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Mr Sizhe Chen

PhD student

Machine Learning for past climate reconstruction: Identifying AMOC variations using climate-proxy fingerprints



  • 2022-present: PhD candidate in Geography, Downing College, University of Cambridge, UK
  • 2018-2022: BA in Atmospheric Sciences, SYSU


  • BA in Atmospheric Sciences, SYSU


  • SYSU University Outstanding Graduation Thesis Award (2022)
  • SYSU First-class Scholarship – Outstanding Student Scholarship (2021)
  • SYSU Special Scholarship for Discipline Competition (2021)
  • SYSU Special Scholarship for Academic Progress (2020)


My research aims to apply machine learning methods and use climate proxy fingerprints to generate historical AMOC strength. The Atlantic meridional overturning circulation (AMOC) is a key driver of the global climate system. Despite its importance, direct and continuous mooring measurement of AMOC only started in 2004, which is too short to quantify multidecadal and longer-term variations. Climate-proxy fingerprints have been widely seen as a useful tool to reconstruct AMOC strength beyond the instrumental period. In my project, I’m planning to use the AMOC climate-proxy fingerprints and machine learning methods to reconstruct AMOC at high temporal resolution for the past 2000 years.



  • Lin, Y., Yang, Q., Li, X., Yang, C., Wang, Y., Wang, J., Liu, J., Chen, S., & Liu, J. (2023). Optimization of the k-nearest-neighbors model for summer Arctic Sea ice prediction. Frontiers in Marine Science, 10, 1260047.