A 50% chance of showers: Can we improve the communication of probabilistic weather forecasts?

Recent improvements in weather forecasting technology have allowed the Met Office to produce new short-range forecasts of the likelihood of summer showers. In this project, students from the departments of Meteorology, Psychology and Information Design will seek to investigate and improve the way these forecasts are presented so that their benefit to the general public is maximised.

Department: Meteorology

Supervised by: Andrew Charlton-Perez

The Placement Project

An increasingly important part of weather forecasting is the ability to predict the uncertainty of any given forecast in addition to the forecast itself. Techniques which were originally applied to forecasts on the medium-range (5-10 days ahead) have now been applied and adapted to forecasts on a wide variety of lead times. Recently, the Met Office designed and implemented a new short-range (0-24 hours ahead) ensemble prediction system to be able to predict the uncertainty in the rainfall at very small horizontal scales. A big part of fully exploiting the potential of this forecasting system is understanding how best to communicate the forecasts it makes to the general public. Previous research on public perception of probabilistic forecasts of precipitation has shown that both prior experience of this type of forecast and the method of communication can strongly affect the accuracy with which end-users consume the forecast information. In this project, three linked UROP students will begin to consider how best to communicate this new type of weather forecast to the public. The UROP student in Meteorology will analyse the forecasts produced by the Met Office forecasting system, understanding their performance and limitations and then producing some case studies which the rest of the project team will use to test methods of forecast communication. The student will work closely with colleagues at the Met Office to understand the new forecast system and will also be required to interact strongly with PIs of linked UROP projects and other UROP students. The project will form part of the recently funded NERC PURE project of which the University of Reading is a major contributor.


1. Visit to the UK Met Office to discuss the forecasting system which will be studied. [1.5 days] 2. Downloading and preparing data from Met Office short-range ensemble forecasts. [20% of placement] 3. Analysis of data to identify typical examples of forecast output and performance.[30% of placement] 4. Preparation of data from case studies identified in 3 for use by UROP student in Information Design.[10% of placement] 5. Discussion of results of design work to assess suitability and accuracy.[10% of placement] 6. Assisting in the collection of survey data in the Wimbledon queue or similar public forum.[4 days] 7. Production of one section of research paper (figures and text). [15% of placement]

Skills, knowledge and experience required

The student will need the following key core skills: • Specialist knowledge of forecasting/predictability, numerical modelling and convective processes. • Basic knowledge of mathematics and statistics. • Ability to communicate effectively with other scientists and those from different disciplines. • Outgoing and friendly character to be able to assist with survey data collection. • Willingness to develop new skills, typical outside of degree specialism.

Skills which will be developed during the placement

The student will develop the following skills during the placement: • Independent research skills • Specialist knowledge of short-term ensemble prediction • Team-working skills • Inter-disciplinary research communication skills • Research presentation and communication skills

Place of Work

The student will have a desk in the Philip Lyle building since this is where the PI will be working once the project commences.

Hours of Work

Start date and hours of work to be agreed

Approximate Start and End Dates (not fixed)

Friday 12 July 2013 - Friday 23 August 2013

How to Apply

Application by CV and covering letter to Andrew Charlton-Perez (

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