Project description
Improved models to simulate Arctic Ocean ice in summer
As the Arctic Ocean ice rapidly diminishes owing to climate change, the demand for accurate and timely ice forecasts is growing. However, certain challenges in data processing limit availability of summer observations, creating a key observation gap for polar research. Funded by the European Research Council, the SI3D project aims to fill this gap by harnessing deep machine learning and radar altimeter response modelling. By integrating satellite data from multiple ESA missions, SI3D plans to create a high-accuracy record of the sea ice thickness spanning 15 years, including the summer months. This unique data set will enhance understanding of seasonal decay mechanisms and improve sea ice forecasts. Project results could help transform Arctic system science, improving modelling, forecasting, mass budgeting and biogeochemistry studies during the critical summer melting months.
Objective
Arctic sea ice is diminishing with climate warming at a rate unmatched for 1000 years. As the receding ice pack changes rapidly and becomes increasingly mobile, the demand from academic and commercial stakeholders for accurate and timely sea ice forecasts is intensifying. Forecasting accuracy is enhanced with the assimilation of sea ice thickness observations from satellite altimetry. However, these data are currently unavailable during summer when they would be most valuable for stakeholders, owing to significant data processing challenges. This has been identified as a key observation gap for polar research by the IPCC.
SI/3D will address this gap, harnessing deep machine learning, modelling of the radar altimeter response, and dedicated field campaigns, to overcome the processing barriers. I will integrate satellite data from multiple ESA, EU-Copernicus, and NASA altimetry missions to produce the first 15+ year high-accuracy record of pan-Arctic sea ice thickness without interruptions in the summer. With this unique dataset, I can achieve the following goals. (1) To close the Arctic sea ice volume budget, pinpointing the mechanisms driving seasonal decay and breakup of the ice pack and the feedbacks of sea ice loss on Arctic temperatures. (2) To upgrade seasonal sea ice forecasts from state-of-the-art modelling systems by assimilating summer ice thickness observations.
SI/3D will create a new discipline of sea ice research by using altimetry to study the Arctic summer, which is risky. Having led the first published pilot research in this field, however, I am ideally placed to carry out the project and will leverage the expertise I have gained at three international Arctic research institutions to make it happen. On completion, this work will transform opportunities for Arctic system science, improving sea ice modelling, forecasting on timescales from weeks to years, mass budgeting, and biogeochemistry studies during the critical summer melting months.
Fields of science
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
- natural sciencesearth and related environmental sciencesphysical geographyglaciology
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencescomputer and information sciencesdata sciencedata processing
- natural sciencescomputer and information sciencessoftwaresoftware applicationssimulation software
Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
9019 Tromso
Norway