Abstract
The present study is about the analysis of mean maximum and mean minimum temperatures carried out on annual, seasonal, and monthly timescales examining the data from 15 meteorological stations in Bangladesh for the period 1961–2008. Various spatial and statistical tools were used to display and analyze trends in temperature data. ArcGIS was used to produce the spatially distributed temperature data by using Thiessen polygon method. The nonparametric Mann–Kendall test was used to determine whether there is a positive or negative trend in data with their statistical significance. Sen’s method was also used to determine the magnitude of the trends. The results reveal positive trends in annual mean and mean maximum temperatures with 95 % significance. Trend test reveals that the significant positive trend is found in June to November in case of mean maximum temperature, but according to the mean minimum temperature, the situation is different and a significant positive trend was found from November to February. The analysis of the whole record reveals a tendency toward warmer years, with significantly warmer summer periods and slightly colder winters. These warming patterns may have important impacts on energy consumption, water supply, human health, and natural environment in Bangladesh.
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