PhD Studentship: Redeveloping Central England Temperature: Modernising a Historic Climate Series, CASE project with Met Office

Primary supervisor - Prof Tim Osborn

Research challenge 

Central England Temperature (CET) is the world’s longest instrumental temperature record (monthly from 1659, daily since 1772). Preserving its consistency and homogeneity across centuries – despite changes in instrumentation, weather station locations, land use and urbanisation patterns – remains a significant scientific challenge. Originally compiled by Manley (1953) and later refined and improved (e.g. Parker et al. 1992; Legg et al. 2024), the CET now requires a modern, transparent redevelopment that meets these growing challenges. 

Approach 

This PhD will develop a new CET dataset using robust, reproducible methods that account for all the complexities of station changes, urbanisation effects and measurement biases. You will quantify uncertainties across time, evaluating biases and errors from instrumentation, measurement techniques and station selection. 

A key innovation will be the use of Machine Learning (ML) techniques to detect and correct inhomogeneities, model relationships between overlapping station records, and estimate missing data. Techniques such as neural networks, Bayesian inference and ensemble learning will be explored, with a focus on “explainable methods” to ensure the resulting dataset is physically justified and scientifically transparent. 

The new CET record will be compared with other multi-century instrumental records of temperature and atmospheric circulation to assess whether these related records are physically consistent with each other. You will subsequently apply the new CET record for evaluating climate models, assessing current temperature extremes in a long-term historical context, and for comparing present-day climate change to that experienced over the past four centuries. 

Training 

You will work alongside supervisors at the University of East Anglia (UEA), the Met Office and the University of Reading. Placements at the Met Office will embed you within the National Climate Information Centre and the Climate Monitoring group. Training will include advanced data science (including software engineering with Python), climate analysis and science communication – preparing you for careers in academia, government or industry. 

Applicant Profile 

The project would suit a numerate student with a science degree and strong interest in climate science. Experience with data analysis or coding (e.g. Python/R) would be beneficial. 

Entry requirements

A minimum 2:1 degree or equivalent in numerate, computational, or environmental subject areas, including examples below. 

Numerate Subject Areas: 

Mathematics, Statistics, Physics, Geophysics 

Computational Subject Areas: 

Data Science, Machine Learning, Computer Science 

Environmental Subject Areas: 

Environmental Science, Climate Science, Physical Geography, Geographic Information Systems (GIS), Earth Systems Science, Environmental Engineering, Oceanography, Meteorology, Atmospheric Science, Hydrology, Geophysics 

Mode of study

Full-time

Start date

1 October 2026

Funding

This PhD project is in a competition for a Faculty of Science funded studentship. Funding is available to UK applicants and comprises ‘home’ tuition fees and an annual stipend for 3 years.

Closing Date 

10/12/2025

To apply for this role, please click on the 'Apply' button above.

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