Your question corresponds to a point from a classic lecture course on periodic signal analysis. It's unclear why you're asking it in such a generalized form ;)

I asked the following open ended question because I am expecting the following response from others which can easily be attributed to research question:

Fourier transformation is pertinent in detecting and delineating rhythms contained in meteorological findings. It primarily translates the intricate time series into the frequency domain, making recurring trends clearer. This allows climate scientists to separate and discern central frequencies associating with different phenomena e.g. recurrent shapes, El Niño–Southern Oscillation, and longer time oscillations. It is accomplished by breaking down climatic dimensions, precipitation, or air impulse records into constructing sinusoids. Extracting these harmonious waves from non-standard changes and interference, Fourier analysis is crucial to comprehend the diversity of meteorological phenomena, estimate the future course, and measure the influence of external forces. Besides, this approach plays a fundamental role in creating models that incorporate the time organization of meteorological procedures. This enhances the foundation of both descriptive and anticipative meteorology.