The Department of Meteorology at the University of Reading is offering premium online courses with support from internationally-renowned academic staff.
This training is suitable for professional meteorologists, consultants, STEM students, graduates and academics seeking to improve their range of skills and knowledge. The courses may be suitable CPD for chartered meteorologists.
This course is delivered by Professor David Brayshaw. It runs during April and May 2026.
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.
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.
What to expect
- Each week, new lecture notes with videos.
- Weekly live online interactive sessions.
- Exercises and assessments.
- The opportunity to ask for help at live online sessions and on class discussion boards.
- To study between four and eight hours per week.
- Feedback on your work.
- A certificate when you successfully complete the course.
