preindustrial Control experiment to be used in VolMIP analyses. The piControl experiment is the CMIP6-DECK piControl experiment described in Eyring et al. (2016). piControl provides initial climate states that are sampled to start most of VolMIP experiments (Zanchettin et al., 2016). The dataset contains monthly values of selected variables spatially averaged over four regions. These are the full globe (GL), the Northern Hemisphere extratropics (30°-90°N, NH), the tropics (30°S-30°N, TR), and the Southern Hemisphere (30°-90°S, hereafter SH). The considered variables have the following cmor names: hfls, hfss, pr, rlds, rldscs, rlus, rlut, rlutcs, rsds, rsdscs, rsdt, rsus, rsut, rsutcs, tas. Additionally, the climate indices NAO and Nino34 are part of the dataset. Considered models are CanESM5, IPSL-CM6A-LR, GISS-E2.1-G, MIROC-ES2L, MPI-ESM1.2-LR (named MPI-ESM-LR in the files of this dataset) and UKESM1. Considered experiments are piControl and volc-pinatubo-full, with initial date and final date as specified for each model in Zanchettin et al. (2021). Different realizations are considered for the participating models depending on availability.

Idealized volcanic-forcing coupled climate model experiment using the 1991 Pinatubo forcing as used in the CMIP6 historical simulations. It is a Tier 1 (mandatory) VolMIP experiment based on a large ensemble of short-term “Pinatubo” climate simulations aimed at accurately estimating simulated responses to volcanic forcing that may be comparable to the amplitude of internal interannual climate variability. Initialization is based on equally distributed predefined states of ENSO (cold/neutral/warm states) and of the North Atlantic Oscillation (NAO, negative/neutral/positive states). Sampling of an eastern phase of the Quasi-Biennial Oscillation (QBO), as observed after the 1991 Pinatubo eruption, is preferred for those models that spontaneously generate such mode of stratospheric variability. VIRF diagnostics must be calculated for this experiment for the whole integration and for all ensemble members, as these are required for the “volc-pinatubo-strat”/“surf” experiments. A minimum length of integration of 3 years is requested. Details about the experiment are provided by Zanchettin et al. (2016). The dataset contains monthly values of selected variables spatially averaged over four regions. These are the full globe (GL), the Northern Hemisphere extratropics (30°-90°N, NH), the tropics (30°S-30°N, TR), and the Southern Hemisphere (30°-90°S, hereafter SH). The considered variables have the following cmor names: hfls, hfss, pr, rlds, rldscs, rlus, rlut, rlutcs, rsds, rsdscs, rsdt, rsus, rsut, rsutcs, tas. Additionally, the climate indices NAO and Nino34 are part of the dataset. Considered models are CanESM5, IPSL-CM6A-LR, GISS-E2.1-G, MIROC-ES2L, MPI-ESM1.2-LR (named MPI-ESM-LR in the files of this dataset) and UKESM1. Considered experiments are piControl and volc-pinatubo-full, with initial date and final date as specified for each model in Zanchettin et al. (2021). Different realizations are considered for the participating models depending on availability.

A number of idealised simulation experiments of ice rises in Antarctica using the finite element model Elmer/Ice are performed. The model solves the Stokes equations and ice rises are formed by a protrusion of the bed into the ice shelf. The surrounding ice is floating and hydrostatic pressure is applied. There is a constant influx of ice on one side of the domain and the ice is allowed to flow out of the domain on the opposite side, subject to hydrostatic pressure. The three simulations in this data repository correspond with three varying basal friction coefficients. To understand the response of ice rises to changes in sea level, we perform transient simulations increasing and decreasing sea level at a constant rate. The data includes vtu and pvtu files, which allow for visualisation of the simulation using Paraview. Each vtu file contains the data for one partition of the domain and the pvtu file allows the entire domain to be visualised. The result files can be used to restart simulations in Elmer/Ice. The mesh generation and simulation initialisation for all experiments (LowFriction, IntermediateFriction and HighFriction) are generated using the code in the Remesh and Init directories in the the LowFriction directory. The code used to run the simulations and the post-processing code are also provided.

In work package 6 of the nextGEMS project, several ocean-only model runs were performed with FESOM (Version 2.0) and ICON-O (Version 2.6.6), to test the sensitivity of the upper tropical Atlantic to different settings of the vertical mixing scheme. Two different mixing schemes were tested: TKE and KPP. For TKE, we tested different settings of the c_k parameter (0.1, 0.2 and 0.3), and for KPP different settings of the critical bulk Richardson number (0.3 and 0.27). These runs were done with both ICON-O and FESOM, to enable a comparison of the effects of the vertical mixing settings across different models. From ICON-O only, there are some additional TKE runs available, where we increased the interior ocean background mixing, and switched on the Langmuir turbulence parameterisation. There is also an ICON-O run which uses the FESOM default forcing bulk formulae, to check how much of the differences between the models originates from their different default bulk formulae. All model runs are ocean only, forced with hourly ERA5 reanalysis data. The horizontal resolution is 10km (for FESOM, the extratropical regions have a coarser grid). The output from the tropical Atlantic from these model runs is provided here, with a high temporal resolution of 3 hours, and interpolated to a 0.1°x0.1° latitude-longitude grid. Please read the readme before using the data: https://www.wdc-climate.de/ui/entry?acronym=nextGEMSWp6OceanREADME nextGEMS is funded through the European Union’s Horizon 2020 research and innovation program under the grant agreement number 101003470.

