In this paper, 10-year meteorological data observed at Taipei, Taiwan, from 2006 to 2015, are studied to investigate the inherent correlation between renewable resources. The data are investigated in the time frequency space using wavelet analysis including wind speed, global solar radiation and air temperature. Through the wavelet transform of the time series, the related cross wavelet transform, wavelet coherence and phase angle are obtained. The results show that the wavelet power spectra exhibit prominent oscillations at annual and half-year periods for the three kinds of meteorological data, while some oscillations for other periods do not show a regular pattern. Wind speed spectrum is more irregular than the other two types of data due to climatic and geographic factors, whereas temperature has the most regular form. From the cross wavelet transform of data pairs, it is seen wind speed and solar radiation have an anti phase correlation, implying that wind and solar energy can be used in complementary roles in electricity generation in this region. The results of wavelet analysis coincide with the variation trend of the monthly mean of the meteorological data over the 10-year period. Wavelet analysis is a robust tool for the oscillation characteristic study on time series data. (C) 2016 Elsevier Ltd. All rights reserved.