Bern3D-LPX simulations with the adaptive emission reduction approach (AERA)

The files provide the model output from Bern3D-LPX forced with the Adaptive Emission Reduction Approach (AERA) that are presented in Terhaar et al. (2022). The AERA allows to develop time series of CO2 forcing equivalent emissions that allow the global warming to converge to a given temperature target. The simulations here include the standard simulations as well as the simulations with (i) variying non-CO2 radiative agent trajectories, (ii) using GWP-100 instead of CO2 forcing equivalent emissions, as well as (iii) various roubstness tests of the AERA. The simulations demonstrate that the AERA works robustly and that it can be used for policy decisions.

Each simulations follows the same name structure:

The file names follow this structure: AXX_YYYY_Z

AXX describes the model configuration, the first number stands for diapycnal mixing (1=1e-4 m2 s-1, 2 =2e-5 m2 s-1, 3=1e-4 m2 s-1), the second for the feedback parameter lambda in Bern3D (1=0.1 W m-2 K-1, 2=-0.3 W m-2 K-1, 3=-0.7 W m-2 K-1).

YYYY describes the run and the interannual variability. The first two digits are without a special meaning and just give the run numbers, the standard is ‘11’. The third number is the phasing of the superimposed inter-annual variability (1=0 years, 2=50 years, 3 = 25 years, 4=75 years) and the third says if the variability is added (0) or subtracted (1).

Z is the temperature target: 1 is 1.5°C, 2 is 2.0°C and 4 is 1.75°C until 2050 and 1.5°C in 2100.

For more information, please read through the associated publication and GitHub repository (https://github.com/Jete90/AERA).

The files provide the model output from Bern3D-LPX forced with the Adaptive Emission Reduction Approach (AERA) that are presented in Terhaar et al. (2022). The AERA allows to develop time series of CO2 forcing equivalent emissions that allow the global warming to converge to a given temperature target. The simulations here include the standard simulations as well as the simulations with (i) variying non-CO2 radiative agent trajectories, (ii) using GWP-100 instead of CO2 forcing equivalent emissions, as well as (iii) various roubstness tests of the AERA. The simulations demonstrate that the AERA works robustly and that it can be used for policy decisions.

Each simulations follows the same name structure:

The file names follow this structure: AXX_YYYY_Z

AXX describes the model configuration, the first number stands for diapycnal mixing (1=1e-4 m2 s-1, 2 =2e-5 m2 s-1, 3=1e-4 m2 s-1), the second for the feedback parameter lambda in Bern3D (1=0.1 W m-2 K-1, 2=-0.3 W m-2 K-1, 3=-0.7 W m-2 K-1).

YYYY describes the run and the interannual variability. The first two digits are without a special meaning and just give the run numbers, the standard is ‘11’. The third number is the phasing of the superimposed inter-annual variability (1=0 years, 2=50 years, 3 = 25 years, 4=75 years) and the third says if the variability is added (0) or subtracted (1).

Z is the temperature target: 1 is 1.5°C, 2 is 2.0°C and 4 is 1.75°C until 2050 and 1.5°C in 2100.

For more information, please read through the associated publication and GitHub repository (https://github.com/Jete90/AERA).

Disciplines

Cross-discipline

Keywords

Paris Agreement, Climate simulations, Temperature targets

Data

FileSizeFormatProcessingAccess
Model output for simulations when applying the adaptive emission reduction approach every ten years
98 MoNetCDFRaw data
Model output for simulations with the adaptive emission reduction approach with variations in the aerosol forcing
351 MoNetCDFRaw data
Model output for simulations with the adaptive emission reduction approach with variations in CH4 and N2O emissions
299 MoNetCDFRaw data
Model output for simulations with the adaptive emission reduction approach with various compliance rates
100 MoNetCDFRaw data
Model output for simulations with the adaptive emission reduction approach with constant CO2 emissions
69 MoNetCDFRaw data
Model output for simulations with the adaptive emission reduction approach with changing allowed exdeence emissions
50 MoNetCDFRaw data
Model output for simulations with the adaptive emission reduction approach using GWP instead of CO2-fe emissions
148 MoNetCDFRaw data
Model output for simulations with the adaptive emission reduction approach with variations in the allowed REB uncertainty
50 MoNetCDFRaw data
Model output for simulations with the adaptive emission reduction approach using the standard version
224 MoNetCDFRaw data
How to cite
Terhaar Jens, Frölicher Thomas L, Aschwanden Mathias T, Joos Fortunat (2022). Bern3D-LPX simulations with the adaptive emission reduction approach (AERA). SEANOE. https://doi.org/10.17882/90901
In addition to properly cite this dataset, it would be appreciated that the following work(s) be cited too, when using this dataset in a publication :
Terhaar Jens, Frölicher Thomas L., Aschwanden Mathias T., Friedlingstein Pierre, Joos Fortunat (2022). Adaptive emission reduction approach to reach any global warming target. Nature Climate Change, 12 (12). https://doi.org/10.1038/s41558-022-01537-9

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