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MTMNUM: Numerical Modelling for Weather and Climate Science

MTMNUM: Numerical Modelling for Weather and Climate Science

Module code: MTMNUM

Module provider: Meteorology; School of Mathematical, Physical and Computational Sciences

Credits: 20

Level: Postgraduate Masters

When you'll be taught: Semester 2

Module convenor: Professor Pier Luigi Vidale, email: p.l.vidale@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s): IN THE SAME YEAR AS TAKING THIS MODULE YOU MUST TAKE MTMFMD (Compulsory)

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: No

Last updated: 21 May 2024

Overview

Module aims and purpose

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. To bring you up to speed with experimental designs used in solving “Grand Challenge” problems with geoscientific modelling. 

Module learning outcomes

By the end of the module, it is expected that students will be able to: 

  1. Recognise the strengths and weaknesses of the main numerical methods used to model the atmosphere and oceans and explain their derivation. 
  2. Design numerical models to solve atmosphere/ocean problems, and 
  3. Perform numerical analysis, prior to model implementation 
  4. Implement idealised models by programming in Python, Julia, FORTRAN or C++, and
  5. Evaluate models using benchmark problems and known properties of the system 
  6. Understand complex model design and process-based assessment 

Module content

  1. History of numerical modelling: from first principles in the 1800s to today’s exascale challenges 
  2. Finite difference methods: Advection and diffusion, CFL in 1-D and 2-D 
  3. Advanced time schemes: from explicit to implicit and iterative schemes 
  4. Fluids on rotating Earth: traditional 2-D finite difference schemes 
  5. From Euler’s equations to the shallow water model 
  6. Chaos and predictability in weather and climate 
  7. Using complex nonlinear models: experimental designs and injection of uncertainty by design 
  8. Wave dispersion in finite difference models: from 1D to 2D, to Arakawa grid staggering 
  9. Alternative numerical methods for transport by the flow: finite volumes, finite elements, spectral elements 
  10. Alternative numerical methods for transport by the flow: the spectral method 
  11. Alternative numerical methods for transport by the flow: the Semi-Lagrangian method 
  12. Parameterization of unresolved processes: radiation and aerosols 
  13. Parameterization of unresolved processes: convective parametrisation and microphysics 
  14. Parameterization of unresolved processes: turbulence, orographic and gravity wave drag 
  15. Parameterization of unresolved processes: biophysics and carbon modelling on land and in the ocean 
  16. Coupling of multiple Earth System components: model hierarchies and experimental design for solving Earth System prediction problems 
  17. New methods to represent unresolved processes: stochastic physics, artificial intelligence, reduced precision numerical schemes 
  18. Supercomputing at the exascale: parallelism,  scalability, new programming paradigms, Large Data strategies 
  19. Supercomputing at the exascale: new dynamical cores, unstructured meshes. 

Structure

Teaching and learning methods

The module counts on 20 lectures which enable the students to tackle three practicals: 

  1. On advanced time integration, starting with simple oscillation and going into the design and implementation of a simple model of ENSO, which includes ensemble prediction 
  2. On simulation of an ocean gyre with a shallow water model, which teaches students about wave propagation in 2D and about coupled equations 
  3. (Formative Practical): On designing and running a simple prediction problem with an idealised (simplified) version of a state-of-the-art numerical model. 

Study hours

At least 50 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  Summer
Lectures 20
Seminars
Tutorials
Project Supervision 10
Demonstrations
Practical classes and workshops 30
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  Summer
Directed viewing of video materials/screencasts 5
Participation in discussion boards/other discussions
Feedback meetings with staff
Other
Other (details)


 Placement and study abroad  Semester 1  Semester 2  Summer
Placement
Study abroad

Please note that the hours listed above are for guidance purposes only.

 Independent study hours  Semester 1  Semester 2  Summer
Independent study hours 135

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 50% to pass this module.

Summative assessment

Type of assessment Detail of assessment % contribution towards module mark Size of assessment Submission date Additional information
Written coursework assignment Practical 1: computer project and scientific report 40 6 weeks
Written coursework assignment Practical 2: computer project and scientific report 40 6 weeks
In-class test administered by School/Dept Test 20 1 hour

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: https://www.reading.ac.uk/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.

Practical 

Reassessment

Type of reassessment Detail of reassessment % contribution towards module mark Size of reassessment Submission date Additional information
Written coursework assignment Practical: computer project and scientific report 80 During the University resit period
In-class test administered by School/Dept Test 20 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.

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