Abstract
Anthropogenic influence on the climate system is clear, and the recent emissions of greenhouse gases are the highest in history. This particular activity is aimed to project the future climate using different representative concentration pathways of emission scenarios for Jima station. Statistical downscaling approach was used to downscale rainfall and temperature. Predictors were synthesized based on correlation analysis between large scale climate predictors and observed station climate data. Monthly predictors were used to establish a regression model between the predictors and observed climate variables. The regression models were validated against observed station data and were used to generate downscaled future rainfall and temperature. Data for future scenario were collected from the Canadian Centre for Climate Modeling and Analysis (CCCma) of Canada Environment.
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