the assessment of regional climate change impacts , 2002, Environ. Model. Softw..

[27]  R. Fealy,et al.  Statistical downscaling of precipitation for a selection of sites in Ireland employing a generalised linear modelling approach , 2007 .

[28]  N. Ahmad,et al.  Irrigated agriculture of Pakistan , 1988 .

[29]  V. V. Srinivas,et al.  Downscaling of precipitation for climate change scenarios: A support vector machine approach , 2006 .

[30]  Subimal Ghosh,et al.  Modeling GCM and scenario uncertainty using a possibilistic approach: Application to the Mahanadi River, India , 2008 .

[31]  M. Clark,et al.  Hydrological responses to dynamically and statistically downscaled climate model output , 2000 .

[32]  P. Coulibaly,et al.  Hydrologic impact of climate change in the Saguenay watershed: comparison of downscaling methods and hydrologic models , 2005 .

[33]  F. Wentz,et al.  How Much More Rain Will Global Warming Bring? , 2007, Science.

[34]  Raquel V. Francisco,et al.  Regional Climate Information—Evaluation and Projections , 2001 .

[35]  F. De Smedt,et al.  Analysing the effect of climate changes on streamflow using statistically downscaled GCM scenarios , 2004 .

[36]  P. H. Ang,et al.  A comparison of different regional climate models and statistical downscaling methods for extreme rainfall estimation under climate change , 2012 .

[37]  Paulin Coulibaly,et al.  Uncertainty analysis of statistical downscaling methods , 2006 .

[38]  J. Pallant.  SPSS survival manual : a step-by-step guide to data analysis using SPSS version 15 , 2007 .

[39]  Robert L. Wilby,et al.  Integrated modelling of climate change impacts on water resources and quality in a lowland catchment: River Kennet, UK , 2006 .

[40]  D. Gellens,et al.  Streamflow response of Belgian catchments to IPCC climate change scenarios , 1998 .

[41]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .

[42]  Subimal Ghosh,et al.  Statistical downscaling of GCM simulations to streamflow using relevance vector machine , 2008 .

[43]  David J. Sailor,et al.  Application of tree-structured regression for regional precipitation prediction using general circulation model output , 2000 .

[44]  Chong-Yu Xu,et al.  Estimation of future precipitation change in the Yangtze River basin by using statistical downscaling method , 2011 .

[45]  Xuebin Zhang,et al.  Downscaling and Projection of Winter Extreme Daily Precipitation over North America , 2008 .

[46]  Chong-Yu Xu,et al.  Climate Change and Hydrologic Models: A Review of Existing Gaps and Recent Research Developments , 1999 .

[47]  Chong-Yu Xu,et al.  Daily precipitation‐downscaling techniques in three Chinese regions , 2006 .

[48]  R. Wilby,et al.  A comparison of statistical downscaling and climate change factor methods: impacts on low flows in the River Thames, United Kingdom , 2005 .

[49]  S. Charles,et al.  Evaluation of two statistical downscaling models for daily precipitation over an arid basin in China , 2011 .

[50]  Deliang Chen,et al.  Statistical downscaling of daily precipitation over Sweden using GCM output , 2009 .

[51]  Jie Chen,et al.  Trend and uncertainty analysis of simulated climate change impacts with multiple GCMs and emission scenarios , 2011 .

[52]  M. Souvignet,et al.  Statistical downscaling in the arid central Andes: uncertainty analysis of multi-model simulated temperature and precipitation , 2011 .

[53]  M. Babel,et al.  Spatial disaggregation of bias-corrected GCM precipitation for improved hydrologic simulation: Ping River Basin, Thailand , 2007 .

[54]  L. Hay,et al.  A COMPARISON OF DELTA CHANGE AND DOWNSCALED GCM SCENARIOS FOR THREE MOUNTAINOUS BASINS IN THE UNITED STATES 1 , 2000 .