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SDS 426/ ES 416: Atmospheric Modelling

Course Title

Atmospheric Modelling

Course Code

SDS 426 / ES 416

Course Type

Elective

Level

Master’s

Year / Semester

2nd Semester

Instructor’s Name

Assoc. Prof. Theodoros Christoudias (Lead Instructor), Prof. Johannes Lelieveld, Assoc. Prof. Panos Hadjinicolaou, Dr Demetris Charalambous

ECTS

10

Lectures / week

3

Laboratories / week

None

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.

Prerequisites

None

Requirements  

Course Content

W1: Introduction to Atmospheric Modelling W2: Governing Equations and Assumptions

W3: Programming Numerical Solutions to the Equations W4: Spectral Models

W5: Physical-process Parameterizations W6: Boundary Conditions

W7: Data Assimilation

W8: Experimental Design in Model-based Research

W9: Atmospheric Predictability and Ensemble Forecasting W10: Atmospheric Chemistry Modelling

W11: Coupled Special-applications Models W12: Climate Modelling and Downscaling

W13: Post-processing Enhancement of Model Data

Teaching Methodology

Lectures. Seminars. Case studies. Literature Reviews. Project.

Bibliography

  • “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

Assessment

Coursework and exam

Language

English

Publications & Media