Global climate models (GCMs) generally use mathematical equations derived from physical principles to simulate atmospheric circulation and global climate(Wright et al., 2015). The GCMs are continuously upgraded to improve their reliability by adopting new physical processes and reliable data (Zamani et al., 2020; Nie et al., 2020). Intergovernmental Panel on Climate Change (IPCC) coordinates the updates through Coupled Model Intercomparison Projects (CMIP). The CMIP6 is the latest version that consists of state-of-the-art GCMs with a broader range of experiments to provide a wider variety of scientific questions (Gusain et al., 2020; Narsey et al., 2020; Rivera and Gabriel, 2020). CMIP6 also differs from earlier phases in terms of new future scenarios named shared socioeconomic pathways (SSPs) derived according to different socioeconomic assumptions (O'Neill et al., 2016; Veronika et al., 2016; Yukimoto et al., 2019; Boucher et al., 2020).
The SSP119 is a new scenario that provides climate simulation for global warming below 1.5ºC by 2100 compared to preindustrial levels. This mildest scenario offers an understanding of the least likely climate changes. SSP126 provides a climate simulation for global warming of 2ºC by 2100 (O'Neill et al., 2016). Projections for SSP119 and SSP126 can tell how climate will change for 1.5ºC and 2.0ºC temperature rise scenarios and how the change can be due to a further rise of temperature by 0.5ºC. Studies in different parts of the globe showed significant changes in rainfall and disaster risk due to 0.5°C more warming of the globe (Hulme, 2016; Mitchell et al., 2016). Population under heatwaves are projected to increase from 14% in 1.5°C warming scenario to 37% in 2°C warming scenario. Nearly 61 million more people will be in water scarcity for a 2°C warming than a 1.5°C warming. About 32 to 80 million people would be exposed to flooding from sea-level rise under 2°C compared to 31 to 59 million under a 1.5°C warming ( James et al., 2017; Hoegh-Guldberg et al., 2018; Schleussner et al., 2016).
The impact of half-degree more warming would not be the same over the globe (Mitchell et al., 2016). The effect may be more visible in tropical monsoon rainfall countries due to significant sea surface temperature variability. The impact will also be more in highly populated but less developed countries where a small change in droughts or floods may affect a large amount of population. Governments of those countries need to revise the climate change adaptation strategies based on projections for these scenarios. However, possible consequences for 1.5º and 2.0ºC temperature rise are still not available in many developing countries. Such projections are specifically significant for the regions where a small rise in global temperature can cause a large change in the climate. Besides, those are required for vulnerable countries where climate changes can have severe implications.
Bangladesh is highly susceptible to any small changes in climate due to its high dependency on agriculture and the recurrence of hydrological hazards like floods and droughts (Mohsenipour et al., 2018). The damage risk to a moderate hydrological hazard is very high for the country due to high population density and low adaptation capability. Understanding possible changes in climate are the key to developing adaptation policies and building climate resiliency. Therefore, a considerable amount of research has been conducted to project possible changes in rainfall and temperature for different climate change scenarios (Alamgir et al., 2019; Alamgir et al., 2020; Khan et al., 2020; Mondal et al., 2020; Mortuza et al., 2019; Pour et al., 2018; Xu et al., 2019). All the previous studies used GCMs of CMIP5 or the earlier versions to project climate for different RCP or SRES scenarios. No study has been conducted until now to evaluate climate change for SSP scenarios using CMIP6 models. Almazroui et al. (2020) projected precipitation and temperature changes over South Asia using CMIP6 models at a resolution 1º×1º grid. Due to coarse resolution, it was not possible to understand the regional changes in Bangladesh's climate from their projections. Besides, the changes in seasonal rainfall and rainfall distribution have not been evaluated in their study.
The objective of this is to employ CMIP6 GCMs for the projection of spatiotemporal changes in precipitation and droughts in Bangladesh for SSP119 and SSP126 scenarios to appraise the least possible alterations in droughts and its variability due to 0.5ºC further rise of global temperature. Six CMIP6 models released so far, which have projections for both SSP119 and SSP126 scenarios, were used in this study. The projected rainfall was used to assess the future spatiotemporal scenarios of drought frequency in Bangladesh. The results presented in the article have the potential to be used for adaptation planning for building a climate-resilient society.