most citedBenchmarking atmospheric circulation variability in an AI emulator, ACE2, and a hybrid model, NeuralGCM

2 citations · 3 across the 3 of their papers we have counts for

collaborators
Showing physics.ao-phShow all

5 papers · 1 filter

physics.ao-ph2026

ClimateBench v2.0: Probabilistic Climate Model Benchmarking

Duncan Watson-Parris, Willa Tobin, Aytaç Paçal +32

We present ClimateBench v2, a standardized protocol for evaluating climate models on diagnostics expected to be informative for their skill in projecting mid-century regional tempe…

physics.ao-ph2026

Water vapor buoyancy and the African easterly jet

Heng Quan, Da Yang, William Boos +4

The African easterly jet (AEJ) is a prominent circulation feature in the tropical atmosphere. It transports mineral dust and generates easterly waves that serve as seeds for hurric…

physics.ao-ph2025

Benchmarking Regional Thermodynamic Trends in an AI emulator, ACE2, and a hybrid model, NeuralGCM

Katharine Rucker, Ian Baxter, Pedram Hassanzadeh +2

AI models have emerged as potential complements to physics-based models, but their skill in capturing observed regional climate trends with important societal impacts has not been…

physics.ao-ph2025★ 2 cited

Benchmarking atmospheric circulation variability in an AI emulator, ACE2, and a hybrid model, NeuralGCM

Ian Baxter, Hamid Pahlavan, Pedram Hassanzadeh +2

Physics-based atmosphere-land models with prescribed sea surface temperature have notable successes but also biases in their ability to represent atmospheric variability compared t…

physics.ao-ph2025★ 1 cited

Predicting Beyond Training Data via Extrapolation versus Translocation: AI Weather Models and Dubai's Unprecedented 2024 Rainfall

Y. Qiang Sun, Pedram Hassanzadeh, Tiffany Shaw +1

Artificial intelligence (AI) models have transformed weather forecasting, but their skill for gray swan extremes is unclear. Here, we analyze GraphCast, AIFS, and FuXi forecasts of…