EdGCM

Abstract: Downscaling is a state-of-the-art technique to generate fine-resolution climate change prediction and an obvious tool for forecasting future climate scenarios for many data-scarce areas like Bangladesh. The Educational Global Climate Model (EdGCM) predicts numerically and its performance was not evaluated for Bangladesh earlier. Due to this reason, an attempt has been made to apply a new geostatistical approach with the help of transform software to downscale EdGCM for identifying the trend of surface air temperature at the Sylhet district. Both Doubled_CO2 and Global_Warming_01 are simulated from EdGCM and maps are generated to depict global temperature variations. Downscaling is applied to the outputs from Doubled_CO2 scenario. Percent of bias (PBIAS), Nash-Sutcliffe efficiency (NSE) and the ratio of root mean square error to the standard deviation of measured data (RSR) values are satisfactory and acceptable. The trend analysis was performed using the Mann-Kendall Trend test and Sen’s slope estimator. Temperature changes are significant for both downscaled and observed results of p-value which is less than alpha = 0.05. Mann-Kendall Z tests for annual downscaled and IPCC during (2006-2020) show a positive trend. Downscaled predicted annual average temperature (simulations by Doubled_CO2) for 2020 is 21.67 ̊C for the Sylhet district.

Abstract: Environmental changes and global warming have direct impact on human life. Estimation of these changes in various parameters of hydrologic cycle is necessary for future planning and development of a country. In this paper the impact of environmental changes and global warming on temperatures of Pakistan has been studied. The temperature changes in Pakistan have been extracted from simulations made using EdGCM model developed at Columbia University. Simulation study to the end of 21st century is executed using the model for GHG (Greenhouse Gases) scenario with doubled_CO 2 and scenario of Modern_Predicted SST (Sea Surface Temperature). The model analysis has been carried out for seasonal and annual changes for an average of last 5 years period from 2096-2100. Maps are generated to depict global temperature variations. The study divides Pakistan into five (05) main areas for twenty six (26) stations. A part-plan of globe focusing Pakistan is generated showing the five divisions for twenty six (26) data stations of Pakistan. This part plan is made compatible with grid-box resolution of EdGCM. Eagle-Point Engineering software has been used to generate isohyets of interval (0.5 o C) for downscaling GCM (Global Climate Model) grid data to data stations. The station values of different seasons and annual changes are then compared with the values of base period data to determine changes in temperature. It is observed that impact of global environmental changes on temperature are higher (i.e. there is an increase in annual temperature for double_CO 2 experiment) at places near the Arabian Sea than areas located away from this sea. It is also observed that the temperature increase will be more in winter than that in other seasons for Pakistan.