Climate Modelling
We investigate the coupled Arctic climate system with the overall aim to (i) improve our understanding and model representation of key climate processes in the Arctic and (ii) to improve our understanding of Arctic – midlatitude linkages. We apply regional and global climate models for associated research. Our climate modelling research is part of national and international research projects, such as AC3, REKLIM, Arctic CORDEX, PolarRES, and WarmWorld.
Background
The phenomenon of Arctic amplification has a suite of causes, which include various interconnected processes and feedbacks, such as sea ice loss and albedo feedback, meridional atmospheric and oceanic energy fluxes, and radiation-climate feedbacks linked with temperature, water vapor, clouds and ozone. The relative importance of these different feedback mechanisms is still subject of debate. In parallel, climate models have difficulties in reproducing the observed drastic Arctic climate changes and the uncertainty in Arctic climate projections is large. That arises, in large part, from gaps in our understanding of key Arctic processes and feedbacks.
A large body of evidence demonstrates how changes in the Arctic climate influence weather and climate at lower latitudes (Cohen et al., 2020). For example, declining Arctic sea ice is linked to atmospheric circulation changes (Jaiser et al., 2023), which in turn affect climate extremes in the Northern Hemisphere midlatitudes, including Central Europe (Riebold et al., 2023). The Arctic interacts with lower latitudes through both tropospheric and stratospheric pathways, primarily via horizontal advection of heat and moisture and planetary wave dynamics within the coupled troposphere-stratosphere system (Hanna et al., 2024).
However, the coupling and impacts of the Arctic climate system to lower latitudes is not fully understood. The knowledge on Arctic-midlatitude linkages we gained through our research is disseminated via the Sea Ice Portal (read more here and here) and REKLIM.
Regional Modelling
The ICON model (Zängl et al., 2015) is set up in limited area mode (LAM) over the Arctic region. Simulations are performed for the Arctic at horizontal grid resolutions of down to ca. 2.5 km. Simulation results show the ability of ICON-LAM to represent the observed spatio-temporal structure of the selected moisture intrusion event and its signature in the temperature, humidity, and wind profiles, and in the surface radiation (Bresson et al., 2022; Kirbus et al., 2023; Tiedeck, 2025). Ongoing research is on MOSAiC-related modeling studies, specifically on atmospheric rivers and surface energy budget processes.
In addition to ICON-LAM, we have applied the large eddy model (LEM) version of ICON (Dipankar et al., 2015) as a high-resolving mesoscale model with horizontal grid-scales between 800 m and 100 m using a non-idealized setup with lateral boundary forcing from downscaled weather analysis data and lower boundary conditions ideally derived from MOSAiC data.
The primary objective was to evaluate boundary layer and surface processes in the sea-ice covered central Arctic (Littmann, 2024) in order to improve the description of these processes also in larger-scale versions of the ICON model.
HIRHAM-NAOSIM is a coupled regional climate model for the Arctic (Dorn et al., 2019; Dorn Klimanavigator arcticle), primarily designed for improving our understanding of key physical processes in atmosphere, sea ice, and ocean, which are involved in interactions that play a major role in the coupled Arctic climate system. On the one hand, we apply the coupled model to analyze regional feedback processes (Wendisch et al., 2022), including mechanisms of cyclone impacts on sea ice (Aue et al., 2023); on the other hand, we use the coupled model as a test bed for adapted parameterizations and process-based evaluation under quasi realistic atmospheric boundary conditions (Jäkel et al., 2024; Foth et al., 2024). Ongoing research in this context is on improved parameterization of processes related to snow on sea ice, open-water leads, and the heat and momentum exchange at the air-ice and ice-ocean interfaces.
The Community Land Model (CLM5; Lawrence et al., 2019) is part of the Community Earth System Model (CTSM) (https://github.com/ESCOMP/CTSM). It is used in modelling permafrost-related processes in the Arctic. It has replaced our earlier research with CLM4.5 (Matthes et al., 2017). The CLM5 simulations are evaluated with extensive land data sets (soil temperatures, active layer thickness, soil temperatures, and permafrost extent). Sensitivity of the permafrost representation with respect to soil texture, soil organic matter, and snow thermal conductivity is explored (Damseaux, 2024; Damseaux et al., 2024). The coupling to the atmospheric component ICON-LAM is ongoing.
Aue, L., L. Röntgen, W. Dorn, P. Uotila, T. Vihma, G. Spreen, and A. Rinke, 2023: Impact of three intense winter cyclones on the sea ice cover in the Barents Sea: A case study with a coupled regional climate model, Front. Env. Sci., https://doi.org/10.3389/feart.2023.1112467
Damseaux, A., Matthes, H., Dutch, V. R., Wake, L., and Rutter, N., 2024: Impact of Snow Thermal Conductivity Schemes on pan-Arctic Permafrost Dynamics in CLM5.0, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-1412
Damseux, A.,2024: Improving permafrost dynamics in land surface models: insights from dual sensitivity experiments, Dissertation, Univ. Potsdam, https://doi.org/10.25932/publishup-63945
Foth, L., Dorn, W., Rinke, A., Jäkel, E., and Niehaus, H., 2024: On the importance to consider the cloud dependence in parameterizing the albedo of snow on sea ice, The Cryosphere, 18, 4053–4064, https://doi.org/10.5194/tc-18-4053-2024
Jäkel, E., et al. , 2024: Observations and modeling of areal surface albedo and surface types in the Arctic, The Cryosphere, 18, https://doi.org/10.5194/tc-18-1185-2024
Lawrence, D. M., et al. (2019). The Community Land Model Version 5: Description of New Features, Benchmarking and Impact of Forcing Uncertainty. Journal of Advances in Modeling Earth Systems, 11(12):4245–4287.
