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MLR Based Statistical Downscaling of Temperature and Precipitation in Lidder Basin Region of India
YasirAltaf, Ahanger Manzoor Ahmad and Fahimuddin Mohd
In the present study, the multiple linear regression technique was employed to relate the monthly predictors obtained from the Global Climate Model namely CGCM3 (Canadian Centre for Climate Modelling and Analysis) with the monthly Predictands such as the locally observed precipitation and temperature at Pahalgam meteorological station which is located in the Lidder River Basin. Appropriate predictand-predictor relationships were found out for the region by carrying out sensitivity analysis .Regression equations were developed and subsequently future monthly and annual projections for precipitation, maximum temperature and minimum temperature for the entire 21st century were made. It was observed that at the end of the 21st century the CGCM3 model predicted an increase of 18.07% annual precipitation, whereas the average maximum and minimum annual temperatures were predicted to increase by 0.62°C and 0.76°C, respectively.