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Continuous and discrete wavelet transforms based analysis of weather data of North Western Region of Saudi Arabia

Continuous and discrete wavelet transforms based analysis of weather data of North Western Region... 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 continues and discrete wavelet transforms were used and found to be capable of showing the increasing or decreasing trends of the meterorological parameters with. The seasonal variability was also very well represented by the wavelet analysis used in this study. High levels of compressions were obtained retaining the originality of the signals. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png World Journal of Science, Technology and Sustainable Development Emerald Publishing

Continuous and discrete wavelet transforms based analysis of weather data of North Western Region of Saudi Arabia

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Publisher
Emerald Publishing
Copyright
Copyright © 2010 Emerald Group Publishing Limited. All rights reserved.
ISSN
2042-5945
DOI
10.1108/20425945201000023
Publisher site
See Article on Publisher Site

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 continues and discrete wavelet transforms were used and found to be capable of showing the increasing or decreasing trends of the meterorological parameters with. The seasonal variability was also very well represented by the wavelet analysis used in this study. High levels of compressions were obtained retaining the originality of the signals.

Journal

World Journal of Science, Technology and Sustainable DevelopmentEmerald Publishing

Published: Nov 1, 2010

Keywords: Weather; Meteorology; Compression; Decomposition; Wavelet transform; Trend analysis

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