Equilibrium simulations

The GFDL Earth system model CM2Mc was run to quasi-equilibrium (3000 to 5000 years) under a broad range of external forcings, in which atmospheric carbon dioxide, orbital parameters and ice sheets were systematically varied over more than 40 combinations. The purpose of these simulations was to map out the expectations of a modern climate model – of the sort used for conducting future climate change scenarios – under conditions that have occurred in the geologically-recent past.

These simulations were described by Galbraith and de Lavergne (Climate Dynamics, 2019). Changes in ocean carbon storage among the simulations were also explored by Eggleston and Galbraith (Biogeosciences, 2018), and Newsom et al. (Earth and Planetary Science Letters, 2021) showed implications for global heat transport and overturning. However, these descriptions only scratch the surface – the output could be used to explore general mechanisms within the climate system, as well as their interactions with global biogeochemistry. The results could also be tested against new paleoclimate observations, to identify aspects of the simulations that are consistent, as well as to identify model biases and shortcomings when confronted with reality.

Runscripts

All runscripts (i.e. the shell scripts used to define runtime parameters and input files, and to run the model executable) are provided in a tar archive.

All runscripts (5M)

Output (netcdf format)

Output files are provided for the final century of each simulation. Two types of files are included: timeseries (_ts, annual averages of each variable during each year of the century) and climatologies (_avg, monthly averages of each variable during all years of the century). Note the _avg climatologies are not available for the 147… or 180L… simulations.

List of all output variables by file type (see source code for variable details)

Each link below points to a single tar archive that includes one netcdf file per simulation, i.e. ~40 netcdf files per archive. Analysis of the output will require unpacking the tar archive and loading it in suitable analysis software (e.g. Ferret or Matlab).

* Caution: an inconsistency was found in this version of the BLING δ13C code, please do not trust the δ13C simulation. Everything else should be ok, though note that BLING.v0 is the fully documented version.