Littmann, D., 2024: Large eddy simulations of the Arctic boundary layer around the MOSAiC drift track, Dissertation, Univ. Potsdam, https://doi.org/10.25932/publishup-62437
Kirbus, B., et al., 2023: Surface impacts and associated mechanisms of a moisture intrusion into the Arctic observed in mid-April 2020 during MOSAiC, Front. Earth Sci., https://doi.org/10.3389/feart.2023.1147848
Matthes, H., A. Rinke, X. Zhou, and K. Dethloff (2017), Uncertainties in coupled regional Arctic climate simulations associated with the used land surface model, J. Geophys. Res. Atmos., 122, 7755–7771, https://doi.org/10.1002/2016JD026213
Tiedeck, S., 2025: Atmospheric rivers in the Arctic: Physical processes and impact on the surface energy budget, Dissertation, Univ. Potsdam, https://doi.org/10.25932/publishup-67022
Wendisch, M., et al., 2022: Atmospheric and surface processes, and feedback mechanisms determining Arctic amplification: A review of first results and prospects of the AC3 project, BAMS, https://doi.org/10.1175/BAMS-D-21-0218.1
Global Modelling
We employ the global ICON model (Zängl et al., 2015) to investigate the mechanisms driving polar-midlatitude linkages. We aim to improve the understanding of the underlying mechanisms with a focus on tropo-stratospheric interactions (Köhler et al, 2023). In addition, we investigate the effects that better represented dynamical and physical atmospheric processes in the polar regions have on the simulation of polar-lower latitude teleconnections. We apply two complementary approaches to improve the representation of Polar processes relevant for Polar-lower-latitude linkages
(1) Better described small-scale physical processes (improved physical parametrizations)
(2) Better resolved polar processes through regional refinement (for details see figure on the right side)
To follow approach (1) we concentrate on the impact improved description of the gravity wave-drag (Köhler et al., 2021) and on an improved description of boundary layer and surface processes (as in Khosravi, 2023, Sea Ice Portal read more here and here) on our model simulations in close collaboration with the regional modelling group. Approach (2) relies on recent model development and computational improvements which allow for simulating climate dynamics at different spatial scales on a global domain on a varying mesh. This allows for resolving the polar regions at spatial scales between 5-13 km (typical for regional climate models), while retaining resolutions of about 50 km (typical for state-of-the-art global climate models) for the rest of the globe. We implemented this set-up for the global ICON model (see figure on the right side) in the framework of the EU project PolarRES and evaluate the impact of better resolved polar processes on polar-lower latitude linkages for the present-day climate and for climate change storylines for the last decade of the 21st century.
Cohen, J., Zhang, X., Francis, J. et al. including Handorf, D., 2020: Divergent consensuses on Arctic amplification influence on midlatitude severe winter weather. Nat. Clim. Chang. 10, 20–29. https://doi.org/10.1038/s41558-019-0662-y
Hanna, E. et al. incl. Jaiser, R., Köhler, R., 2024: Influence of high-latitude blocking and the northern stratospheric polar vortex on cold-air outbreaks under Arctic amplification of global warming. Environmental Research: Climate, 3(4), 042004, https://doi.org/10.1088/2752-5295/ad93f3
Jaiser, R., Akperov, M., Timazhev, A., Romanowsky, E., Handorf, D., and Mokhov, I., 2023: Linkages between Arctic and Mid-Latitude Weather and Climate: Unraveling the Impact of Changing Sea Ice and Sea Surface Temperatures, Meteorol. Z., 32, 173–194, https://doi.org/10.1127/metz/2023/1154
Khosravi, S. (2023): The effect of new turbulence parameterizations for the stable surface layer on simulations of the Arctic climate, Dissertation, Univ. Potsdam, https://doi.org/10.25932/publishup-64352
Köhler, R., Handorf, D., Jaiser, R., Dethloff, K., Zängl, G., Majewski, D., and Rex, M., 2021: Improved circulation in the Northern Hemisphere by adjusting gravity wave drag parameterizations in seasonal experiments with ICON‐NWP, Earth Space Sci., 8(3), e2021EA001676, https://doi.org/10.1029/2021EA001676
Köhler, R.H., Jaiser, R., and Handorf, D., 2023: How do different pathways connect the stratospheric polar vortex to its tropospheric precursors? Weather Clim. Dyn., 4, 1071–1086, https://doi.org/10.5194/wcd-4-1071-2023
Riebold, J., Richling, A., Ulbrich, U., Rust, H., Semmler, T., & Handorf, D. (2023): On the linkage between future Arctic sea ice retreat, Euro-Atlantic circulation regimes and temperature extremes over Europe. Weather and Climate Dynamics, 4(3), 663-682, https://doi.org/10.5194/wcd-4-663-2023
Zängl, G., Reinert, D., Rípodas, P., & Baldauf, M. (2015). The ICON (ICOsahedral Non‐hydrostatic) modelling framework of DWD and MPI‐M: Description of the non‐hydrostatic dynamical core. /Quarterly Journal of the Royal Meteorological Society/, /141/(687), 563-579, https://doi.org/10.1002/qj.2378 <https://doi.org/10.1002/qj.2378
Contact
Regional Modelling
Dr Annette Rinke
Global Modelling
Dr Dörthe Handorf