We successfully utilized OCLF ORNL GPU computing resources for efficient uncertainty analysis, which addressed the computational overhead caused by our proposed probabilistic models.
Oak Ridge National Laboratory researchers developed an invertible neural network (INN) to effectively and efficiently solve earth-system model calibration and simulation problems.
A numerical weather forecasting model (WRF) was used to simulate 120 storms over the Alabama-Coosa-Tallapoosa (ACT) river basin to explore the effect of climate change on probable maximum precipitation (PMP).