most citedACE2-SOM: Coupling an ML atmospheric emulator to a slab ocean and learning the sensitivity of climate to changed CO

4 citations · 7 across the 3 of their papers we have counts for

collaborators

3 papers

physics.ao-ph2025

Applying the ACE2 Emulator to SST Green's Functions for the E3SMv3 Global Atmosphere Model

Elynn Wu, Finn Rebassoo, Pappu Paul +5

Green's functions are a useful technique for interpreting atmospheric state responses to changes in the spatial pattern of sea surface temperature (SST). Here we train version 2 of…

physics.ao-ph2024★ 4 cited

ACE2-SOM: Coupling an ML atmospheric emulator to a slab ocean and learning the sensitivity of climate to changed CO

Spencer K. Clark, Oliver Watt-Meyer, Anna Kwa +6

While autoregressive machine-learning-based emulators have been trained to produce stable and accurate rollouts in the climate of the present-day and recent past, none so far have…

physics.ao-ph2024★ 3 cited

ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses

Oliver Watt-Meyer, Brian Henn, Jeremy McGibbon +6

Existing machine learning models of weather variability are not formulated to enable assessment of their response to varying external boundary conditions such as sea surface temper…