## MTMW12-Introduction to Numerical Modelling

Module Provider: Meteorology
Number of credits: 10 [5 ECTS credits]
Level:7
Terms in which taught: Autumn term module
Pre-requisites:
Non-modular pre-requisites: A-level mathematics and modules in mathematics in undergraduate degree.
Co-requisites:
Modules excluded:
Current from: 2019/0

Module Convenor: Dr Hilary Weller

Type of module:

Summary module description:
We will derive and analyse a number of numerical methods for solving the type of equations used in atmosphere and ocean modelling. Students will implement some of these methods using the Python programming language.

Aims:

The aim of this module is to familiarise the students with a range of concepts and techniques used in the numerical modelling of atmospheric and oceanic fluid flows.  This will include mathematical analysis, modelling and some good programming practices.

Assessable learning outcomes:

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

• Derive numerical schemes using Taylor series;

• Explain the concept of stability and perform a basic stability analysis;

• Implement and test the behaviour of numerical schemes using Python;

• Recognize sources of numerical error and derive and measure order of accuracy;

• Use Fourier series for analysing both numerical methods and climate data;

• Use functions and loops in Python and avoid code duplication;

• Have some knowledge about how code should be tested

Students will develop skills of working to deadlines and preparing clear, concise written reports.

Outline content:

The lecture content covers:

• Derive finite difference approximations using Taylor series;

• Differential equations with time and space derivatives;

• Techniques for solving the diffusion equation and the advection equation;

• Use of Fourier series:

• Python including use of functions and testing:

The practical classes cover:

• Introduction to Python;

• Implementation of numerical schemes and demonstration of their behaviour.

Brief description of teaching and learning methods:

Lectures, computing practical classes, written reports on practicals and peer instruction.  A list of background reading is supplied with the lecture notes.

Contact hours:
 Autumn Spring Summer Lectures 14 Practicals classes and workshops 18 Guided independent study: 68 Total hours by term 100 0 0 Total hours for module 100

Summative Assessment Methods:
 Method Percentage Report 60 Class test administered by School 40

Summative assessment- Examinations:
1 hour 50 minute class test at the end of the module during the Autumn term. Answer all 4 questions.

Summative assessment- Coursework and in-class tests:
Written exam worth 40%. 55% is made up of 2 assignments involving programming and report writing worth 20% and 35%. The 35% assignment will involve team work.

Formative assessment methods:
Students receive 5% of the final module total for participating in a peer assessed assignment.

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

Assessment requirements for a pass:

A mark of 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.