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MT2NSM: Numerical and Statistical Methods for Weather and Climate Science
Module code: MT2NSM
Module provider: Meteorology; School of Mathematical, Physical and Computational Sciences
Credits: 20
Level: Level 2 (Intermediate)
When you'll be taught: Semester 1
Module convenor: Professor Paul Williams, email: p.d.williams@reading.ac.uk
Module co-convenor: Professor Ted Shepherd, email: theodore.shepherd@reading.ac.uk
Pre-requisite module(s): BEFORE TAKING THIS MODULE YOU MUST TAKE MT1SES OR TAKE MT12C OR TAKE MT1SESNU OR TAKE MT12CNU (Compulsory)
Co-requisite module(s):
Pre-requisite or Co-requisite module(s):
Module(s) excluded:
Placement information: NA
Academic year: 2024/5
Available to visiting students: Yes
Talis reading list: Yes
Last updated: 21 May 2024
Overview
Module aims and purpose
This module comprises both a lecture and a computer practical component, which together introduce students to the numerical and statistical methods that are used in weather and climate science. The aim is to provide students with an understanding of the basic theoretical principles involved in both kinds of methods, their appropriate use for weather and climate science, and experience with their practical implementation using computer programs. Because numerical and statistical methods underlie pretty much any application in weather and climate science, this knowledge is essential for correctly deriving or interpreting scientific results.Â
Module learning outcomes
By the end of the module, it is expected that students will be able to:Â
- Develop numerical algorithms for solving equations and implement them as computer programsÂ
- Use numerical analysis to evaluate the results produced by the programs and design ways to improve themÂ
- Describe the main concepts in statistical science and use statistical softwareÂ
- Critically analyse data and draw correct inferences using appropriate statistical methodsÂ
Module content
- Introduction to numerical methodsÂ
- Numerical solution of algebraic equationsÂ
- Numerical solution of ordinary and partial differential equations via finite difference methodsÂ
- Multi-dimensional systems and chaos theoryÂ
- The physical behaviour of solutions to the advection and diffusion equationsÂ
- Accuracy, stability, and convergence of numerical algorithmsÂ
- Introduction to statistics, history and controversiesÂ
- Exploratory data analysis, forecast verificationÂ
- Linear and multiple regressionÂ
- Probability theory, probability distributionsÂ
- Parameter estimationÂ
- Hypothesis testingÂ
Structure
Teaching and learning methods
Lectures are followed by computer practical sessions which are designed to illustrate and give students hands-on experience with the theoretical concepts presented in the lectures.Â
Study hours
At least 62 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.
 Scheduled teaching and learning activities |  Semester 1 |  Semester 2 | Ìý³§³Ü³¾³¾±ð°ù |
---|---|---|---|
Lectures | 20 | ||
Seminars | |||
Tutorials | 2 | ||
Project Supervision | |||
Demonstrations | |||
Practical classes and workshops | 40 | ||
Supervised time in studio / workshop | |||
Scheduled revision sessions | |||
Feedback meetings with staff | |||
Fieldwork | |||
External visits | |||
Work-based learning | |||
 Self-scheduled teaching and learning activities |  Semester 1 |  Semester 2 | Ìý³§³Ü³¾³¾±ð°ù |
---|---|---|---|
Directed viewing of video materials/screencasts | |||
Participation in discussion boards/other discussions | |||
Feedback meetings with staff | |||
Other | |||
Other (details) | |||
 Placement and study abroad |  Semester 1 |  Semester 2 | Ìý³§³Ü³¾³¾±ð°ù |
---|---|---|---|
Placement | |||
Study abroad | |||
 Independent study hours |  Semester 1 |  Semester 2 | Ìý³§³Ü³¾³¾±ð°ù |
---|---|---|---|
Independent study hours | 138 |
Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.
Semester 1 The hours in this column may include hours during the Christmas holiday period.
Semester 2 The hours in this column may include hours during the Easter holiday period.
Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.
Assessment
Requirements for a pass
Students need to achieve an overall module mark of 40% to pass this module.
Summative assessment
Type of assessment | Detail of assessment | % contribution towards module mark | Size of assessment | Submission date | Additional information |
---|---|---|---|---|---|
Set exercise | Numerical methods coursework | 50 | Around 10 pages | Semester 1, Teaching Week 7 | |
Set exercise | Statistical methods coursework | 50 | Around 10 pages | Semester 1, Assessment Week 3 |
Penalties for late submission of summative assessment
The Support Centres will apply the following penalties for work submitted late:
Assessments with numerical marks
- where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
- the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
- where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
- where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.
Assessments marked Pass/Fail
- where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
- where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.
The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.
Formative assessment
Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.
Short interactive exercises/quizzes in each lecture, plus informal feedback in each computer practical session.Â
Reassessment
Type of reassessment | Detail of reassessment | % contribution towards module mark | Size of reassessment | Submission date | Additional information |
---|---|---|---|---|---|
Set exercise | Alternative Numerical methods coursework | 50 | Around 10 pages | During the University resit period | |
Set exercise | Alternative Statistical methods coursework | 50 | Around 10 pages | During the University resit period |
Additional costs
Item | Additional information | Cost |
---|---|---|
Computers and devices with a particular specification | ||
Required textbooks | ||
Specialist equipment or materials | ||
Specialist clothing, footwear, or headgear | ||
Printing and binding | ||
Travel, accommodation, and subsistence |
THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.