A Statistical Downscaling Technique for Assessment of Meteorological Parameters under Climate Change Condition Using SDSM-DC Model in Raipur District

Abstract

Changes in maximum and minimum temperature with occurrence of extreme events are major threat to future food security due to climate change. Climate change related occurrence of extreme events can have serious consequences for human health and agricultural production. Chhattisgarh (Raipur) is already facing increased temperatures in summers. In the present study, efforts have been made to analyze meteorological parameters aspects of climate change at Raipur district in Chhattisgarh. The data of climatic parameters including maximum temperature, minimum temperature, relative humidity, sunshine hour, wind speed and evaporation has been used for forecasting the three future periods FP-1 (2011-2040), FP-2 (2041-2070) and FP-3 (2071-2099) under A1B and A2 climate forcing conditions. The statistical downscaling technique proposed in SDSM-DC 5.2 was used to select an appropriate set of climate predictors. The selected sets of predictors were further used to project future climate for three different periods and multiple series after debiased were further used to ascertain the change from base period mean monthly values for climatic parameters and peak over threshold & peak below threshold values. Generation of multiple series for meteorological parameters under A1B and A2 climate scenario has been worked for analysis of changes in meteorological parameters due to change of climate. A comparison of different meteorological parameters has been revolved that helped for making future planning under climate change condition.