From the 1 of 6 linked papers with an AI index.
1 citations · 1 across the 3 of their papers we have counts for
6 papers
Stochastic Emulation of a Fully Coupled Preindustrial E3SMv3 Simulation
Elynn Wu, James P. C. Duncan, Troy Arcomano +11
We present a stochastic coupled emulator of E3SM version 3, built on the SamudrACE framework, which couples an atmosphere emulator (ACE2) with a full-depth ocean emulator (Samudra)…
AIMIP Phase 1: systematic evaluations of AI weather and climate models
Brian Henn, Christopher S. Bretherton, Nikolay Koldunov +18
The paper introduces AIMIP Phase 1, an intercomparison framework for AI‑based weather and climate models that evaluates their ability to simulate historical atmospheric conditions…
Disentangling the effects of sea surface temperature and CO in global machine learned weather-climate emulators
Spencer K. Clark, Troy Arcomano, James P. C. Duncan +8
While previous versions of the Ai2 Climate Emulator (ACE) have been trained with CO as a forcing, they are only accurate within a narrow range of scenarios, for example climate…
FloeNet: A mass-conserving global sea ice emulator that generalizes across climates
William Gregory, Mitchell Bushuk, James Duncan +8
We introduce FloeNet, a machine-learning emulator trained on the Geophysical Fluid Dynamics Laboratory global sea ice model, SIS2. FloeNet is a mass-conserving model, emulating 6-h…
HiRO-ACE: Fast and skillful AI emulation and downscaling trained on a 3 km global storm-resolving model
W. Andre Perkins, Anna Kwa, Jeremy McGibbon +5
Kilometer-scale simulations of the atmosphere are an important tool for assessing local weather extremes and climate impacts, but computational expense limits their use to small re…
Skilful global seasonal predictions from a machine learning weather model trained on reanalysis data
Chris Kent, Adam A. Scaife, Nick J. Dunstone +4
Machine learning weather models trained on observed atmospheric conditions can outperform conventional physics-based models at short- to medium-range (1-14 day) forecast timescales…