This paper is an annotated review of variance spectrum analysis. Faced with the impossible task of reviewing here the technique, providing illustrative examples from the field of hydrology, and providing learned insight into the uses of these techniques that are likely to be productive, I make no apology for the material included and omitted. The researcher with the appropriate problem and the ability to perceive that this or that particular tool is suited to the solution of that problem is the researcher who advances the science. It is my hope that the discussion and examples contained in this review will stimulate workers to acquaint themselves with spectral techniques and thereby prepare themselves to choose those problems in time (or space) series for which the techniques are suited. Spectrum and cross‐spectrum analyses are useful in analyzing the random or stochastic components in a time (or space) series. For certain problems auto‐ or cross‐correlation analysis may be most attractive, and for others spectrum analysis might be more appropriate.