5 citations · 10 across the 18 of their papers we have counts for
3 papers · 1 filter
Deep Generative Data Assimilation in Multimodal Setting
Yongquan Qu, Juan Nathaniel, Shuolin Li +1
Robust integration of physical knowledge and data is key to improve computational simulations, such as Earth system models. Data assimilation is crucial for achieving this goal bec…
Joint Parameter and Parameterization Inference with Uncertainty Quantification through Differentiable Programming
Yongquan Qu, Mohamed Aziz Bhouri, Pierre Gentine
Accurate representations of unknown and sub-grid physical processes through parameterizations (or closure) in numerical simulations with quantified uncertainty are critical for res…
ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction
Juan Nathaniel, Yongquan Qu, Tung Nguyen +4
Accurate prediction of climate in the subseasonal-to-seasonal scale is crucial for disaster preparedness and robust decision making amidst climate change. Yet, forecasting beyond t…