IceNet is a deep learning sea ice forecasting system developed by an international team and led by the British Antarctic Survey and The Alan Turing Institute. The original IceNet research model, published in Nature Communications was trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. This version advanced the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model (ECMWF SEAS5) in seasonal forecasts of summer sea ice, particularly for extreme sea ice events.
Since then, the IceNet team has focussed on building an operational version of the model which forecasts on a daily resolution. The original research code was refactored into icenet - a library for operational forecasting. The icenet library can support further research efforts into AI-based operational sea ice forecasting.
In addition, several use cases and an ecosystem of service components are contained within this organisation, supporting execution and downstream analysis.
For further information about the team involved, please look at the project pages at BAS or The Alan Turing Institute.”
Repositories
The various repositories under the IceNet project, click for more information
A list of outputs
2021
2021
A detailed walkthrough the research.
2021
Tom Andersson describing IceNet.
2022
Demonstration of the original proof of concept pipeline approach online for AI UK 2022 with James Byrne and James Robinson.
2023
James Byrne described how the IceNet project used software engineering to operationalise research for climate science at Climate Informatics 2023.
2023
Scott Hosking of BAS and The Alan Turing Institute highlighting the importance of AI approaches on Al Jazeera.
The IceNet project is a collaboration between The Alan Turing Institute and British Antarctic Survey. It’s only made possible thanks to the contributions of many across the environmental research, data science and international sea-ice and ecosystems communities at large. The names here are only those who continually manage the project, but many more have been responsible for the innovation and research that makes IceNet “an infrastructure for the future”!
Principal Investigation
Lead Research Software Engineer
Ecosystems Researcher
Research Application Manager
Original ML Researcher
Research Software Engineer
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