Abstract
The rise in the frequency and magnitude of extreme temperature phenomena across the globe has led to the recurrent incidence of global climate hazards, which have had severe effects on socioeconomic development. The daily maximum and minimum temperature datasets of 27 sites in Bangladesh were used to detect spatiotemporal trends of temperature extremes over Bangladesh during 1980-2017 based on ten temperature extreme indices using multi-statistical modeling namely linear regression, Pearson correlation coefficient, and factor analyses. Besides, mutation analyses based on the Mann-Kendall test, Sen's slope estimator, and Pettit test were employed to show the changing trend in extreme temperature. Results show that except for warmest days, the warm indices showed an increasing trend, mainly since the 2000s, while the growth rate was faster, and the response to global climate warming was sensitive. The cold indices were demonstrated a reverse trend since the 2010s. Diurnal temperature range (DTR) and summer days (SU) increased faster, implying that the rising speed of daily max temperature was higher than of daily min-temperature in Bangladesh. The de-trended fluctuation analysis (DFA) revealed a continuous increase in temperature extreme in the future except for cold days. The probability distribution functions (PDF) analysis revealed an evident variation of the curves in recent decades compared to the past three decades. Besides the warm night, DTR and SU primarily control the general warming trend of temperature extremes over Bangladesh during the study period. The mutation of the warm indices occurred before the cold index, indicating that the warm indices were more sensitive to global climate warming. The temperature extremes recognized in our research suggest that elevated warm temperature extremes due to global climate warming may have huge implications on the sustainable development of Bangladesh in the forthcoming period.