2 citations · 2 across the 2 of their papers we have counts for
2 papers
physics.ao-ph2026
OCELOT: Direct Atmospheric Forecasting from Heterogeneous Earth Observations Using a Graph-Transformer Hybrid Model
Azadeh Gholoubi, Ronald McLaren, Mu-Chieh Ko +7
This study presents OCELOT (Observation-Centric Estimation and Learning for Outlook Trajectories), a global machine-learning forecasting system that predicts future Earth observati…
physics.ao-ph2024★ 2 cited
Exploring the Use of Machine Learning Weather Models in Data Assimilation
Xiaoxu Tian, Daniel Holdaway, Daryl Kleist
The use of machine learning (ML) models in meteorology has attracted significant attention for their potential to improve weather forecasting efficiency and accuracy. GraphCast and…