|KAMRUZZAMAN, MOHAMMAD - Bangladesh Rice Research Institute|
|WAHID, SHAHRIAR - Csiro, Black Mountain Laboratories|
|SHAHID, SHAMSUDDIN - University Technology Malaysia|
|ALAM, E - University Of Chittagong, Bangladesh|
|MAINUDDIN, MOHAMMED - Csiro, Black Mountain Laboratories|
|ISLAM, H.M TOUHIDUL - Begum Rokeya University|
|CHO, JEAPIL - International Water Management Institute (IWMI)|
|RAHMAN, MIZANUR - Bangladesh Rice Research Institute|
|BISWAS, JATISH CHNADRA - Krishi Gobeshona Foundation (KGF)|
Submitted to: Heliyon
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/11/2023
Publication Date: 5/13/2023
Citation: Kamruzzaman, M., Wahid, S., Shahid, S., Alam, E., Mainuddin, M., Islam, H., Cho, J., Rahman, M., Biswas, J., Thorp, K.R. 2023. Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs. Heliyon. 9(5). Article e16274. https://doi.org/10.1016/j.heliyon.2023.e16274.
Interpretive Summary: Global climate models are continuously updated to provide more accurate predictions of future climate conditions across the globe. Among the nations of the world, Bangladesh is a developing country that is considered vulnerable to climate change, particularly in terms of extreme weather events. This study evaluated future climate predictions across Bangladesh using data from recently updated global climate models. Spatial and temporal trends in predictions of future precipitation and maximum and minimum air temperatures were analyzed for different time periods, seasons, and socioeconomic pathways. Results of the study will be useful for intergovernmental agencies focusing on mitigation of climate change threats to food security.
Technical Abstract: Understanding spatiotemporal variability in precipitation and temperature and their future projections is critical for assessing environmental hazards and planning long-term mitigation. 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. The post-monsoon season was predicted to experience the most significant increase in precipitation (41.6%) in the far future for SSP5-8.5. In contrast, winter precipitation was predicted to decrease most (15.0%) in the mid-future for SSP3-7.0. 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.