ERA5-based present-day ICON simulations with variable polar resolution

Koehler, Raphael; Handorf, Dörthe

ERA5-based present-day ICON simulations with variable polar resolution

doi:10.26050/WDCC/PolarRES_ICON

Koehler, Raphael; Handorf, Dörthe

ExperimentDOI

amip-hist ICON atmosphere model polar climate

Summary: 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.
Project: PolarRES_ICONvR (PolarRES: Global variable-resolution ICON simulations with polar refinements)
Contact: Dr. Raphael Koehler (
Raphael.Koehler@nullawi.de
0000-0002-3378-8012)
Dörthe Handorf (
Doerthe.Handorf@nullawi.de
0000-0002-3305-6882)
Location(s): Antarctica
global
Arctic region
Spatial Coverage: Longitude 0 to 359.88 Latitude -90 to 90 Altitude: 100000 Pa to 100 Pa
Temporal Coverage: 1985-01-01 to 2014-12-31 (proleptic_gregorian)
Use constraints: Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)
Data Catalog: World Data Center for Climate
Size: 4.46 TiB (4899776064749 Byte)
Format: NetCDF
Status: completely archived
Creation Date: 2025-06-06
Future Review Date: 2035-06-09

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Cite as: Koehler, Raphael; Handorf, Dörthe (2025). ERA5-based present-day ICON simulations with variable polar resolution. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/PolarRES_ICON

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Funding: European Commission - Horizon Europe
Grant/Award No: 101003590 - PolarRES: Polar Regions in the Earth System

FAIR

F-UJI result: total 69.23 %

Description: Summary:
Findable: 6 of 7 level;
Accessible: 3 of 7 level;
Interoperable: 4 of 6 level;
Reusable: 5 of 6 level
Method: F-UJI online v3.5.0 automated
Method Description: Checks performed by WDCC. Metrics documentation: https://doi.org/10.5281/zenodo.15045911 Metric Version: metrics_v0.8
Method Url: https://www.f-uji.net
Result Date: 2025-07-22

Scientific Quality Assurance (SQA)

SQA - Scientific Quality Assurance 'approved by author'

Result Date: 2025-07-21

Technical Quality Assurance (TQA)

TQA - Technical Quality Assurance 'approved by WDCC'

Description: 1. Number of data sets is correct and > 0: passed;
2. Size of every data set is > 0: passed;
3. The data sets and corresponding metadata are accessible: passed;
4. The data sizes are controlled and correct: passed;
5. The spatial-temporal coverage description (metadata) is consistent to the data: passed;
6. The format is correct: passed;
7. Variable description and data are consistent: passed
Method: WDCC-TQA checklist
Method Description: Checks performed by WDCC. The list of TQA metrics are documented in the 'WDCC User Guide for Data Publication' Chapter 8.1.1
Method Url: https://www.wdc-climate.de/docs/WDCC_User_Guide_Data_v1.pdf
Result Date: 2025-07-21

Contact type	Person	ORCID	Organization
Contact	Dr. Raphael Koehler	0000-0002-3378-8012	Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research
Contact	Dörthe Handorf	0000-0002-3305-6882	Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research
Author	Dr. Raphael Koehler	0000-0002-3378-8012	Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research
Author	Dörthe Handorf	0000-0002-3305-6882	Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research
Investigator	Dr. Raphael Koehler	0000-0002-3378-8012	Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research
Funder	-	-	European Commission - Horizon Europe

Is documented by

[1] Tiedtke, M. (1989). A comprehensive mass flux scheme for cumulus parameterization in large-scale models.

[2] DOI Zängl, Günther; Reinert, Daniel; Rípodas, Pilar; Baldauf, Michael. (2014). The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core. doi:10.1002/qj.2378

[3] DOI Lott, François; Miller, Martin J. (1997). A new subgrid-scale orographic drag parametrization: Its formulation and testing. doi:10.1002/qj.49712353704

[4] DOI Köhler, Raphael; Handorf, Dörthe; Jaiser, Ralf; Dethloff, Klaus; Zängl, Günther; Majewski, Detlev; Rex, Markus. (2021). Improved Circulation in the Northern Hemisphere by Adjusting Gravity Wave Drag Parameterizations in Seasonal Experiments With ICON‐NWP. doi:10.1029/2021ea001676

[5] DOI Bechtold, Peter; Köhler, Martin; Jung, Thomas; Doblas‐Reyes, Francisco; Leutbecher, Martin; Rodwell, Mark J.; Vitart, Frederic; Balsamo, Gianpaolo. (2008). Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time‐scales. doi:10.1002/qj.289

