## MTMW14-Numerical Modelling of Atmospheres and Oceans

Module Provider: Meteorology
Number of credits: 10 [5 ECTS credits]
Level:7
Terms in which taught: Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites: MTMW12 Introduction to Numerical Modelling MTMW11 Fluid Dynamics of the Atmosphere and Oceans
Modules excluded:
Module version for: 2017/8

Module Convenor: Prof Pier Luigi Vidale

Summary module description:
Numerical models are central to predicting the evolution of fluid flows, including weather forecasting and climate simulation. Atmosphere and ocean science has advanced rapidly by using models; they represent the essence of what we know about fluid behaviour and enable us to obtain approximate solutions for complex, nonlinear problems where analytic solutions are unknown. This module considers the formulation of model equations, schemes to solve them numerically and ways in which model performance can be evaluated using knowledge of fluid properties and phenomena. You will also implement idealised models yourself to solve problems using computer programming.

Aims:
To show how numerical schemes can be designed to preserve fundamental properties of fluid flows. To bring you up to speed with the core components of state-of-the-art numerical models for the atmosphere and oceans and their use in predicting weather and climate.

Assessable learning outcomes:

By the end of this module the student should be able to:

• Recognise the strengths and weaknesses of the main numerical methods used to model the atmosphere and oceans and explain their derivation;

• Design numerical models to solve atmosphere/ocean problems;

• Implement idealised models by programming in Python and FORTRAN (or C++);

• Evaluate models using benchmark problems and known properties of the system.

Knowledge of the key historical events in the development of numerical models of the atmospheres and oceans.

Outline content:

LECTURES:

1. Fundamental properties of atmospheres and oceans and the first numerical models;

2. Finite difference methods: advanced time schemes;

3. Fluids on rotating Earth and 2-D finite difference schemes;

4. Wave dispersion in finite difference models;

5. Alternative numerical methods for transport by the flow;

6. Using complex nonlinear models (chaos and predictability);

7. Advanced methods - discrete representation of spatial distributions;

8. Advanced methods - spectral techniques;

9. Parameterizations of unresolved processes.

PRACTICALS:

Week 1: Solve oscillatory, 1-D advection, and diffusion problems;

Weeks 2-5: Project 1, Ensemble simulation with a reduced model of El Niño Southern Oscillation;

Weeks 7-10: Project 2, Wind driven ocean gyre modelled using shallow water equations;

Week 10: Test.

Brief description of teaching and learning methods:

Lectures including some problem solving within class in small groups. Practicals in the computing lab, working individually but with help from lecturer and demonstrators.

Contact hours:
 Autumn Spring Summer Lectures 9 Practicals classes and workshops 18 Guided independent study 73 Total hours by term 100.00 Total hours for module 100.00

Summative Assessment Methods:
 Method Percentage Report 70 Class test administered by School 30

Other information on summative assessment:
Two projects solving atmosphere/ocean problems by designing numerical models and implementing them using computer programs. Each project assessed by a scientific report on it. A 90 minute test during the week 10 session.

Formative assessment methods:

Penalties for late submission:
Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information: http://www.reading.ac.uk/internal/exams/student/exa-guidePG.aspx

Length of examination:
90 minute class test in Autumn term. Answer all 5 questions.

Requirements for a pass:

50% overall.

Reassessment arrangements:
For candidates who have failed, an opportunity to take a resit examination will be provided within the lifetime of the course.