Wavelet based correlation coefficient of time series of Saudi Meteorological Data S. Rehman a, * , A.H. Siddiqi b a Center for Engineering Research, Research Institute, King Fahd University of Petroleum and Minerals, Dhahran-31261, Saudi Arabia b Department of Mathematical Sciences, King Fahd University of Petroleum and Minerals, Dhahran-31261, Saudi Arabia Accepted 18 June 2007 Abstract In this paper, wavelet concepts are used to study a correlation between pairs of time series of meteorological param- eters such as pressure, temperature, rainfall, relative humidity and wind speed. The study utilized the daily average val- ues of meteorological parameters of nine meteorological stations of Saudi Arabia located at different strategic locations. The data used in this study cover a period of 16 years between 1990 and 2005. Besides obtaining wavelet spectra, we also computed the wavelet correlation coefficients between two same parameters from two different locations and show that strong correlation or strong anti-correlation depends on scale. The cross-correlation coefficients of meteorological parameters between two stations were also calculated using statistical function. For coastal to costal pair of stations, pressure time series was found to be strongly correlated. In general, the temperature data were found to be strongly correlated for all pairs of stations and the rainfall data the least. Ó 2007 Elsevier Ltd. All rights reserved. 1. Introduction Major changes are likely to be experienced in the arid and semi-arid regions in the coming few decades as pointed out by Warren et al. [30]. Furthermore, the changes will be induced by increasing human pressure like exponential pop- ulation growth, continuing fossil fuel usage and ambitious water development projects. The actions of the human beings on the ecosystems cause the climatic changes. Climatic changes strongly affect the process of desertification by its impact on the vegetation, soil and hydrological cycle as stated by Pimenta et al. [22]. The changes in climate directly change the temperature, wind speed, barometric pressure and rain fall, see [25]. The climate variability and cli- mate changes have been studied based on the analysis of different climatic variables. Temperature and rainfall time-ser- ies are commonly used to study the climatic changes as seen from Elagib and Mansell [14], Lazaro et al. [20] and Moonen et al. [21], etc. Investigators from around the world have investigated climatic change such as Balling and Brazel [8] for United States of America, Jose et al. [16] for Philippines, Elagib and Abdu [13] for The Kingdom of Bahrain, Arnell [4] for 0960-0779/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.chaos.2007.06.054 * Corresponding author. Tel.: +966 3 8603802; Mobile: +966 502085496; fax: +966 3 860 3996. E-mail address: srehman@kfupm.edu.sa (S. Rehman). URL: http://faculty.kfupm.edu.sa/ri/srehman (S. Rehman). Chaos, Solitons and Fractals 39 (2009) 1764–1789 www.elsevier.com/locate/chaos