Kenneth Chan

Department IMPRS
Group IMPRS doctoral candidate
Position Phd Candidate
phone +49 40 42838-5331
Email kenneth.chan@mpimet.mpg.de
Room G 1639

Research

Stratocumulus clouds are particularly common in the subtropical regions and cover one-fifth of the Earth's surface. They regulate the climate and create a cooling effect on the surface through the reflection of the incoming solar radiation. Stratocumulus coverage will decrease with the current warming conditions, but how much remains unclear. The strong coupling between metre-scale processes in the cloud-top region, the free troposphere and the SST complicates the projections. Numerical models with insufficient resolution overestimate mixing and mask the sensitivity of stratocumulus to changes in the environmental conditions. How reliable are then these models when used to study the role of stratocumulus in the climate system?

Direct numerical simulations with increased resolution improve the representation of mixing, such that radiation effects can be better accessed. In my research, the microscale model will be coupled with the radiative transfer model to study the effect of water vapour in longwave radiation, as well as the shortwave radiation and the diurnal cycle of stratocumulus.

Supervisors: Prof. Juan Pedro Mellado, Prof. Stefan Bühler

Curriculum Vitae

Education

Since 2023: PhD Candidate at the Max Planck Institute for Meteorology, Hamburg, Germany


2021 - 2023: MSc Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland

  • Thesis: Evaluating Potential Impact of Seeding Tropical Cyclones with Aerosols in the Numerical Model ICON

2016 - 2021: BSc Physics (1st major) and Earth System Science (2nd major), The Chinese University of Hong Kong, Shatin, Hong Kong

  • 1st Thesis: Probability of Occurrence of Strong and Gale Force Winds in Hong Kong during the Passage of Tropical Cyclones
  • 2nd Thesis: Tropical Cyclone Intensity Forecast using ECMWF EPS with Machine Learning

Practical Experience

2019 - 2020: Student Intern at Hong Kong Observatory, Tsim Sha Tsui, Hong Kong

  • 1st Project: Machine Learning in Calibrating Tropical Cyclone Intensity Forecast of ECMWF EPS
  • 2nd Project: Enhancing Automatic Weather Forecast System (Wind & Thunderstorm)
  • 3rd Project: Probability of Occurrence of Strong and Gale Force Winds in Hong Kong during the Passage of Tropical Cyclones

Teaching 

2021: Teaching Assistant of the course "Ecosystems and Climate" at The Chinese University of Hong Kong, Shatin, Hong Kong

Publications

Chan, M. H. K., Wong, W. K., & Au-Yeung, K. C. (2021). Machine learning in calibrating tropical cyclone intensity forecast of ECMWF EPS. Meteorological Applications28(6), e2041. https://doi.org/10.1002/met.2041

 

Master's Thesis

Chan, K. (2023): Evaluating Potential Impact of Seeding Tropical Cyclones with Aerosols in the Numerical Model ICON

  • Supervisors: Prof. Ulrike Lohmann & Nadja Omanovic

Bachelor's Thesis

Chan, M. H. K. (2020): Probability of Occurrence of Strong and Gale Force Winds in Hong Kong during the Passage of Tropical Cyclones

  • Supervisors: Prof. Francis Tam & Chun-wing Choy

Chan, M. H. K. (2020): Tropical Cyclone Intensity Forecast using ECMWF EPS with Machine Learning

  • Supervisors: Prof. Francis Tam & Wai-kin Wong