preindustrial Control experiment to be used in VolMIP analyses. The piControl experiment is the CMIP6-DECK piControl experiment described in Eyring et al. (2016). piControl provides initial climate states that are sampled to start most of VolMIP experiments (Zanchettin et al., 2016). The dataset contains monthly values of selected variables spatially averaged over four regions. These are the full globe (GL), the Northern Hemisphere extratropics (30°-90°N, NH), the tropics (30°S-30°N, TR), and the Southern Hemisphere (30°-90°S, hereafter SH). The considered variables have the following cmor names: hfls, hfss, pr, rlds, rldscs, rlus, rlut, rlutcs, rsds, rsdscs, rsdt, rsus, rsut, rsutcs, tas. Additionally, the climate indices NAO and Nino34 are part of the dataset. Considered models are CanESM5, IPSL-CM6A-LR, GISS-E2.1-G, MIROC-ES2L, MPI-ESM1.2-LR (named MPI-ESM-LR in the files of this dataset) and UKESM1. Considered experiments are piControl and volc-pinatubo-full, with initial date and final date as specified for each model in Zanchettin et al. (2021). Different realizations are considered for the participating models depending on availability.

Idealized volcanic-forcing coupled climate model experiment using the 1991 Pinatubo forcing as used in the CMIP6 historical simulations. It is a Tier 1 (mandatory) VolMIP experiment based on a large ensemble of short-term “Pinatubo” climate simulations aimed at accurately estimating simulated responses to volcanic forcing that may be comparable to the amplitude of internal interannual climate variability. Initialization is based on equally distributed predefined states of ENSO (cold/neutral/warm states) and of the North Atlantic Oscillation (NAO, negative/neutral/positive states). Sampling of an eastern phase of the Quasi-Biennial Oscillation (QBO), as observed after the 1991 Pinatubo eruption, is preferred for those models that spontaneously generate such mode of stratospheric variability. VIRF diagnostics must be calculated for this experiment for the whole integration and for all ensemble members, as these are required for the “volc-pinatubo-strat”/“surf” experiments. A minimum length of integration of 3 years is requested. Details about the experiment are provided by Zanchettin et al. (2016). The dataset contains monthly values of selected variables spatially averaged over four regions. These are the full globe (GL), the Northern Hemisphere extratropics (30°-90°N, NH), the tropics (30°S-30°N, TR), and the Southern Hemisphere (30°-90°S, hereafter SH). The considered variables have the following cmor names: hfls, hfss, pr, rlds, rldscs, rlus, rlut, rlutcs, rsds, rsdscs, rsdt, rsus, rsut, rsutcs, tas. Additionally, the climate indices NAO and Nino34 are part of the dataset. Considered models are CanESM5, IPSL-CM6A-LR, GISS-E2.1-G, MIROC-ES2L, MPI-ESM1.2-LR (named MPI-ESM-LR in the files of this dataset) and UKESM1. Considered experiments are piControl and volc-pinatubo-full, with initial date and final date as specified for each model in Zanchettin et al. (2021). Different realizations are considered for the participating models depending on availability.

The experiment includes the source code, compile and run scripts for ICON-ESM-V1.0 in the configuration “Ruby-0”, the initialization data for ICON-ESM-V1 in the configuration “Ruby-0”, and scripts, libraries, and input data used to produce figures.

MPI-ESM1-2-LR’s CMIP6 CovidMIP baseline simulations are based on simulations forced with CO2 emissions allowing interactive carbon cycle. The baseline simulations (ssp245-cov-baseline, publish here) is a reference to the CovidMIP simulations (ssp245-covid, ssp245-cov-fossil, ssp245-cov-strgreen, and ssp245-cov-modgreen, published under CMIP6 CovidMIP) to investigate the effects of COVID-19 induced emission reductions on global carbon cycle, climate change and feedbacks. As presented in Jones et al. (2021), the radiative and climate responses of MPI-ESM1-2-LR are within the range of multi-model simulation results. have 10 ensemble members of the simulation named from r1i1p1f99 to r10i1p1f99. Here f99 is used in the file name *r*i1p1f99* of all CovidMIP simulations because of the updated aerosol forcing (Fiedler et al. 2021). Fiedler, S.; Wyser, K.; Rogelj, J. & van Noije, T. (2021): Radiative effects of reduced aerosol emissions during the COVID-19 pandemic and the future recovery, Atmospheric Research, 264, 105866, https://doi.org/10.1016/j.atmosres.2021.105866 Jones, C. D., Hickman, J. E., Rumbold, S. T., Walton, J., Lamboll, R. D., Skeie, R. B., ... & Ziehn, T. (2021). The climate response to emissions reductions due to COVID‐19: Initial results from CovidMIP. Geophysical research letters, 48(8), e2020GL091883.