Md Shah Alam
DOI: 10.59427/rcli/2025/v25.027-031
Temperature and relative humidity (RH) are two critical meteorological variables that shape weather patterns, human comfort, and climate processes. While conventional correlation techniques provide only a static relationship, wavelet analysis enables exploration of time–frequency interactions, revealing how correlations evolve across different scales. In this study, daily temperature and RH data for 2019 analyzed using statistical methods and wavelet coherence. Results show that temperature range between 14–35°C with a mean of 27.29°C, while RH varies between 21–100% with a mean of 82.39%. The overall relationship between temperature and RH is negative, with strong inverse coherence observed during the pre-monsoon summer and weaker coupling during the monsoon. The findings highlight the advantages of wavelet analysis in revealing non-stationary, scale-dependent interactions between climate variables.
Pag 027.031
