AI for Seasonal Sea Ice Forecasting (IceNet)

Start date
1 September, 2019
End date
1 December, 2025

IceNet is a probabilistic, deep learning sea ice forecasting system developed by an international team and led by British Antarctic Survey and The Alan Turing Institute [Andersson et al., 2021]. IceNet has been trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. IceNet advances the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model in seasonal forecasts of summer sea ice, particularly for extreme sea ice events. This step-change in sea ice forecasting ability brings us closer to conservation tools that mitigate risks associated with rapid sea ice loss.


News, Blogs and Podcasts


  • Seasonal sea ice forecasting
  • Provide decision support information for wildlife conservation efforts
  • Aid efficient route-planning for the RRS Sir David Attenborough ship and autonomous underwater vehicles (AUVs)
  • To help understand the drivers of sea ice change using explainable AI methods