2 papers
cs.CV2025
Knowledge-Guided Machine Learning: Illustrating the use of Explainable Boosting Machines to Identify Overshooting Tops in Satellite Imagery
Nathan Mitchell, Lander Ver Hoef, Imme Ebert-Uphoff +4
Machine learning (ML) algorithms have emerged in many meteorological applications. However, these algorithms struggle to extrapolate beyond the data they were trained on, i.e., the…
eess.SP2024
SRViT: Vision Transformers for Estimating Radar Reflectivity from Satellite Observations at Scale
Jason Stock, Kyle Hilburn, Imme Ebert-Uphoff +1
We introduce a transformer-based neural network to generate high-resolution (3km) synthetic radar reflectivity fields at scale from geostationary satellite imagery. This work aims…