3 papers
cs.LG2025
Discovering Spatial Correlations of Earth Observations for weather forecasting by using Graph Structure Learning
Hyeon-Ju Jeon, Jeon-Ho Kang, In-Hyuk Kwon +1
This study aims to improve the accuracy of weather predictions by discovering spatial correlations between Earth observations and atmospheric states. Existing numerical weather pre…
cs.AI2024
Explainable Graph Neural Networks for Observation Impact Analysis in Atmospheric State Estimation
Hyeon-Ju Jeon, Jeon-Ho Kang, In-Hyuk Kwon +1
This paper investigates the impact of observations on atmospheric state estimation in weather forecasting systems using graph neural networks (GNNs) and explainability methods. We…
cs.LG2024
CloudNine: Analyzing Meteorological Observation Impact on Weather Prediction Using Explainable Graph Neural Networks
Hyeon-Ju Jeon, Jeon-Ho Kang, In-Hyuk Kwon +1
The impact of meteorological observations on weather forecasting varies with sensor type, location, time, and other environmental factors. Thus, quantitative analysis of observatio…