<ul><li>TelePiT is a new deep learning architecture designed for improved global Subseasonal-to-Seasonal (S2S) forecasting.</li><li>It integrates multi-scale physics and teleconnection awareness to tackle the challenges of modeling complex atmospheric systems and interactions across different scales.</li><li>TelePiT comprises Spherical Harmonic Embedding, Multi-Scale Physics-Informed Neural ODE, and Teleconnection-Aware Transformer as its key components.</li><li>Extensive experiments show that TelePiT outperforms existing data-driven models and operational weather prediction systems, achieving a significant 57.7% reduction in RMSE for 2-meter temperature forecasts.</li></ul>

Physics-Informed Teleconnection-Aware Transformer for Global Subseasonal-to-Seasonal Forecasting

Discover more