This course is delivered by Professor David Brayshaw and Professor John Methven. It runs during April and May 2025.
During our Climate Services and 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 Impact Modelling course is developed from the Climate Services and Climate Impact Modelling module.
Online Timetabled sessions in 2025 (UK time)
- 23 April 14:00-15:00 Online lecture
- 30 April 14:00-15:00 Online lecture
- 7 May 14:00-15:00 Online lecture
- 7 May 15:00-17:00 Online computing lab
- 14 May 14:00-15:00 Online lecture
- 14 May 15:00-17:00 Online computing lab
- 21 May 14:00-15:00 Online lecture
- 21 May 15:00-17:00 Online computing lab
Optional guest seminars
Times and dates between 21 April and 23 May 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.
Prerequisites
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 online 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
- Recent use of mathematics including:
- Linear equations and functions
- Basic statistics (e.g., mean, variance, regression and line fitting, correlation, probability distributions)
- Familiarity with common mathematical notation
- Basic calculus
- Representing data in line and scatter plots and tables.
- 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.
Application
Apply by 7 April 2025.
Further Learning
Find out about the Department of Meteorology, the scheduled online courses and open online courses.