Replication Data for: A simple training-free acoustic approach for rainfall monitoring based on Power Spectral Density analysis

This is the current repository for the paper "A simple training-free acoustic approach for rainfall monitoring based on Power Spectral Density analysis". The main objective of the paper is the development of a simple acoustic metric that can be used for rainfall monitoring in combination with other traditional tools, such as satellite data. It contains 16 datasets in the CSV format related to the 8 research sites, and data was collected in different periods between 2023 and 2026: baseline datasets: consisting of the mean PSDs of dry-weather samples for each hour of the day. Columns are labeled with the frequency values of the mean PSDs, and the index consists of hours (0-23) psds datasets: consisting of the extracted PSDs of 7 rainfall events, selected for the analysis presented in the research, with additional rain gauge data (total_rain column, in millimeters), a column describing if the audio contains the sound of rain (True/False), and the rainfall event ID (1-7). PSD columns are labeled with the frequency values Additionally, it contains an interactive Jupyter Notebook with simple code, used to calculate the proposed acoustic metric presented in the research, and a brief explanation of the employed methodology, along with figures for a visual aid.