MODELING OF FUTURE PRECIPITATION IN SRINAGAR CITY USING MULTIPLE LINEAR REGRESSION MODEL

Abstract

The aim of this study is to analyze the performances of prediction procedure based on Multiple Linear Regression Model (MLRM), for the precipitation amounts for yearly and monthly time scales, in Srinagar City located in Jammu and Kashmir, India. For this purpose we have used as predict and monthly amounts of precipitation and as predictors Mean Sea level pressure(mslpas),Mean temperature at 2m(tempas),Specific humidity at 2m (humas), Geopotential height at 500 hPa (p500-as), Surface zonal velocity(u) and Surface meridional velocity(v). The selection of predictors is based on the backward elimination or predicative (ptest) analysis.All data sets used in this study are gridded data with a spatial resolution of 2º x 2º lat/lon and are obtained from Canadian Global Climate model version 3(CGCM3) .The analysis is made for a period of 45 years between1970 and 2015, the period 1970– 2010 being used to build the MLRM and the period 2011 – 2015 for testing the prediction performances of the MLRM. Using MLRM we have obtained some good correlation between predicted and measured precipitation amount. The correlation coefficient varies between 0.57 and 0.84, with the smallest values in winter and the greatest values in spring. The total annual precipitation shows a decrease of 41.42% at the end of 21st century for Srinagar city.