Wavelet Analysis of Meteorological Data Collected by an Automated Microcontroller-Weather Station System

The present paper reports the findings obtained through a wavelet analysis, applied to meteorological data collected by means of a LSI-LASTEM weather-station, connected to a microcontroller. For the data collection, the station was located at the Polo Papardo of Messina University (38° 15’ 35.10’’ N latitude and 15° 35’ 58.86’’ E longitude), while a multi-scale wavelet approach was employed for the data analysis. The first part of the work is addressed to the data acquisition system description, which also includes the sensors and the remote microcontroller. Then, the wavelet protocol is introduced and applied by means of both continuous and discrete wavelet transforms; this method provides a time frequency representation of the analyzed signals, capable of highlighting the correlation among the registered meteorological parameters. The analysis through the evaluated wavelet scalograms shows that for all the months a positive correlation between maximum temperature and minimum temperature exists whereas, contrarily to what in most cases occurs, a constant negative correlation exists between daily rainfall and maximum temperature as well as daily rainfall and minimum temperature.