Weather phenomena forecasting is undergoing a significant transformation with the latest research, introducing a AI-based to atmospheric prediction. The new study, published in IEEE Transactions on Geoscience and Remote Sensing, marks the pioneering use of GNSS tomography for ensemble forecasting, setting a new pathway in the field. Traditional troposphere models often struggle with low spatial resolution and irregular data distribution. By leveraging GNSS troposphere tomography, the study generates high-resolution, three-dimensional wet refractivity fields, effectively addressing these critical challenges. Unlike previous deterministic models, the research employs ensemble forecasting using Generative Adversarial Networks (GAN), enhancing predictive accuracy by generating realistic time series data and providing probability-based forecasts. At the core of the model are Long Short Time Memory (LSTM) networks, optimized with Genetic Algorithms (GA), ensuring robust predictive performance
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