Abstract
In this paper, wavelet concepts are used to study a correlation between pairs of time series of meteorological parameters such as pressure, temperature, rainfall, relative humidity and wind speed. The study utilized the daily average values 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.
| Original language | English |
|---|---|
| Pages (from-to) | 1764-1789 |
| Number of pages | 26 |
| Journal | Chaos, Solitons and Fractals |
| Volume | 39 |
| Issue number | 4 |
| DOIs | |
| State | Published - 28 Feb 2009 |
Bibliographical note
Funding Information:The authors acknowledge the support of King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia for the grant under the project INT/FRACTAL/310 to carry out this study.
ASJC Scopus subject areas
- Statistical and Nonlinear Physics
- General Mathematics
- General Physics and Astronomy
- Applied Mathematics