Mohamed A. El-Gebeily, Shafiqur Rehman, Luai M. Al-Hadhrami and Jaafar AlMutawa, King Fahd University of Petroleum and Minerals, Saudi Arabia
Abstract: The present study utilizes daily mean time series of meteorological parameters (air temperature, relative humidity, barometric pressure and wind speed) and daily totals of rainfall data to understand the changes in these parameters during 17 years period i.e. 1990 to 2006. The analysis of the above data is made using continuous and discrete wavelet transforms because it provides a time–frequency representation of an analyzed signal in the time domain. Moreover, in the recent years, wavelet methods have become useful and powerful tools for analysis of the variations, periodicities, trends in time series in general and meteorological parameters in particular. In present study, both continuous and discrete wavelet transforms were used and found to be capable of showing the increasing or decreasing trends of the meteorological parameters with. The seasonal variability was also very well represented by the wavelet analysis used in this study. High levels of compressions were obtained while retaining the originality of the signals.
Keywords: weather; meteorology; compression, decomposition, wavelet transform, trend analysis