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DOI: https://doi.org/10.4491/eer.2019.383
Application of transform software for downscaling global climate model EdGCM results in North-Eastern Bangladesh
Fahmida Ishaque, Israt Jahan Ripa, Altaf Hossain, Abdur Rashid Sarker, Gazi Tamiz Uddin, Hafizur Rahman, and Joyshankar Baidya
Department of Agricultural Construction and Environmental Engineering, Sylhet Agricultural University, Bangladesh
Corresponding Author: Israt Jahan Ripa ,Tel: +8801789069174, Email: isratsau46@gmail.co
Received: September 17, 2019;  Accepted: January 6, 2020.
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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_〖C0〗_2 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 〖C0〗_2 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_〖C0〗_2) for 2020 is 21.67℃ for the Sylhet district.
Keywords: Climate | Downscaling | EdGCM | Mann-Kendall Trend test | NSE | Surface air temperature
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