3 papers
physics.ao-ph2025
Leveraging data-driven weather models for improving numerical weather prediction skill through large-scale spectral nudging
Syed Zahid Husain, Leo Separovic, Jean-François Caron +9
Operational meteorological forecasting has long relied on physics-based numerical weather prediction (NWP) models. Recently, this landscape has faced disruption by the advent of da…
cs.LG2025
Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss Function
Christopher Subich, Syed Zahid Husain, Leo Separovic +1
Recent advancements in data-driven weather forecasting models have delivered deterministic models that outperform the leading operational forecast systems based on traditional, phy…
cs.LG2025
Efficient fine-tuning of 37-level GraphCast with the Canadian global deterministic analysis
Christopher Subich
This work describes a process for efficiently fine-tuning the GraphCast data-driven forecast model to simulate another analysis system, here the Global Deterministic Prediction Sys…