A statistical validation for the cycles found in air temperature data using a Morlet wavelet-based method

Recently, new cycles, associated with periods of 30 and 43 months, respectively, have been observed by the authors in surface air temperature time series, using a wavelet-based methodology. Although many evidences attest the validity of this method applied to climatic data, no systematic study of its efficiency has been carried out. Here, we estimate confidence levels for this approach and show that the observed cycles are significant. Taking these cycles into consideration should prove helpful in increasing the accuracy of the climate model projections of climate change and weather forecast.