Weibin Chen

"Leveraging and creating systematic and responsible AI and statistical techniques on sea-ice analysis”

PhD project title:

Integrated Approach to Summer Sea Ice Analysis and Uncertainty Estimation through AI and Advanced Statistical Techniques

  

Weibin Chen

Project description:

Understanding summer sea ice and its inherent uncertainty as currently monitored by satellites is crucial for climate change research. Traditional methods pioneered at UCL and CPOM in the field of radar altimetry have been successfully implemented to retrieve the sea ice thickness but face limitations (especially over melted sea ice surfaces in the summer) that necessitate innovative solutions. The integration of Artificial Intelligence (AI) and advanced statistical techniques is a groundbreaking approach that is bound to become prominent in the design of future satellite missions. AI’s ability to process vast datasets and identify complex patterns offers nuanced insights into sea ice evolution and enhances the adaptability and accuracy of analysis.


My research project aims to develop an integrated approach, amalgamating AI and statistical methods, to advance summer sea ice analysis and reduce associated uncertainties. My work is partly funded and comes in support of the future polar Copernicus altimetry mission CRISTAL (CLEV2ER ESA project). The exploration of synergies between various AI models and statistical frameworks is pivotal for optimising remote sensing processing algorithms which makes them also more robust and adaptable to diverse climate change scenarios. The insights gained will contribute to developing better polar sea ice products, informed climate change strategies, ultimately marking a significant advancement in the field.

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