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ES 416: Atmospheric Modelling

Course Title

Atmospheric Modelling

Course Code

ES 416

Course Type




Year / Semester

1st / 2nd (Subject to change)

Instructor’s Name

Theodoros Christoudias (Lead Instructor), Johannes Lelieveld, Panos Hadjinicolaou, Andrea Pozzer, Demetris Charalambous



Lectures / week

1 (3h)

Laboratories / week


Course Purpose and Objectives

The numerical methods, formulation and parameterizations used in models of the circulation of the atmosphere will be described in detail. Widely used numerical methods will be the focus but we will also review emerging concepts and new methods. The numerics underlying a hierarchy of models will be discussed, ranging from simple GFD models to the high-end GCMs with atmospheric chemistry. Parameterizations of convection and large scale condensation, the planetary boundary layer and radiative transfer will be reviewed.

Learning Outcomes

At the end of the course students should be able to: use atmospheric models currently used in research, meteorological and air quality institutes and consultancies; address how modelling can assist in understanding societal relevant environmental problems e.g. extreme weather, wind, energy or air quality; design numerical experiments related to specific research questions; explain and discuss the principles and theory of atmospheric models from local to regional scales; assess the potential applications of these models and their limitations; apply these models in real working situations to understand and interpret meteorological and air quality phenomena; evaluate model performance by comparison of model results with observations or other models; present model results and their analysis, related to concrete research questions.




Course Content

1. Introduction to Atmospheric Modelling
2. Governing Equations and Assumptions
3. Programming Numerical Solutions to the Equations
4. Spectral Models
5. Physical-process Parameterizations
6. Boundary Conditions
7. Data Assimilation
8. Experimental Design in Model-based Research
9. Atmospheric Predictability and Ensemble Forecasting
10. Atmospheric Chemistry Modelling
11. Coupled Special-applications Models
12. Climate Modelling and Downscaling
13. Post-processing Enhancement of Model Data

Teaching Methodology

Lectures. Seminars. Case studies. Literature Reviews. Short Projects.


“Numerical Weather and Climate Prediction”, Thomas Tomkins Warner, Cambridge University Press, ISBN 978-0-521-51389-0

"Fundamentals of Atmospheric Modelling", Jacobson, Cambridge University Press

"Atmospheric Modelling, Data Assimilation and Predictability", Eugenia Kalnay, Cambridge University Press


Coursework and exam



Publications & Media