TREND ANALYSIS OF RELATIVE HUMIDITY IN KHULNA OF BANGLADESH FROM HISTORICAL DATA

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Bangladesh, despite having a subtropical climate, is characterized by dry winters and hot summers, ranks top among the most vulnerable countries to climate change. In recent years, climate change has drawn significant attention from academics, researchers, and policymakers worldwide. This study examines the trends in annual and monthly relative humidity in Khulna, Bangladesh, over a 15-year period (2007-2021). Its aim is to provide updated insights into weather patterns, particularly relative humidity, in Khulna. Secondary data on rainfall, temperature, and relative humidity were obtained from the Regional Inspection Center (RIC) of the Bangladesh Meteorological Department in Gollamary, Khulna. Mean, standard deviation (SD), and coefficient of variation (CV), were calculated to assess the annual and monthly distribution of relative humidity. Trend analyses were conducted applying bivariate analysis, and linear regression was utilized to examine the relationship between relative humidity and time. The associations between relative humidity and temperature, as well as between relative humidity and rainfall, were also assessed. Additionally, annual and monthly thermal heat index (THI) values were calculated. The findings revealed that annual relative humidity remained relatively stable, with minimal deviation across the years. Mean monthly relative humidity fluctuated significantly, ranging from 71.60% to 87.27%, following a tri-modal distribution pattern. When plotted against years, annual relative humidity showed a negative but non-significant trend (y = – 0.0823x + 245.86, R2 = 0.0646). Most months showed a declining trend in average relative humidity, with the most substantial and statistically significant reduction occurring in September. THI levels were generally uncomfortable for the human body across most months and years. Monthly average relative humidity displayed a negative relationship with mean monthly temperature and a positive association with mean monthly rainfall. Both relationships were found to be statistically significant (p &lt 0.001). This study highlights the urgent need for adaptive strategies to ensure sustainable agricultural productivity in Khulna and recommends improved monitoring systems due to the variability and uncertainty in relative humidity patterns.