Assessment of future climate change over the north-west region of Bangladesh using SDSM and CanESM2 under RCP scenarios

被引:0
作者
Md.Masud Rana [1 ]
Sajal Kumar Adhikary [2 ]
Md. Bashirul Islam [3 ]
Md. Hafizur Rahman [4 ]
机构
[1] Northern University of Business & Technology Khulna,Department of Civil Engineering
[2] Khulna University of Engineering & Technology,Department of Civil Engineering
[3] Chittagong University of Engineering & Technology,Institute of River, Harbor and Environmental Science
[4] Monash University Malaysia,Department of Civil Engineering, Faculty of Engineering
关键词
Climate change; GCM; Statistical downscaling; SDSM; Monsoon seasons; RCP scenarios;
D O I
10.1007/s12517-024-12089-x
中图分类号
学科分类号
摘要
The frequency of extreme hydrologic events such as floods, storm surges, droughts, heat waves, extreme precipitation, and other similar occurrences has been increasing in Bangladesh due to the impact of climate change. Therefore, the assessment of changes in future climates is essential for climate-induced risk management in the country to safeguard natural resources and human lives. The main purpose of the current study is to assess the trend of maximum temperature (Tmax), minimum temperature (Tmin), and precipitation for the north-west region of Bangladesh in seasonal and annual scales for three future periods, including 2025–2050, 2051–2080, and 2081–2100, respectively. In order to achieve this goal, a large-scale atmospheric dataset obtained from the well-known general circulation model (GCM), CanESM2, is downscaled to finer scales at the local level using the widely used statistical downscaling model (SDSM). The downscaling of local climate variables is carried out using daily observed climate data under three representative concentration pathways (RCP) scenarios, including RCP2.6, RCP4.5, and RCP8.5, respectively. Correlation matrices with p-values have been utilized to select the most suitable predictors from NCEP/NCAR reanalysis data. Both the calibration (0.87 < R2 < 0.98, 0.87 < EV < 0.99, 19.24 > SE < 0.12) and validation findings demonstrate that the model performs satisfactorily. The bias correction approach is also adopted to achieve more consistent results. Seasonally, the mean seasonal temperature and precipitation are projected to rise in all seasons (except winter for precipitation). Annually, Tmax and Tmin have grown by 0.49 °C and 1.36 °C, respectively, whereas precipitation has increased by 49% up to the next century considering the RCP8.5 scenario (worst case). Overall, the outcome of the current study is expected to be supportive to policymakers and water managers in planning climate-resilient agricultural and infrastructure development activities for managing climate-induced disastrous events in the north-west region of Bangladesh.
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