Machine Learning Applications Across the Weather Forecasting Value Chain

Traditional numerical weather prediction (NWP) models have made remarkable progress over the past few decades. Yet, as we inch closer to the limits of deterministic forecasting, there remains a growing need for innovative techniques to enhance forecast accuracy. Enter machine learning (ML) — a subset of artificial intelligence that is causing a paradigm shift in meteorological forecasting. This presentation offers a comprehensive overview of the latest advancements in the application of machine learning at Tomorrow.io across the weather forecasting value chain. There will be a focus on a core algorithm that post-processes NWP data with a multi-task neural network with a Continuous Ranked Probability Score (CRPS) custom loss function to generate probabilistic forecasts, but will also cover ML techniques used in short-term nowcasting and generative AI to summarize weather impact for customers.