There is a fundamental presentational problem in discussing how to examine the evidence of cyclic behaviour in any stream of data recorded at regular intervals. This is that such examination usually requires some ferocious statistical analysis. Whether we are considering weather data or any other data recorded at set times (e.g. economic series), there is no way we can avoid this statistical approach. But to make it easier to present the underlying analytical techniques, the mathematics will be kept to a minimum in this chapter. This approach does, however, run the risk of glossing over the complexities of the analysis and giving the impression that the statistics can be put on one side. So to understand the problems of sifting through the evidence it is necessary to consider not only the description provided in this chapter but also the basic mathematics given in Appendix A. Failure to recognise the need for mathematical rigour can result in the reader being led up the garden path. It is important to belabour this unpalatable fact, as many of the published examples of ‘weather cycles’ have wittingly or unwittingly been the product of superficial or selective analysis of the available data.

Bearing in mind these words of warning, we must now consider the examination of the evidence of weather cycles. As explained in Chapter 1, the scale of the effort that has been devoted to the search for cycles is massive.