2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 2 cited
A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics
Junqi Yin, Siming Liang, Siyan Liu +4
The weather and climate domains are undergoing a significant transformation thanks to advances in AI-based foundation models such as FourCastNet, GraphCast, ClimaX and Pangu-Weathe…
physics.ao-ph2022
A Spatiotemporal-Aware Climate Model Ensembling Method for Improving Precipitation Predictability
Ming Fan, Dan Lu, Deeksha Rastogi +1
Multimodel ensembling has been widely used to improve climate model predictions, and the improvement strongly depends on the ensembling scheme. In this work, we propose a Bayesian…