A spectral analysis of meteorological data for weather forecast applications
Eros Gian Alessandro Pasero, Alfonso Montuori, Giovanni Raimondo · PORTO Publications Open Repository TOrino (Politecnico di Torino) · 2006
The great majority of natural signals are not stationary and they undergo transients which include a large range of frequencies in a short period of time. Fourier Transform is not sufficient to process this kind of signals because all the information on time location of a certain frequency is lost in the analytical process. The complexity of climate variability on all time scales requires the use of several refined tools to unravel its primary dynamics from observations. The analysis of the temporal series has shown that climatic variations are extremely irregular in the time-space domain. This feature makes them difficult to be foreseen if no particular mathematical tools are used. The aim of this paper is to describe how to analyze and represent climatic signals in order to foresee their future short-time evolution for weather nowcasting. A spectral analysis of the meteorological data is described. More precisely the purpose of the spectral analysis is the determination of the optimum sampling frequency for a set of climatic not stationary signals and the description of an algorithm for the automatic adjustment of such a frequency.