Exploring the role of sea ice physics in Arctic climate variability and predictability

Recent observed changes in the Arctic have become a 'poster child' for global climatic changes, particularly because the summer sea ice extent has shrunk rapidly over the past 35 years. This retreat of the sea ice has led to growth of trans-Arctic shipping and plans to extract minerals and fossil fuels from the ocean floor.

Observations of the Arctic have also improved in recent years with new satellites measuring sea ice properties from space. In particular, these satellites now provide estimates of the sea ice thickness across the Arctic during the winter months. This development allows better monitoring of the state of the sea ice and a new way to test and assess our physical understanding and the latest climate model simulations.

The latest assessment of the Intergovernmental Panel on Climate Change (IPCC) concluded that it was likely that the Arctic would become reliably ice-free by 2050 assuming greenhouse gas emissions continue to increase. This change would provide both enormous risks and opportunities.

However, the climate simulations used by the IPCC often fail to realistically capture large scale properties of the Arctic sea ice, such as the extent, variability and recent trends. Therefore, there is a key need to improve simulations of Arctic sea ice to provide better understanding of the recent observed changes and credible projections of the future to help assess risks and opportunities and inform important policy decisions about adaptation and mitigation.

In addition, there is a growing need for shorter-term sea ice forecasts, such as a few weeks or months ahead, to help inform local communities and industry stakeholders, such as shipping companies. This project will seek to better understand the role of natural weather and climate fluctuations in producing recent Arctic sea ice changes on annual to decadal timescales.

One essential ingredient for improving the climate model simulations is to better represent the missing relevant physical processes in the latest sea ice models. This proposal will develop and implement improved physics for the sea ice model, which is used by many international groups, including the Met Office. The enhanced sea ice model will be further developed to improve its simulation of Arctic climate, and its ability to provide more reliable sea ice predictions will also be tested.

Understanding how and why Arctic sea ice conditions change on seasonal to decadal timescales is a critical issue facing international governments and business. Improved predictions of Arctic sea ice through scientific research has economic, social and environmental implications. This research brings together broad international expertise in sea ice model development to ensure maximal benefit to sea ice research, modelling and prediction groups. The Met Office and Los Alamos National Laboratory are both Project Partners offering in-kind support to help deliver the improvements to sea ice models, and visits are planned for both to ensure maximal usage of the research.

The main direct beneficiaries of the knowledge generated by this project will be:

1. The UK Met Office and other international modelling groups who will be able to utilise an enhanced and improved sea ice component in their global climate models

2. Sea ice forecast providers: the improved quantification of Arctic predictability will guide the development of seasonal climate forecasting systems. These include the Met Office, ECMWF and other international groups producing such predictions.

3. The international climate research community, including the IPCC, through collaborative analysis of the Arctic system to understand the causes of recent changes

4. Policy makers (such as DECC, DEFRA and FCO) who will have an improved understanding of the risks and opportunities presented by a changing Arctic. This work also has the potential to be used to inform mitigation and adaptation decisions under the UNFCCC climate negotiations.

5. This project will also enhance future prediction systems for the Arctic and Northern Hemisphere mid-latitudes, which would have benefits to the stakeholders such as the oil, gas and mineral extraction industry, trans-Arctic shipping, tourism and indigenous communities. The general public and local communities would also benefit from improved forecasts.