Singapore Government
Mr Joshua LEE

Mr Joshua LEE

Research Scientist
Department of Weather Research
Weather Modelling Development Branch


Mr Joshua LEE

Mr Joshua Lee’s work in CCRS focuses on improving the data assimilation system for SINGV, a convective-scale numerical prediction model for Singapore, as part of a team. Prior to this, he worked on the Madden-Julian Oscillation and its teleconnections, as a potential source of sub-seasonal/seasonal predictability. Aside from his research interest in data assimilation, he is also excited about the possibility of implementing machine learning techniques in weather forecasting.


    • 2017-2018
    • MSc in Atmosphere, Ocean and Climate, University of Reading, United Kingdom
    • 2014-2017
    • BSc in Mathematics and Meteorology, University of Reading, United Kingdom

Working Experience

    • 2018-present
    • Research Officer/Scientist, Centre for Climate Research Singapore, MSS

Research Interests

  • Data assimilation
  • Sub-seasonal/Seasonal predictions
  • Madden-Julian Oscillation
  • Applications of machine learning in meteorology

Lee, J. C. K., Lee, R. W., Woolnough, S. J., and Boxall, L. J., 2020:

The links between the Madden-Julian Oscillation and European weather regimes.

Theoretical and Applied Climatology, 141, 567-586.

Lee, J. C. K., and Huang, X.-Y., 2020:

Background error statistics in the tropics: Structures and impact in a convective-scale numerical weather prediction system.

Quarterly Journal of the Royal Meteorological Society, 146, 2154-2173.

Lee, J. C. K., and Klingaman, N. P., 2018:

The effect of the quasi-biennial oscillation on the Madden-Julian oscillation in the Met Office Unified Model Global Ocean Mixed Layer configuration.

Atmospheric Science Letters, 19(5), e816.