Learning Numerical Weather Prediction with CPAS: Theory, Practice and Visualization

About

This course is divided into 2 sections. In the first section (1-3 weeks) you can learn about both the theoretical and practical aspects of numerical weather prediction (NWP), including the numerics and discretization method of models, physics parameterization, and practical aspects of running a weather model. You can also get a chance to run a weather model by yourself. In the second section (4-6 weeks) you can learn to use Python programming language to visualize weather data and model simulation results. Contents include data manipulation with numpy, Xarray, pandas, geospatial visualization using cartopy, visualizing weather data through matplotlib and hvplot, and simple model evaluation.  

** This course was a 2-credit summer course delivered in the Chinese University of Hong Kong in 2022.

** This course is an undergraduate-level course that assumes basic knowledge of the general circulation of the atmosphere and basic knowledge of the syntax and libraries of the Python programming language.

Instructors

Lecturer

Chi Chiu (Chris) Cheung

I am a Senior Director of Technology at ClusterTech Limited. I have a Bachelor of Science in Physics with a minor in Computer Science and a Master of Philosophy in Computer Science and Engineering. I have worked on High-Performance Computing, ClusterTech’s main business, for more than 20 years, and in the past 7+ years I have been working on numerical weather prediction.  I am passionate about learning Physics theories and trying out innovative ideas. 

Tutor

Jimmy Wong

I am a Computational Scientist at ClusterTech Limited. I have a Bachelor of Science in Earth System Science (the Chinese University of Hong Kong). I am passionate about atmospheric science and experienced in visualizing and analyzing atmospheric data. I am also working on my Master's Degree in Atmospheric and Climate Sciences.

Offered by

ClusterTech Limited, Hong Kong SAR, China

Syllabus

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