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ANALYSIS OF TEMPERATURE TREND IN KHULNA DISTRICT OF BANGLADESH.

Authors :
Jahan, Md. Sarwar
Nishita, Sanjida Akter
Tamim, Afifa
Abdullah Al Mamun, S. M.
Source :
Environment & Ecosystem Science (EES); 2024, Vol. 8 Issue 2, p134-142, 9p
Publication Year :
2024

Abstract

This study examines the trends in monthly maximum, minimum, and average temperatures over a 20-year period (2003-2022) in Khulna district, Bangladesh. The temperature data were sourced from the Regional Inspection Center (R.I.C) of the Bangladesh Meteorological Department, Gollamary, Khulna. The aim was to assess temperature deviations in the district over time. Using linear trend analysis, long-term temperature changes were evaluated. The annual mean maximum, minimum, and average temperatures showed increasing trends when plotted against the years, though the year-to-year variability was not statistically significant. The regression equations obtained for maximum, minimum, and average temperatures were: (y = 0.0251x - 19.006, R² = 0.1525), (y = 0.0177x - 8.789, R² = 0.1492), and (y = 0.0098x + 2.5477, R² = 0.0476), respectively. A bimodal dispersion pattern was observed across all three temperature aspects throughout the months during 2003-2022. Monthly temperatures (maximum, minimum, and average) did not follow a consistent pattern, as shown by the linear regression analysis, with both increasing and decreasing trends identified over the two decades. May was found to be the warmest month, while January was the coldest when considering mean monthly maximum and average temperatures. Furthermore, the highest upsurge in mean monthly average temperature was recorded in July (0.0539°C), while the bulk reduction was detected in February (0.0367°C). Principal component analysis indicated that the first two components accounted for 93% of the total variation. The study recommends further temperature monitoring methods due to observed instability in temperature. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
25210882
Volume :
8
Issue :
2
Database :
Complementary Index
Journal :
Environment & Ecosystem Science (EES)
Publication Type :
Academic Journal
Accession number :
182801688
Full Text :
https://doi.org/10.26480/ees.02.2024.134.142