Magnitude uncertainty dominates intermodel spread in zonal-mean precipitation response to anthropogenic aerosol increase
Data files
Aug 11, 2025 version files 157.96 GB
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Geng_2025.zip
157.96 GB
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README.md
4.06 KB
Abstract
Anthropogenic aerosols are an important driver of historical climate change, but the climate response is not fully understood, and the climate model simulations suffer from large uncertainties. Based on a multi-model ensemble of historical aerosol forcing simulations for a period of global aerosol increase during 1965–1989, here, we show that the precipitation response shares a common southward displacement of the tropical rain band, but the magnitude differs markedly among models, accounting for 76% of the intermodel uncertainty in zonal-mean precipitation change. Our analysis of atmospheric energetics further reveals key mechanisms for magnitude uncertainty: aerosol radiative forcing drives, cloud radiative feedback amplifies, and ocean circulation damps the intermodel uncertainty in cross-equatorial atmospheric energy transport change and the meridional shift of tropical rain bands. This has important implications for understanding and reducing intermodel uncertainty in anthropogenic climate change.
Dataset DOI: 10.5061/dryad.4j0zpc8qh
Description of the data and file structure
The zip file contains the variables of 13 CMIP6-DAMIP models in hist-aer and hist-GHG single-forcing simulations and the variables of 7 models in piClim-histaer simulation that I used in this study.
Files and variables
File: Geng_2025.zip
Description:
The dataset archive (Geng_2025.zip) contains three subfolders corresponding to three CMIP6 simulation experiments:
hist-aer: Historical simulations with anthropogenic aerosol-only forcing
hist-GHG: Historical simulations with greenhouse gas–only forcing
piClim-histaer: An Atmospheric General Circulation Model experiment where SST is kept constant at the pre-industrial monthly climatology, and only the anthropogenic aerosols radiative forcing varies historically over time.
Folder Structure
Within the hist-aer folder, there are 13 subfolders, each representing one variable (hfls, hfss, od550aer, pr, rlds, rlus, rlut, rsds, rsdt, rsus, rsut, rsutcs, ts).
The hist-GHG folder contains 11 variable folders (hfls, hfss, pr, rlds, rlus, rlut, rsds, rsdt, rsus, rsut, ts).
The piClim-histaer folder contains one subfolder named Amon, which includes 3 variable folders (rlut, rsdt, rsut).
Each variable folder includes NetCDF files (.nc) from multiple CMIP6 models (13 models for hist-aer and hist-GHG, and 7 models for piClim-histaer). All files were downloaded from the ESGF CMIP6 archive and then regridded to a uniform resolution of 2.5° × 2.5° using bilinear interpolation for consistency across models.
NetCDF File naming convention
The NetCDF file names follow a standardized naming pattern. For example:
hfls_ACCESS-CM2_hist-aer_ungrid_r1_185001-202012.nc
This filename can be interpreted as follows:
hfls: Variable name
ACCESS-CM2: Name of the climate model
hist-aer: The simulation experiment (historical anthropogenic aerosol-only forcing)
ungrid: Indicates that the data have been regridded to a common resolution (2.5° × 2.5°)
r1: Member ID – this is the first ensemble member for this experiment of this model
185001-202012: Time span of the data, representing monthly means from January 1850 to December 2020
This naming convention is applied consistently across all variables, models, and experiments in the dataset.
Variable List and Descriptions
The following CMIP6 standard variables are included in this dataset. All definitions, units, and data types are also embedded in the metadata of the NetCDF files.
| Variable | Description | Unit |
|---|---|---|
| hlfs | Surface Upward Latent Heat Flux | W m⁻² |
| hfss | Surface Upward Sensible Heat Flux | W m⁻² |
| od550aer | Ambient Aerosol Optical Depth at 550 nm | number (0–1) |
| pr | Precipitation Flux | kg m⁻² s⁻¹ |
| rlds | Surface Downwelling Longwave Radiation | W m⁻² |
| rlus | Surface Upwelling Longwave Radiation | W m⁻² |
| rlut | TOA Outgoing Longwave Radiation | W m⁻² |
| rsds | Surface Downwelling Shortwave Radiation | W m⁻² |
| rsdt | TOA Incident Shortwave Radiation | W m⁻² |
| rsus | Surface Upwelling Shortwave Radiation | W m⁻² |
| rsut | TOA Outgoing Shortwave Radiation | W m⁻² |
| rsutcs | TOA Outgoing Shortwave Radiation (Clear Sky) | W m⁻² |
| ts | Surface Temperature | K |
Access information
Other publicly accessible locations of the data:
- NA
Data was derived from the following sources: