Seasonal variability in climate time series in Rajshahi division, Bangladesh

Md. Nezam Uddin; Syed Mustafizur Rahman; Md. Sultan-Ul- Islam; Md. Shuzon Ali; Md. Abdullah Al Mamun

doi:10.15625/0866-7187/42/1/14755

Author affiliations

Authors

Md. Nezam Uddin Institute of Environmental Science, University of Rajshahi, Rajshahi-6205, Bangladesh
Syed Mustafizur Rahman Geophysics Lab, Department of Electrical and Electronic Engineering, University of Rajshahi, Rajshahi-6205, Bangladesh
Md. Sultan-Ul- Islam Department of Geology and Mining, University of Rajshahi, Rajshahi-6205, Bangladesh
Md. Shuzon Ali Department of Mathematics, Bangabandhu Sheikh Mujibur Rahman Science and Technology Universi-ty, Gopalgonj-8100, Bangladesh
Md. Abdullah Al Mamun Department of Mathematics, Bangladesh Army University of Engineering and Technology, Natore-6431, Bangladesh

DOI:

https://doi.org/10.15625/0866-7187/42/1/14755

Keywords:

Hilbert transform, dry season, wet season, seasonal variability, fourier transform, seasonal boundary

Abstract

This work has presented yearly dry and wet seasons in the analysis of 28 years daily recorded temperature, relative humidity and rainfall data from 1988 to 2015 in Rajshahi division, Bangladesh using Hilbert frequency analysis. Analysis has estimated the seasonal boundaries in time according to the instantaneous frequency in cycles/day and the estimations are verified with studying power spectrum of the time series. Two boundaries are obtained in each analysis over the average of yearly analysis of four years. Obtained seasonal boundaries on 16 March and 20 October are indicated as the differentiator of wet season comprises of pre-monsoon and rain in each year. Results have also shown that the length of the wet season is varying ±11days. Estimations have further justified with average rainfall distribution as shown in this work. It is even difficult to differentiate rainy season in rainfall data, however, the estimated wet season using Hilbert analysis well supported the rainy season over temperature and humidity. The presented analysis may assist further to learn more about the seasonal variability in climate dynamics.

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