This dataset includes all variables of the model experiment “simA historical” conducted with the global ocean-sea ice-biogeochemistry model FESOM1.4-REcoM2 with ice-shelf cavities and eddy-permitting resolution on Antarctic shelves. For this experiment, both atmospheric CO2 concentrations and all other atmospheric forcing variables (e.g., air temperature, winds, humidity, precipitation) vary throughout the simulation. Output is provided from 1980-2014 (monthly and annual output frequency) and 1990-2009 (daily output frequency). The years 1950-1979 are interpreted as spin-up and not provided here. The output is sorted by output frequency (monthly or daily) and model component (FESOM or REcoM). The data is sorted as follows: - annual_FESOM - annual_REcoM - monthly_FESOM - monthly_REcoM - daily_FESOM - daily_REcoM Filname convention: Variable_outputFreq_FESOM1.4-REcoM2_experimentName_experimentTime_year.nc Computing resources were provided by the North-German Supercomputing Alliance (HLRN) project hbk00079.

This dataset includes all variables of the model experiment “simA ssp245” conducted with the global ocean-sea ice-biogeochemistry model FESOM1.4-REcoM2 with ice-shelf cavities and eddy-permitting resolution on Antarctic shelves. For this experiment, both atmospheric CO2 concentrations and all other atmospheric forcing variables (e.g., air temperature, winds, humidity, precipitation) vary throughout the simulation. Output is provided from 2015-2100. The output is sorted by output frequency (monthly or daily) and model component (FESOM or REcoM). The data is sorted as follows: - annual_FESOM - annual_REcoM - monthly_FESOM - monthly_REcoM Filname convention: Variable_outputFreq_FESOM1.4-REcoM2_experimentName_experimentTime_year.nc Computing resources were provided by the North-German Supercomputing Alliance (HLRN) project hbk00079.

This dataset includes all variables of the model experiment “simA ssp370” conducted with the global ocean-sea ice-biogeochemistry model FESOM1.4-REcoM2 with ice-shelf cavities and eddy-permitting resolution on Antarctic shelves. For this experiment, both atmospheric CO2 concentrations and all other atmospheric forcing variables (e.g., air temperature, winds, humidity, precipitation) vary throughout the simulation. Output is provided from 2015-2100. The output is sorted by output frequency (monthly or daily) and model component (FESOM or REcoM). The data is sorted as follows: - annual_FESOM - annual_REcoM - monthly_FESOM - monthly_REcoM Filname convention: Variable_outputFreq_FESOM1.4-REcoM2_experimentName_experimentTime_year.nc Computing resources were provided by the North-German Supercomputing Alliance (HLRN) project hbk00079.

This dataset includes all variables of the model experiment “simA ssp585” conducted with the global ocean-sea ice-biogeochemistry model FESOM1.4-REcoM2 with ice-shelf cavities and eddy-permitting resolution on Antarctic shelves. For this experiment, both atmospheric CO2 concentrations and all other atmospheric forcing variables (e.g., air temperature, winds, humidity, precipitation) vary throughout the simulation. Output is provided from 2015-2100 (monthly and annual output frequency) and 2080-2100 (daily output frequency). The output is sorted by output frequency (monthly or daily) and model component (FESOM or REcoM). The data is sorted as follows: - annual_FESOM - annual_REcoM - monthly_FESOM - monthly_REcoM - daily_FESOM - daily_REcoM Filname convention: Variable_outputFreq_FESOM1.4-REcoM2_experimentName_experimentTime_year.nc Computing resources were provided by the North-German Supercomputing Alliance (HLRN) project hbk00079.

This dataset includes all variables of the model experiment “simC historical” conducted with the global ocean-sea ice-biogeochemistry model FESOM1.4-REcoM2 with ice-shelf cavities and eddy-permitting resolution on Antarctic shelves. For this experiment, atmospheric CO2 concentrations vary, but all other atmospheric forcing variables (e.g., air temperature, winds, humidity, precipitation) are held constant throughout the simulation. Output is provided from 1980-2014. The years 1950-1979 are interpreted as spin-up and not provided here. The output is sorted by output frequency (monthly or daily) and model component (FESOM or REcoM). The data is sorted as follows: - annual_FESOM - annual_REcoM - monthly_FESOM - monthly_REcoM Filname convention: Variable_outputFreq_FESOM1.4-REcoM2_experimentName_experimentTime_year.nc Computing resources were provided by the North-German Supercomputing Alliance (HLRN) project hbk00079.

This dataset includes all variables of the model experiment “simC ssp245” conducted with the global ocean-sea ice-biogeochemistry model FESOM1.4-REcoM2 with ice-shelf cavities and eddy-permitting resolution on Antarctic shelves. For this experiment, atmospheric CO2 concentrations vary, but all other atmospheric forcing variables (e.g., air temperature, winds, humidity, precipitation) are held constant throughout the simulation. Output is provided from 2015-2100. The output is sorted by output frequency (monthly or daily) and model component (FESOM or REcoM). The data is sorted as follows: - annual_FESOM - annual_REcoM - monthly_FESOM - monthly_REcoM Filname convention: Variable_outputFreq_FESOM1.4-REcoM2_experimentName_experimentTime_year.nc Computing resources were provided by the North-German Supercomputing Alliance (HLRN) project hbk00079.

