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

Email: h.weller@reading.ac.uk

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


Additional outcomes:

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.

Additional Costs (specified where applicable):

1) Required text books: 2) Specialist equipment or materials: 3) Specialist clothing, footwear or headgear: 4) Printing and binding: 5) Computers and devices with a particular specification: 6) Travel, accommodation and subsistence:


Last updated: 11 April 2019

THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.

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