DOI: 10.5061/dryad.d2547d8cf
title: GF4ACE -- Data from: Reanalysis-based global radiative response to sea surface temperature patterns: Evaluating the Ai2 climate emulator

description: The sensitivity of the radiative flux at the top of the atmosphere to
 surface temperature perturbations cannot be directly observed. The
 relationship between sea surface temperature and top-of-atmosphere
 radiation can be estimated with Green's function simulations by
 locally perturbing the sea surface temperature boundary conditions in
 atmospheric climate models. We perform such simulations with the Ai2
 Climate Emulator (ACE), a machine learning-based emulator trained on ERA5
 reanalysis data (ACE2-ERA5). This produces a sensitivity map of the
 top-of-atmosphere radiative response to surface warming that aligns with
 our physical understanding of radiative feedback. However, ACE2-ERA5
 likely underestimates the radiative response to historical warming. We
 argue that Green's function experiments can be used to evaluate the
 performance and limitations of machine learning-based climate emulators by
 examining if causal physical relationships are correctly represented and
 testing their capability for out-of-distribution predictions.
description: # GF4ACE Senne Van Loon, Maria Rugenstein, & Elizabeth A. Barnes
 (2025), Reanalysis-based Global Radiative Response to Sea Surface
 Temperature Patterns: Evaluating the Ai2 Climate Emulator, 
 [arXiv:2502.10893](https://arxiv.org/abs/2502.10893) Data & Software:
 [https://doi.org/10.5061/dryad.d2547d8cf](https://doi.org/10.5061/dryad.d2547d8cf) [https://doi.org/10.5281/zenodo.14963836](https://doi.org/10.5281/zenodo.14963836) ## Data for GF4ACE This repository contains initial conditions, patch perturbations and global-mean output data for: Senne Van Loon, Maria Rugenstein, & Elizabeth A. Barnes (2025), Reanalysis-based Global Radiative Response to Sea Surface Temperature Patterns: Evaluating the Ai2 Climate Emulator,  [arXiv:2502.10893](https://arxiv.org/abs/2502.10893) ### Files and variables #### File: GF4ACE\_data.zip **Description:** initial conditions, forcing, and output data The zip file contains sample data to be used in combination with the software available on [Zenodo](https://doi.org/10.5281/zenodo.14963836), and is ordered in a file structure consistent with the code. In particular: * `forcing` contains patch forcing files for each model used, for different patch amplitudes * Each folder in `forcing` denotes the version of ACE used ('eam', 'era', or 'fv3') * `patches_*.nc` contains SST patches of amplitude `2K`, `-2K`, `4K`, or `-4K`. * These patches were created with the `create_patches` function in the software available on on [Zenodo](https://doi.org/10.5281/zenodo.14963836) * `initialization` contains initial conditions for the control run of each model * Each folder in `initialization` denotes the version of ACE used ('eam', 'era', or 'fv3') * `20191231_1800.nc` contains the initial conditions for the control run * `output` contains output files of the Green's function experiments * Each folder in `output` denotes the version of ACE used ('eam', 'era', or 'fv3') * pre-processed global-mean radiation from all patch simulations in `R_gm_monthly_*.nc` * Ocean masks for each version in `ocean_mask.nc` * Incoming solar radiation for each version in `rsdt.nc`