This dataset includes all variables of the model experiment “simC ssp585” conducted with the global ocean-sea ice-biogeochemistry model FESOM1.4-REcoM2 with ice-shelf cavities and eddy-permitting resolution on Antarctic shelves. For this experiment, atmospheric CO2 concentrations vary, but all other atmospheric forcing variables (e.g., air temperature, winds, humidity, precipitation) are held constant throughout the simulation. Output is provided from 2015-2100. The output is sorted by output frequency (monthly or daily) and model component (FESOM or REcoM). The data is sorted as follows: - annual_FESOM - annual_REcoM - monthly_FESOM - monthly_REcoM Filname convention: Variable_outputFreq_FESOM1.4-REcoM2_experimentName_experimentTime_year.nc Computing resources were provided by the North-German Supercomputing Alliance (HLRN) project hbk00079.

This dataset includes all variables of the model experiment “simD historical” conducted with the global ocean-sea ice-biogeochemistry model FESOM1.4-REcoM2 with ice-shelf cavities and eddy-permitting resolution on Antarctic shelves. For this experiment, atmospheric CO2 concentrations are held constant, but all other atmospheric forcing variables (e.g., air temperature, winds, humidity, precipitation) vary throughout the simulation. Output is provided from 1980-2014. The years 1950-1979 are interpreted as spin-up and not provided here. The output is sorted by output frequency (monthly or daily) and model component (FESOM or REcoM). The data is sorted as follows: - annual_FESOM - annual_REcoM - monthly_FESOM - monthly_REcoM Filname convention: Variable_outputFreq_FESOM1.4-REcoM2_experimentName_experimentTime_year.nc Computing resources were provided by the North-German Supercomputing Alliance (HLRN) project hbk00079.

This dataset includes all variables of the model experiment “simD ssp585” conducted with the global ocean-sea ice-biogeochemistry model FESOM1.4-REcoM2 with ice-shelf cavities and eddy-permitting resolution on Antarctic shelves. For this experiment, atmospheric CO2 concentrations are held constant, but all other atmospheric forcing variables (e.g., air temperature, winds, humidity, precipitation) vary throughout the simulation. Output is provided from 2015-2100. The output is sorted by output frequency (monthly or daily) and model component (FESOM or REcoM). The data is sorted as follows: - annual_FESOM - annual_REcoM - monthly_FESOM - monthly_REcoM Filname convention: Variable_outputFreq_FESOM1.4-REcoM2_experimentName_experimentTime_year.nc Computing resources were provided by the North-German Supercomputing Alliance (HLRN) project hbk00079.

To evaluate the added value of regional refinement in the ICON model, this experiment focuses on present-day (PD) climate simulations using ERA5 boundary conditions. These simulations serve as a baseline for assessing how increased spatial resolution over polar regions affects the representation of key climate processes, large-scale circulation, and polar–midlatitude linkages. Comparing the uniform and refined configurations enables a systematic evaluation of the performance, internal consistency, and potential improvements introduced by two-way nested domains in a controlled present-day setup. This experiment comprises three atmosphere-only simulations conducted with version 2.6.6 of the ICON model as part of WP2 of the EU Horizon 2020 project PolarRES. All simulations follow an AMIP-style setup and are forced with boundary conditions from ERA5, representing present-day climate conditions. The simulations differ only in their horizontal resolution over the polar regions. PD_ERA_UNREF was performed using a globally uniform R3B5 grid, corresponding to a horizontal resolution of approximately 52.6 km. The two refined simulations, PD_ERA_REF_ARCTIC and PD_ERA_REF_ANTARC, are based on the same R3B5 base grid but include two nested domains over the Arctic and Antarctic, respectively. Each includes an intermediate-resolution nest (R3B6, ~26.3 km) north or south of 50° latitude, and a high-resolution nest (R3B7, ~13.2 km) beyond 57°N or 57°S. Two-way nesting was used to allow feedback from the refined domains to the global domain. All simulations used 90 vertical levels with a model top at approximately 75 km. The time step was halved with each nesting level to ensure numerical stability. All physical parameterisations were applied consistently across domains and chosen to perform robustly across the resolution range. The simulations were initialised on 1 January 1984 using ERA5 data and integrated for 31 years. The first year is discarded as spin-up, yielding 30 years of output (1985–2014). Sea surface temperatures and sea ice concentrations were prescribed daily from ERA5 for the period 1984–2014. While sea ice concentration is prescribed, the model calculates sea ice thickness prognostically. Time-varying greenhouse gas concentrations (CO₂, CH₄, N₂O, and CFCs) follow CMIP6 historical forcings. The ICON dynamical core is based on Zängl et al. (2015) and the model code is available via https://www.icon-model.org/ (release note for version 2.6.6: https://gitlab.dkrz.de/icon/icon-model/-/blob/release-2024.07-public/RELEASE_NOTES.md?ref_type=heads). All three simulations used the ecRad radiation scheme (Hogan et al., 2018), a single-moment cloud microphysics scheme following Doms et al. (2011) and Seifert (2008), and a convection scheme based on Tiedtke (1989) and Bechtold et al. (2008). Turbulent processes are represented by a prognostic TKE-based turbulence scheme (Raschendorfer, 2001). Orographic drag is parameterised following Lott and Miller (1997), and non-orographic gravity wave drag is based on Orr et al. (2010). Parameter settings for subgrid-scale orographic and non-orographic gravity wave drag were guided by Köhler et al. (2021), with adaptations to our model resolution. The land surface is represented using the TERRA component for soil-vegetation-atmosphere transfer (Schrodin and Heise, 2001), with topography derived from the GLOBE dataset (Hastings et al., 1999) at ~1 km native resolution. Post-processing included horizontal interpolation of selected variables to a regular 0.5° × 0.5° lat-lon grid for the global domain (UNREF), and to 0.125° × 0.125° for the high-resolution refined domains. Vertical interpolation to 19 pressure levels was applied to data on native model levels.