Atmospheric Parameter Forecasting for Optical Channel Characterization

This project aimed to enhance optical communication by forecasting atmospheric parameters. The focus was on two main tasks: Weather Forecasting and Predicting Atmospheric Coherence Length (r0). For Weather Forecasting, a sequence-to-sequence approach was used to predict temperature, air pressure, relative humidity, and wind speed at JPL weather stations. A GRU model achieved a 25% reduction in prediction errors for temperature and pressure, while more complex architectures were used for wind speed and humidity. Predicting r0 was challenging due to its high variability, but a hybrid approach combining analytically predicted r0 with a simple GRU model improved nowcasting accuracy. The best models were deployed for live weather forecasting at JPL stations, demonstrating their practical applicability.