[6] DOI Hogan, Robin J.; Bozzo, Alessio. (2018). A Flexible and Efficient Radiation Scheme for the ECMWF Model. doi:10.1029/2018ms001364

[7] DOI Orr, Andrew; Bechtold, Peter; Scinocca, John; Ern, Manfred; Janiskova, Marta. (2010). Improved Middle Atmosphere Climate and Forecasts in the ECMWF Model through a Nonorographic Gravity Wave Drag Parameterization. doi:10.1175/2010jcli3490.1

[8] DOI Doms, G.; Förstner, J.; Heise, E.; Herzog, H.-J.; Mironov, D.; Raschendorfer, M.; Reinhardt, T.; Ritter, B.; Schrodin, R.; Schulz, J.-P.; Vogel, G. (2021). A description of the nonhydrostatic regional cosmo model. Part ii: Physical parameterization . doi:10.5676/DWD_pub/nwv/cosmo-doc_6.00_II

[9] Hastings, D. A.; Dunbar, P. K.; Elphingstone, G. M.; Bootz, M.; Murakami, H.; Maruyama, H.; Masaharu, H.; Holland, P.; Payne, J.; Bryant, N. A.; Logan, T. L.; Muller, J.-P.; Schreier, G.; MacDonald, J. S. (1999). The global land one-kilometer base elevation (globe) digital elevation model, version 1.0. http://www.ngdc.noaa.gov/mgg/topo/globe.html

[10] Raschendorfer, M. (2001). The new turbulence parameterization of lm. https://www.cosmo-model.org/content/model/documentation/newsLetters/newsLetter01/newsLetter_01.pdf

[11] DOI Schrodin, R.; Heise, E. (2001). The multi-layer version of the dwd soil model terra_lm. doi:10.5676/DWD_pub/nwv/cosmo-tr_2

[12] Seifert, A. (2008). A revised cloud microphysical parameterization for cosmo-lme. https://www.cosmo-model.org/content/model/documentation/newsLetters/newsLetter07

Is derived from

[1] DOI Hersbach, Hans; Bell, Bill; Berrisford, Paul; Hirahara, Shoji; Horányi, András; Muñoz‐Sabater, Joaquín; Nicolas, Julien; Peubey, Carole; Radu, Raluca; Schepers, Dinand; Simmons, Adrian; Soci, Cornel; Abdalla, Saleh; Abellan, Xavier; Balsamo, Gianpaolo; Bechtold, Peter; Biavati, Gionata; Bidlot, Jean; Bonavita, Massimo; Chiara, Giovanna; Dahlgren, Per; Dee, Dick; Diamantakis, Michail; Dragani, Rossana; Flemming, Johannes; Forbes, Richard; Fuentes, Manuel; Geer, Alan; Haimberger, Leo; Healy, Sean; Hogan, Robin J.; Hólm, Elías; Janisková, Marta; Keeley, Sarah; Laloyaux, Patrick; Lopez, Philippe; Lupu, Cristina; Radnoti, Gabor; Rosnay, Patricia; Rozum, Iryna; Vamborg, Freja; Villaume, Sebastien; Thépaut, Jean‐Noël. (2020). The ERA5 global reanalysis. doi:10.1002/qj.3803

[2] DOI Hersbach, H.; Bell, B.; Berrisford, P.; Hirahara, S.; Horányi, A.; Muñoz‐Sabater, J.; Nicolas, J.; Peubey, C.; Radu, R.; Schepers, D.; Simmons, A.; Soci, C.; Abdalla, S.; Abellan, X.; Balsamo, G.; Bechtold, P.; Biavati, G.; Bidlot, J.; Bonavita, M.; De Chiara, G.; Dahlgren, P.; Dee, D.; Diamantakis, M.; Dragani, R.; Flemming, J.; Forbes, R.; Fuentes, M.; Geer, A.; Haimberger, L.; Healy, S.; Hogan, R.J.; Hólm, E.; Janisková, M.; Keeley, S.; Laloyaux, P.; Lopez, P.; Lupu, C.; Radnoti, G.; de Rosnay, P.; Rozum, I.; Vamborg, F.; Villaume, S.; Thépaut, J-N. (2017). Complete ERA5 from 1940: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service (C3S) Data Store (CDS) (Accessed on 16-JUN-2022) Data distribution by the German Climate Computing Center (DKRZ). doi:10.24381/cds.143582cf

Attached Datasets ( 3 )

Parent project(s)

PolarRES: Global variable-resolution ICON simulations with polar refinements

[Entry acronym: PolarRES_ICON] [Entry id: 5285856]