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Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs

Mohammad Kamruzzaman, Mohammad Kamruzzaman and Wahid, Shahriar and Shahid, Shamsuddin and Alam, Edris and Mohammed Mainuddin, Mohammed Mainuddin and Islam, H. M. Touhidul and Cho, Jeapil and Rahman, Md. Mizanur and Biswas, Jatish Chandra and Thorp, Kelly R. (2023) Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs. Heliyon, 9 (5). pp. 1-21. ISSN 2405-8440

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Official URL: http://dx.doi.org/10.1016/j.heliyon.2023.e16274

Abstract

Understanding spatiotemporal variability in precipitation and temperature and their future projections is critical for assessing environmental hazards and planning long-term mitigation and adaptation. In this study, 18 Global Climate Models (GCMs) from the most recent Coupled Model Intercomparison Project phase 6 (CMIP6) were employed to project the mean annual, seasonal, and monthly precipitation, maximum air temperature (Tmax), and minimum air temperature (Tmin) in Bangladesh. The GCM projections were bias-corrected using the Simple Quantile Mapping (SQM) technique. Using the Multi-Model Ensemble (MME) mean of the bias-corrected dataset, the expected changes for the four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) were evaluated for the near (2015–2044), mid (2045–2074), and far (2075–2100) futures in comparison to the historical period (1985–2014). In the far future, the anticipated average annual precipitation increased by 9.48%, 13.63%, 21.07%, and 30.90%, while the average Tmax (Tmin) rose by 1.09 (1.17), 1.60 (1.91), 2.12 (2.80), and 2.99 (3.69) °C for SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. According to predictions for the SSP5-8.5 scenario in the distant future, there is expected to be a substantial rise in precipitation (41.98%) during the post-monsoon season. In contrast, winter precipitation was predicted to decrease most (11.12%) in the mid-future for SSP3-7.0, while to increase most (15.62%) in the far-future for SSP1-2.6. Tmax (Tmin) was predicted to rise most in the winter and least in the monsoon for all periods and scenarios. Tmin increased more rapidly than Tmax in all seasons for all SSPs. The projected changes could lead to more frequent and severe flooding, landslides, and negative impacts on human health, agriculture, and ecosystems. The study highlights the need for localized and context-specific adaptation strategies as different regions of Bangladesh will be affected differently by these changes.

Item Type:Article
Uncontrolled Keywords:Downscaling, Global climate models, Multi-model ensemble, Projections, Shared socioeconomic pathways
Subjects:T Technology > TA Engineering (General). Civil engineering (General)
Divisions:Civil Engineering
ID Code:107556
Deposited By: Widya Wahid
Deposited On:23 Sep 2024 06:10
Last Modified:23 Sep 2024 06:10

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