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This course is delivered by Professor David Brayshaw and Professor John Methven. It runs from January to February 2024. Applications for the 2024/25 academic year are not yet open. Email if you would like to be informed when applications open.

During our Climate Services and Climate Impact Modelling course, you will learn the science and practical techniques required for the provision of quantitative climate services and climate impact modelling. By the end, you will be aware of the strengths, limitations and sources of uncertainty in climate data and understand how it is produced (observations, reanalyses, forecasts and projections).

You will be able to handle quantitative weather and climate data, including complex geographical and forecast information, and perform simple processing and analysis tasks in Python.

The course will involve a mixture of online videos and lecture notes, interactive online discussion sessions, and online computing labs. You will have the opportunity to attend additional (optional) seminars given by expert speakers who will share their experiences of delivering weather and climate services to end-users.

Our Climate Services and Climate Impact Modelling course is developed from the Climate Services and Climate Impact Modelling module.

Timetabled sessions in 2024

Times and dates will be published before payment is taken for fees.

  • 10 January 2024, 1400–1500
  • 17 January 2024, 1400–1500
  • 24 January 2024, 1400–1700
  • 31 January 2024, 1400–1700
  • 7 February, 2024, 1400–1700

Optional guest seminars

Times and dates TBC.

These won't be recorded but usually the slides are shared afterwards.

A joining link for timetabled sessions and guest seminars will be given to enrolled learners.


This course is highly quantitative. It is based upon masters-level material. Most students normally undertaking the material would have a good first degree (2.2 or higher) in a quantitative subject such as mathematics, physics, economics or engineering.

You should be competent manipulating data mathematically, statistically and computationally.

The computer-lab sessions will use Python. We expect you will have some programming experience in data analysis.

Some familiarity with meteorology or atmospheric science (such as the online course Fundamentals of Meteorology) would be advantageous but is not essential.

We recommend students have at least:

  • equivalent to a B in A level Maths
  • equivalent to Further Mathematics A level or a pass equivalent to a 2.1 in a first year science undergraduate mathematics module
  • programming experience (for example in R, Python or matlab). Standard equivalent to a first year science undergraduate programming module.

Read the Terms and Conditions for Meteorology Online Courses.


Apply by 19 December 2023.

Further Learning

Find out about the Department of Meteorology, the scheduled online courses and open online courses.