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This paper proposes a heat-wave definition for Bangladesh that could be used to trigger preparedness measures in a heat early warning system (HEWS) and explores the climate mechanisms associated with heat waves. A HEWS requires a definition of heat waves that is both related to human health outcomes and forecastable. No such definition has been developed for Bangladesh. Using a generalized additive regression model, a heat-wave definition is proposed that requires elevated minimum and maximum daily temperatures over the 95th percentile for 3 consecutive days, confirming the importance of nighttime conditions for health impacts. By this definition, death rates increase by about 20% during heat waves; this result can be used as an argument for public-health interventions to prevent heat-related deaths. Furthermore, predictability of these heat waves exists from weather to seasonal time scales, offering opportunities for a range of preparedness measures. Heat waves are associated with an absence of normal premonsoonal rainfall brought about by anomalously strong low-level westerly winds and weak southerlies, detectable up to approximately 10 days in advance. This circulation pattern occurs over a background of drier-than-normal conditions, with below-average soil moisture and precipitation throughout the heat-wave season from April to June. Low soil moisture increases the odds of heat-wave occurrence for 10-30 days, indicating that subseasonal forecasts of heat-wave risk may be possible by monitoring soil-moisture conditions. [ABSTRACT FROM AUTHOR]

The present study is aimed at examining the rainfall changes and their relationship to vegetation dynamics in the central-coastal region of Bangladesh. Different statistical tests were used in the study to investigate the rainfall changes, such as the Mann-Kendall test and Sen's slope estimation. The normalized difference vegetation index (NDVI) time series were collected from Google Earth Engine and processed in R programming to examine the level and extent of vegetation coverage. A correlation analysis was used to determine the association between the total rainfall (June–September) and mean NDVI (October–November). Results depict that annual rainfall decreased in all the stations, with the highest values in Senbag (Z = -5.16 and Q = 55.24). The post-monsoon variability exhibited an increasing trend in the majority of the stations, whereas other seasons showed a decreasing trend with the highest values in Feni (pre-monsoon Z = -2.37 and monsoon Z = -2.49). The relationship between rainfall and vegetation dynamics (NDVI) was observed, which was a moderate to strong positive lag correlation throughout the region. It was also noticed that the locations with higher rainfall fluctuations have a weaker association with the NDVI. Reduced rainfall can reduce vegetation productivity by disrupting growth seasons, lowering soil water content, and increasing salinity in the area. It is expected that the findings will contribute to a better understanding of the impacts of climate change induced rainfall variability and the response of the vegetative environment to it. [ABSTRACT FROM AUTHOR]