Innovative digital twin tools for sea ice in the Arctic and Baltic contexts

The project started in February 2023 and will finish in January 2025. It produces case studies of cryosphere digital twin applications at the interface between science and policy by piloting new models for climate information and impact sectors such as navigability, engineering and vessel design, fishing and shipping, and renewable energy. The tools developed by NOCOS DT will improve climate-smart practices and assessment of climate-related risks making shipping in the Arctic and Baltic Sea safer and more efficient.

This is an overview of where we are now, one year into the project.

Novel methodology using HiDEM code for sea ice applications

Throughout 2023 the HiDEM (Helsinki Discrete Element Model) code, that was initially developed for generic investigation of fragmentation processes and glacier calving, has been adapted to model sea ice breakup. Sea ice breakup events produce drift and pack ice that have significant impact on shipping, off-shore infrastructure, as well as fishing and hunting on sea ice. One of the major objectives of this development has been to construct discrete element model tools to act as complements to more traditional rheology based sea-ice dynamics forecasts models. As a specific application HiDEM is currently used for investigating the interaction of sea ice with off-shore wind-power pylons. The work with HiDEM is a collaboration between CSC – IT Center for Science, the Aalto University, and the Finnish Meteorological Institute. 

Towards holistic understanding in improving navigability

Arctic shipping has significantly increased and the shipping season extended in the past few decades. Occasions of ships navigating in extreme ice conditions have tripled. As one of its key topics, NOCOS DT has focused on the Arctic transpolar route aiming at developing statistics on how the Risk Index Outcome varies seasonally along the route, especially since shipping activity has increased significantly on the transpolar route.

NOCOS DT has investigated the near-cast and now-cast Risk Index Outcome (RIO), which can be used as a climate indicator for real-time navigation decision-making for ships in various ice conditions. The novelty of developing such a tool is to calculate the climate indicator from modeling sea ice data in order to have an insight on past and future navigability in the Arctic Ocean. The NOCOS DT project utilized three modeling data sources to develop the climate indicator based on the Risk Index Outcome algorithm from global forecasting products. In the future, the historical sea ice regime and projection on future sea ice scenario by the Climate Change Adaptation Digital Twin model will be included in the same script to produce Risk Index Outcome climate statistics.

Integrating diverse perspectives in user-relevant sea ice climatologies

Sea ice may offer opportunities and entail risks for people working or living in ice-covered regions. NOCOS DT contributes to increasing preparedness in and near ice-covered areas. The project utilises existing hindcast simulations similar to those of the Climate Adaptation Digital Twin (Climate DT) and remotely sensed products in order to demonstrate how user-tailored information could be derived from the envisioned Climate DT simulations. The project produces tools for analysing landfast ice, ridged ice, Marginal Ice Zone as well as optimisations for Marine Spatial Planning platforms.

Moreover, the project has developed scripts for landfast sea ice, based on the Danish Meteorological Institute’s hindcast and forecast products. The project is deriving a tool for analysing whether or not sea ice is landfast. The criterion for landfast sea ice is primarily built on the modeled velocities whereas the areas of landfast sea ice are validated with ice charts. Further ongoing key conclusions of the project are calculations on models enabling predicting ridging ice likelihood and the Marginal Ice Zone (MIZ). From the high-resolution regional ice model simulations, ice ridging is estimated using both a process-based approach and a threshold method based on ice state variables.

Utilization of climate data in Marine Spatial Planning 

In the context of Marine Spatial Planning (MSP), following discussions with the Swedish Agency for Marine and Water Management and the Nordic-Baltic Marine Spatial Management Tool project (financed by the Nordic Council of Ministers), the project has been preparing aggregated information from high-resolution ocean and sea ice model projections available in the Network Common Data Form (NetCDF) format. This consists of a Python package for aggregating and preparing Marine Spatial Planning relevant ocean climate model output data. The focus was on ice information, which has been shown to have important impacts on certain ecosystem components, such as seals. The package is optimized to handle large, multi-ensemble data sets and to present ensemble mean and uncertainty information. It will be further developed to handle extreme climate information, e.g. about marine heat waves.

What’s coming up in 2024?

The second phase of NOCOS DT builds on the results of the first one. The overall focus is on using the Climate DT data that will become available in 2024. On the use case level, the objectives include applying the discrete element model based sea ice model to drift ice dynamics, integrating landfast sea ice and Marginal Ice Zone tools and an ice ridging probability description method into Climate DT, as well as continued code development on multiple fronts. The plan is also to communicate the project to a wider audience, including attending several international events, such as EGU2024 conference.

Read more 

Publications by the project about the Marginal Ice Zone

• Wang, K., Ali, A., and Wang, C.: Local analytical optimal nudging for assimilating AMSR2 sea ice concentration in a high-resolution pan-Arctic coupled ocean (HYCOM 2.2.98) and sea ice (CICE 5.1.2) model, The Cryosphere, 17, 4487–4510, https://doi.org/10.5194/tc-17-4487-2023, 2023.
• Wang , K., Caixin Wang, Frode Dinessen, Gunnar Spreen, Robert Ricker and Xiangshan Tian-Kunze, Multisensor data fusion of operational sea ice observations, submitted to Frontiers in Marine Science, accepted.

The Discrete Element Model HiDEM is a generic code for ice fracture, and the development for sea ice modelling within this project is done in parallel with other projects, and has recently produced and contributed to the following scientific publications:

• A large-scale high-resolution numerical model for sea-ice fragmentation dynamics. J Åström, J Haapala, A Polojärvi. The Cryosphere Discussions 2023, 1-16, 2023
• Physics of the cryosphere. AF Banwell, JC Burton, C Cenedese, K Golden, J Åström. Nature Reviews Physics 5 (8), 446-449, 2023
• Controls on calving at a large Greenland tidewater glacier: stress regime, self-organised criticality and the crevasse-depth calving law. DI Benn, J Todd, A Luckman, S Bevan, TR Chudley, J Åström, T Zwinger, Journal of Glaciology, 1-16, 2023
• Rapid fragmentation of Thwaites Eastern Ice Shelf. DI Benn, A Luckman, JA Åström, AJ Crawford, SL Cornford, SL Bevan, … The Cryosphere 16 (6), 2545-2564, 2022
• Stability of Ice Shelves and Ice Cliffs in a Changing Climate. JN Bassis, A Crawford, SB Kachuck, DI Benn, C Walker, J Millstein, R Duddu, J Åström, H Fricker, A Luckman. Annual Review of Earth and Planetary Sciences 52, 2024

In October 2023, NOCOS DT produced factsheets about the project and its use cases. Read more: NOrdic CryOsphere Digital Twin boosts digital twin technology in the Nordic and Baltic cryosphere context – Six use cases now online.

Funded by the Nordic Council of Ministers, the Nordic Cryosphere Digital Twin (NOCOS DT) aims at leveraging the Destination Earth Climate Digital Twin for piloting new climate information related products impacting sectors such as navigability, engineering and vessel design, fishing and shipping, renewable energy sectors. It will provide improved modelling and data quality for research of the Arctic and Baltic climate change adaptation. In alignment with the Green Deal objectives, it supports sea ice related data-driven adaptation policies, including measures for traditional hunting and fishing by indigenous people.

Coordinator: CSC – IT Center for Science

Partners: Finnish Meteorological Institute, Danish Meteorological Institute, Tallinn University of Technology, Meteorological Institute of Norway, Swedish Meteorological and Hydrological Institute