Improving Ensemble Forecasts of Abnormally Deflecting Tropical Cyclones with Fused Atmosphere-Ocean-Terrain Data

1. 1Collect and preprocess atmosphere, ocean, and terrain data
2. 2Fuse the data using techniques such as concatenation or attention mechanisms
3. 3Train deep learning models on the fused data to predict tropical cyclone trajectories
4. 4Evaluate and refine the models using ensemble forecasting techniques

Data scientists and researchers on a team can benefit from this approach to improve the accuracy of tropical cyclone forecasts, while software engineers can implement the fused data approach in existing forecasting systems

💡 Fusing multiple data sources can improve the accuracy of deep learning-based tropical cyclone forecasting methods

💡 Fusing atmosphere-ocean-terrain data improves tropical cyclone forecasts