2 citations · 3 across the 2 of their papers we have counts for
3 papers
Constraining Atmospheric River Uncertainty Using Instantaneous Poleward Latent Heat Transport
Ankur Mahesh, William D. Collins, William R. Boos +2
Atmospheric rivers (ARs) are extreme weather events that play a crucial role in the global hydrological cycle. As a key mechanism of latent heat transport (LHT), they help maintain…
FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale
Boris Bonev, Thorsten Kurth, Ankur Mahesh +7
FourCastNet 3 advances global weather modeling by implementing a scalable, geometric machine learning (ML) approach to probabilistic ensemble forecasting. The approach is designed…
Analyzing and Exploring Training Recipes for Large-Scale Transformer-Based Weather Prediction
Jared D. Willard, Peter Harrington, Shashank Subramanian +3
The rapid rise of deep learning (DL) in numerical weather prediction (NWP) has led to a proliferation of models which forecast atmospheric variables with comparable or superior ski…