60 citations · 60 across the 2 of their papers we have counts for
2 papers
physics.ao-ph2026
On the sensitivity of machine-learned probabilistic weather forecast models to scale-aware scoring rules
Simon Lang, Martin Leutbecher, Sam Hatfield
Probabilistic forecast models can be machine-learned from data using loss functions based on scoring rules such as the Continuous Ranked Probability Score (CRPS). This note summari…
physics.ao-ph2021★ 60 cited
Machine learning emulation of gravity wave drag in numerical weather forecasting
Matthew Chantry, Sam Hatfield, Peter Duben +2
We assess the value of machine learning as an accelerator for the parameterisation schemes of operational weather forecasting systems, specifically the parameterisation of non-orog…