Countries around the world have already been experiencing the repercussions of climate change. Bangladesh is cited as one of the most vulnerable countries among them. Due to the utmost contribution to the country’s economy and continuous exposure to climatic extremes, climate change scenarios for the largest division in the country, the Chittagong Division, have a major concern. This study analyzed the potential climatic changes by the downscaling approach for the Chittagong Division under Representative Concentration Pathways (RCPs) i.e., RCP 2.5, RCP 4.5 and RCP 8.5, and Special Report on Emission Scenarios (SRES) i.e., A2, A1B, and B2 scenarios. Statistical Downscaling Model (SDSM) was used for downscaling three General Circulation Models (GCMs) viz. HadCM3, CanESM2, and CGCM3. A quantitative approach was used for both calibration and validation, where the results indicated the suitability of SDSM for downscaling daily mean temperature and precipitation under different scenarios for three future time horizons, i.e., early-twenty-first, mid-twenty-first, and late-twenty-first century. Additionally, bias correction was applied to downscaled climate variables. The downscaled projection showed increasing trends in mean annual temperature and precipitation for all the scenarios by the end of the century. Under CanESM2, the highest increase in temperature and precipitation were projected as 1.1 °C and 1.7 mm for the RCP 8.5. On the other hand, the highest increase in temperature and precipitation were projected as 0.5 °C and 1.4 mm for the SRES scenario A2 under CGCM3 and HadCM3. The spatial distribution of projections shows that the southern coastal part of the division is marked by remarkable future changes. The downscaled pathways have set a basis for assessing the impacts of future climate change on different sectors for the Chittagong Division and other areas in the country.

世界各国已经在经历气候变化的影响。孟加拉国被认为是其中最脆弱的国家之一。由于对国家经济的最大贡献和持续暴露在极端气候下，该国最大的部门吉大港部门的气候变化情景受到了重大关注。本研究根据代表性浓度路径 (RCP)，即 RCP 2.5、RCP 4.5 和 RCP 8.5，以及排放情景特别报告 (SRES)，即 A2、A1B 和 B2，分析了吉大港分部降尺度的潜在气候变化场景。统计降尺度模型 (SDSM) 用于降尺度三个一般循环模型 (GCM)，即。HadCM3、CanESM2 和 CGCM3。定量方法用于校准和验证，结果表明 SDSM 适用于在三个未来时间范围内的不同情景下降低日平均温度和降水量，即 20 年代初、20 年代中期和二十一世纪末。此外，偏差校正应用于缩小的气候变量。缩小比例的预测显示，到本世纪末，所有情景的年平均气温和降水量均呈上升趋势。在 CanESM2 下，RCP 8.5 的最高温度和降水增幅预计为 1.1 °C 和 1.7 mm。另一方面，对于 CGCM3 和 HadCM3 下的 SRES 情景 A2，温度和降水的最高增幅预计为 0.5 °C 和 1.4 mm。投影的空间分布表明，该分区的南部沿海部分未来变化显着。缩小的路径为评估未来气候变化对吉大港分部和该国其他地区不同部门的影响奠定了基础。