A Study on the Heat Wave Conditions over Bangladesh During 1990 - 2019
DOI:
https://doi.org/10.3329/jes.v14i2.71227Keywords:
Extreme temperature, Heat wave, Mann-Kendall test, Pre-monsoon, Severe conditionsAbstract
When temperature exceed 36 degrees with a large area and linger for minimum three or more days can be considered as heat wave (HW). In the Pre-monsoon, the sun ray drops down on the ‘Thar’ desert (India) and the foothill of the Himalayas vertically, the area makes a hot-tempered zone. That is why, these regions produce a trough of low and there is a possibility to advect temperature towards Bangladesh. The south/south westerly wind carries a high amount of moisture over Bangladesh. The heat capacity of moisture is higher than that of dry air. Solar insulation, temperature advection and moisture incursion are three main phenomena that are responsible for HW condition. Veering is also responsible for especially severe and very severe HW conditions. The present study is accompanying with all category’s frequency of heat wave days (HWD) and HW for the Pre-monsoon (March to May) over most of the stations (34) of Bangladesh for the period 1990-2019. Microsoft excel, Surfer and Arc GIS software have been used for data calculation, however, linear trend analysis and Mann-Kendall test have been used to draw the trend of HW frequency. The highest numbers of HWD are found in Jashore (30.9 days) of all types of events whereas the highest frequencies of HW are found in Rajshahi (4.2333) during pre-monsoon season. The lowest numbers of frequency of HWD and HW, both are found at Chattogram. April is the hottest month in Bangladesh. On the basis of frequency of HWD, the obtained highest hot places are Jashore, Chuadanga, Rajshahi, Ishurdi and Satkhira. while in Kutubdia and Teknaf, no HW is found at all. Among 30 years, 2014 is found the hottest year and 2018 is the recorded lowest hot year. By Mann-Kendall test, the HW trend of M. Court, Mongla, Patuakhali and Chandpur have indicated positive significant value, and Mymensing station has given only negative significant value. From spatial distribution, it shows the hottest areas which are south western and middle-western parts of Bangladesh.
Journal of Engineering Science 14(2), 2023, 59-67
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