Climate extremes have a significant impact on vegetation. However, little is known about vegetation response to climatic extremes in Bangladesh. The association of Normalized Difference Vegetation Index (NDVI) with nine extreme precipitation and temperature indices was evaluated to identify the nexus between vegetation and climatic extremes and their associations in Bangladesh for the period 1986-2017. Moreover, detrended fluctuation analysis (DFA) and Morlet wavelet analysis (MWA) were employed to evaluate the possible future trends and decipher the existing periodic cycles, respectively in the time series of NDVI and climate extremes. Besides, atmospheric variables of ECMWF ERA5 were used to examine the casual circulation mechanism responsible for climatic extremes of Bangladesh. The results revealed that the monthly NDVI is positively associated with extreme rainfall with spatiotemporal heterogeneity. Warm temperature indices showed a significant negative association with NDVI on the seasonal scale, while precipitation and cold temperature extremes showed a positive association with yearly NDVI. The DEA revealed a continuous increase in temperature extreme in the future, while no change in precipitation extremes. NDVI also revealed a significant association with extreme temperature indices with a time lag of one month and with precipitation extreme without time lag. Spatial analysis indicated insensitivity of marshy vegetation type to climate extremes in winter. The study revealed that elevated summer geopotential height, no visible anticyclonic center, reduced high cloud cover, and low solar radiation with higher humidity contributed to climatic extremes in Bangladesh. The nexus between NDVI and climatic extremes established in this study indicated that increasing warm temperature extremes due to global warming might have severe implications on Bangladesh's ecology and the environment in the future.
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.
This study evaluates the potential impacts of climate change on Bangladesh by analyzing 19 bioclimatic indicators based on temperature and precipitation. Data from 18 bias-corrected CMIP6 global climate models (GCMs) were used, covering four Shared Socioeconomic Pathways (SSPs)-SSP126, SSP245, SSP370, and SSP585-across three future timeframes: near-term (2015-2044), mid-term (2045-2074), and long-term (2075-2100). Under the high-emission SSP585 scenario, average temperatures are projected to rise by up to 3.76 °C, and annual precipitation could increase by 52.6%, reaching up to 3446.38 mm by the end of the century. The maximum temperature (Bio5) could reach 32.91 °C, while the minimum temperature (Bio6) might rise by 4.43 °C, particularly during winter. Precipitation seasonality (Bio15) is projected to increase by as much as 7.9% in the northwest, indicating heightened variability between wet and dry seasons. The diurnal temperature range (Bio2) is expected to decrease by up to - 1.3 °C, signifying reduced nighttime cooling, which could exacerbate heat stress. Significant reductions in temperature seasonality (Bio4) are forecast for the northeast, with notable declines in isothermality (Bio3) under SSP585, pointing to increased climatic extremes. These climatic shifts pose severe risks to agricultural productivity, water resource availability, and biodiversity, particularly in flood-prone regions. The findings highlight the need for urgent adaptation measures, including improved flood management systems, efficient water resource use, and climate-resilient agricultural practices. By providing robust region-specific projections, this study offers critical insights for policymakers and stakeholders to mitigate the adverse effects of climate change and safeguard environmental and economic sustainability in Bangladesh.