Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN)

PERSIANN is a system that uses satellite images and artificial neural networks—computers modeled after the human brain—to estimate rainfall. It analyzes cloud patterns, temperature, and other weather data captured from space to predict how much rain is falling in a specific area. This method allows for timely and accurate monitoring of precipitation, especially in regions where ground-based measurements are scarce. By leveraging satellite observations and advanced computer models, PERSIANN provides valuable information for weather forecasting, water management, and disaster preparedness.