Abstract
This paper aims to establish a relationship between selective meteorological variables such as wind speed, relative humidity, precipitation, maximum temperature and minimum temperature that contribute in the climate change of Jacobabad, a small district of Sindh province of Pakistan. Mean monthly time series data of meteorological variables were obtained for 10 years from Jan 2001 to Dec-2010. Regression analysis, Co-integration technique and Granger Causality test were applied to model wind speed as a function of meteorological conditions. The results reveal that a stable long run relationship exists between factors of climate change. Bi-directional causality was found between wind speed (V) and independent variables such as humidity (H), maximum temperature (T max) and minimum temperature (T min).