Uncovering sea ice’s role in polar and global climate systems
Earth system models (ESMs) are complex simulations used to represent interactions between the atmosphere, ocean, land, ice and biosphere. Key objectives include better understanding long-term environmental changes, as well as the impacts of human activity on our climate. “ESMs are essential tools for climate science, but face several challenges,” notes CRiceS(opens in new window) project coordinator Risto Makkonen from the Finnish Meteorological Institute(opens in new window). “These include the complexity and interconnectedness of Earth systems, high computational demands, limited observational data, and the technical hurdles of integrating different model components.”
Connecting simulated and observed polar data
The EU-funded CRiceS project strengthens the accuracy and usefulness of the ESMs by improving their ability to reproduce the state and trends of sea ice, snow on sea ice, and aerosol-cloud systems in the polar regions. “This is important because the impact of polar changes on global climate could impair our future climate projections and ability to adapt to climate change in the next decades,” explains Makkonen. To achieve this, a consortium of world-leading experts from Europe, Canada, India and South Africa was formed. In addition to a strong modelling component, the team included experts experienced in polar observations, measurement campaigns and expeditions. “CRiceS brought the observational and modelling communities together,” adds Makkonen. “We wanted to enhance dialogue on observational constraints for model processes and find ways of connecting simulated and observed data.”
Taking account of complex polar processes
Important model improvements have been made. These include taking account of processes around sea ice, such as snow on sea ice, melt ponds, and atmospheric boundary layer turbulence. The physical realm of sea ice has also been more closely linked to biogeochemical cycles such as the effects of radiative transfer schemes for algal blooms, turbulence in nutrient availability and ice algal growth. Polar aerosol-cloud systems and their coupling to ocean and ice systems have been developed, and new sources of aerosols, such as blowing snow, introduced into models. “These enhanced CRiceS models were then validated with a vast amount of multidisciplinary observations in the polar regions,” says Makkonen. “The teams are currently carrying out final simulations. From these, we aim to show the complexity of polar processes like sea ice and the necessity of including these processes in future climate projections.”
More precise polar climate system interactions
The CRiceS project has advanced polar climate research in many directions. Increased understanding of processes related to sea ice, improved tools, synthesised data products and other research outputs(opens in new window) will now be used to benefit future research projects. “Modelling communities will have the opportunity to introduce more precise polar climate system interactions and feedback mechanisms,” remarks Makkonen. “This will ultimately lead to enhanced projections of the polar climate and its impact on the global climate system. We were successful in bringing together modelling and observational communities from several research domains, and we envision that this foundation will support future collaborations and networks within Europe and beyond.” CRiceS-developed components will now feed into CMIP7(opens in new window) model simulations, part of an international effort to improve ESMs that is essential to the work of the Intergovernmental Panel on Climate Change(opens in new window) (IPCC). The project team has also identified artificial intelligence (AI) as likely to play a key role in future climate models. “Future climate models will have some components integrating AI,” adds Makkonen. “AI could also prove helpful in bringing together polar observations and model data, perhaps giving recommendations on observational capacity or model improvements.”
