Background: Recent analysis indicates that the number of cases of Dengue Fever may be as high as 400 million/year in the world. In 2015, according to the Brazilian Ministry of Health, there were 1,621,797 probable cases of Dengue in the country, including all classifications except discarded notifications, and this is the highest number recorded on the historical series since 1990. Many studies have found associations between climatic factors and dengue transmission, specifically to understand the frequency and periodicity of epidemiological cycles dependent on those factors, main purpose of this study. Methods & Materials: In this work, Wavelet Transform based in Morlet function was applied to observed data to characterize the space-time frequency distributions of Dengue Fever incidence, following the gradual change of the atmospheric forcing, for all the Brazilian Northeast capitals, from Jan 2001 to Dec 2012. This allows a spectral description those distributions of dengue epidemics in this area. Results: The Wavelet Transform analysis shows the persistence of Dengue Fever incidence on annual cycle (12-month periods) in all capitals studied. Concomitantly, there is significant periodicity observed between 3.6 and 4.6 years, characterizing the higher Dengue Fever incidence occurrences. Recife, Aracaju and Salvador cities show similar pattern of epidemiological distribution. Indeed, the application of biwavelet permitted the investigation of the relationship between Dengue incidence and climatic variables observed at surface, considering periodicity, frequency and phase-coherence between times series. Significant periodicities of meteorological variables are reflected on incidences, with well-defined nuclei, characterizing periods of higher infection. For instance, in Aracaju, the cross-wavelet power spectrum has shown simultaneous annual phase of the occurrences of dengue and rainfall with subscale of 3 to 4 months, particularly between 2007-2010, showing the sensibility power of the biwavelet technique to covariance and correlation analysis. Conclusion: Based on the review, it is proposed the use of wavelets to relate dengue incidence to climatic variables, considering the space-time frequencies. The model can serve for the understanding of the periodicity of dengue epidemiological peaks, specifically in the capitals of the Northeast of Brazil, with occurrence of 3.6 to 4 years, analysis unprecedented in the literature for this region.