4 citations · 4 across the 2 of their papers we have counts for
3 papers
physics.ao-ph2025
Data-driven global ocean model resolving ocean-atmosphere coupling dynamics
Jeong-Hwan Kim, Daehyun Kang, Young-Min Yang +2
Artificial intelligence has advanced global weather forecasting, outperforming traditional numerical models in both accuracy and computational efficiency. Nevertheless, extending p…
cs.LG2024★ 4 cited
KARINA: An Efficient Deep Learning Model for Global Weather Forecast
Minjong Cheon, Yo-Hwan Choi, Seon-Yu Kang +3
Deep learning-based, data-driven models are gaining prevalence in climate research, particularly for global weather prediction. However, training the global weather data at high re…
cs.AI2024
Advancing Data-driven Weather Forecasting: Time-Sliding Data Augmentation of ERA5
Minjong Cheon, Daehyun Kang, Yo-Hwan Choi +1
Modern deep learning techniques, which mimic traditional numerical weather prediction (NWP) models and are derived from global atmospheric reanalysis data, have caused a significan…