Data from: A framework for minimizing remote effects of regional climate interventions: Cooling the Great Barrier Reef without teleconnections
Data files
May 06, 2025 version files 47.99 GB
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control-branches-quarterly.zip
16.03 GB
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cool-20wm2-eez-quarterly.zip
5.18 GB
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cool-40wm2-DJF-eez-quarterly.zip
5.92 GB
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cool-40wm2-eez-quarterly.zip
15.04 GB
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cool-60wm2-eez-quarterly.zip
5.18 GB
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README.md
4.03 KB
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SOM_forcing_files.zip
118.60 MB
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SST-monthly.zip
528.44 MB
Abstract
Climate interventions like Marine Cloud Brightening (MCB) have gained attention for their potential to protect vulnerable marine ecosystems from the worst impacts of climate change. Early modeling studies raised concerns about potential harmful global side effects stemming from regional interventions. Here we propose a modeling framework to evaluate these risks based on using maximal deployment scenarios in a global climate model to identify potential pathways of concern, combined with more realistic large intervention levels. We demonstrate this framework by modeling a cooling intervention over the Great Barrier Reef using the Community Earth System Model (CESM2). We identify potential impacts on tropical convection that could produce remote impacts, and show that limiting intervention duration to deployment in the key season largely eliminates these risks. Overall we illustrate that the local ecological goals can be achieved at a level of cooling well below what poses a risk of significant remote effects.
https://doi.org/10.5061/dryad.zpc866tj4
Description of the data and file structure
File naming scheme
The naming scheme for all model output netcdf files is as follows:
derecho-som-[experiment]-[branch_year]-[variable]-[timescale].nc
- experiment
- ‘control-qdpnoise[n]’ to indicate the 3 control branches that each have a different random noise pattern added
- ‘anom-eez-[forcing]’ to indicate a [forcing] W/m2 of cooling applied year-round within the domain bounded by the exclusive economic zone
- ‘anom-eez-[forcing]DJF’ to indicate a [forcing] W/m2 of cooling applied only during DJF within the domain bounded by the exclusive economic zone
- branch_year
- Indicates which year the simulation was branched from the spinup simulation
- variable
- CESM2 variable names. Included variables are: CLDTOT, FLUT, OMEGA, PRECC, PRECT, PS, SST, T, TREFHT, TS, U, V, Z3
- timescale
- Either ‘monthly’ or ‘quarterly-JFM’ indicating the timescale that the data is averaged on. Quarterly data is defined as JFM, AMJ, JAS, NOD.
Files and variables
Model output is grouped into the following zip files. Each zip file contains files for all variables at three simulation branches for one level of forcing.
File: cool-20wm2-eez-quarterly.zip
Description:
NetCDF files following the above naming scheme for year-round cooling of 20 W/m2 over coral sea eez domain.
Timescale: Quarterly averaged into JFM, AMJ, JAS, NOD
Forcing: 20 W/m2 year-round
Simulation branches: b50, b55, b60
Variables: CLDTOT, FLUT, OMEGA, PRECC, PRECT, PS, SST, T, TREFHT, TS, U, V, Z3
File: cool-40wm2-eez-quarterly.zip
Description:
NetCDF files following the above naming scheme for year-round cooling of 40 W/m2 over coral sea eez domain.
Timescale: Quarterly averaged into JFM, AMJ, JAS, NOD
Forcing: 40 W/m2 year-round
Simulation branches: b50, b55, b60
Variables: CLDTOT, FLUT, OMEGA, PRECC, PRECT, PS, SST, T, TREFHT, TS, U, V, Z3
File: cool-60wm2-eez-quarterly.zip
Description:
NetCDF files following the above naming scheme for year-round cooling of 60 W/m2 over coral sea eez domain.
Forcing: 60 W/m2 year-round
Simulation branches: b50, b55, b60
Variables: CLDTOT, FLUT, OMEGA, PRECC, PRECT, PS, SST, T, TREFHT, TS, U, V, Z3
File: cool-40wm2-DJF-eez-quarterly.zip
Description:
NetCDF files following the above naming scheme for DJF cooling of 40 W/m2 over coral sea eez domain.
Forcing: 40 W/m2 only in DJF
Timescale: Quarterly averaged into JFM, AMJ, JAS, NOD
Simulation branches: b50, b55, b60
Variables: CLDTOT, FLUT, OMEGA, PRECC, PRECT, PS, SST, T, TREFHT, TS, U, V, Z3
File: SST-monthly.zip
Description:
NetCDF files following the above naming scheme for all cooling scenarios (year-round and DJF)
Timescale: Monthly average
Forcing: 20/40/60 W/m2 year-round and 40 W/m2 seasonal DJF
Simulation branches: b50, b55, b60
Variables: SST
File: control-branches-quarterly.zip
Description:
NetCDF files following the above naming scheme for all control runs.
Timescale: Quarterly average
Forcing: None
Simulation branches: b50, b55, b60
Variables: CLDTOT, FLUT, OMEGA, PRECC, PRECT, PS, SST, T, TREFHT, TS, U, V, Z3
File: SOM_forcing_files.zip
Description:
NetCDF files used to set the SOM forcing within CESM2, following the following naming scheme:
pop_frc.b.e21.B1850.f09_g17.CMIP6-piControl.001_branch2.012120_anom_eez_[forcing].nc
Forcing: 20/40/60 W/m2 year-round and 40 W/m2 seasonal DJF
Software
- paper_figures.ipynb 381.25 KB
- Python notebook containing the code to generate the figures in the manuscript from the included model output files
- supplementary_figs.ipynb 5.15 MB
- Python notebook containing the code to generate the figures in the supplement from the included model output files
The simulations for this study were conducted using the Community Earth System Model (CESM2, Danabasoglu et al. 2020; Computational and Information Systems Laboratory, 2023)) running in a “slab ocean” configuration. In this mode a simplified ocean simulates the mixed layer of the ocean and its interactions with the atmosphere without simulating full ocean circulation. The exchange of heat between the mixed layer and the deeper ocean is approximated with a prescribed monthly Q-flux that is derived from a fully coupled run of the model. All simulations are carried out under preindustrial conditions, with a 50-year spin up period to ensure the model reaches a stable equilibrium before perturbations are applied.
Cooling interventions are implemented using an additional Q-flux term to specify a forcing at the surface of the ocean. The advantage of this approach is that it allows direct control of the location and amount of forcing applied, and can be used to represent cooling that is achieved through cloud brightening, surface albedo enhancement, deep ocean pumping, or any combination of intervention technologies. The limitations of this approach are that it does not include any dynamic adjustments or feedbacks that are specific to an albedo modification or cloud intervention. The simplified ocean also neglects the advection of cooled surface waters due to ocean circulation. This modeling configuration is not aimed at evaluating the efficacy of particular intervention technology at producing cooling, but whether a given level of regional cooling would produce significant impacts outside the region of intervention, in line with step 1 of our framework. Despite these limitations, the SST variability in the Coral Sea region in the slab-ocean simulation is quite similar to both a fully-coupled pre-industrial run of CESM2 and with ERA5 reanalysis (Figure S1).
For each level of forcing, three separate simulations are branched from the control run at five year intervals and run for 13 years. The first year of each branch is discarded as the system is adjusting, producing 36 years of data for each scenario. Using several shorter runs rather than a single long run allows us additional statistics to examine impacts that emerge in the first decade of deployment, when increased scrutiny will be placed on both the effectiveness and any unintended side effects of an intervention. Spacing the branches by five years allows more sampling across conditions of natural variability.