3 papers
physics.ao-ph2026
Event-Aware Loss Design for Forecasting of Convective Precipitation and Lightning
ChangJae Lee, Heecheol Yang, Byeonggwon Kim
Accurate forecasting of high-impact weather, specifically extreme precipitation and lightning, remains a significant challenge in numerical weather prediction (NWP) due to the comp…
physics.ao-ph2025
Exploring Multimodal AI Reasoning for Meteorological Forecasting from Skew-T Diagrams
ChangJae Lee, Heecheol Yang, Jonghak Choi
Forecasting from atmospheric soundings is a fundamental task in operational meteorology, often requiring structured visual reasoning over Skew-T log-P diagrams by human forecasters…
physics.ao-ph2025
Improving Post-Processing for Quantitative Precipitation Forecasting Using Deep Learning: Learning Precipitation Physics from High-Resolution Observations
ChangJae Lee, Heecheol Yang, Byeonggwon Kim
Accurate quantitative precipitation forecasting (QPF) remains one of the main challenges in numerical weather prediction (NWP), primarily due to the difficulty of representing the…