PhD Studentship : New Statistical and Machine-learning Methods for Forecasting High-impact Weather Events in Urban Areas, NERC GW4+ DTP PhD Studentship for September 2025 Entry

About the Partnership

This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP).  The GW4+ DTP consists of the Great Western Four alliance of the University of Bath, University of Bristol, Cardiff University and the University of Exeter plus five Research Organisation partners: British Antarctic Survey, British Geological Survey, Centre for Ecology and Hydrology, the Natural History Museum and Plymouth Marine Laboratory. The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/

Project details

For information relating to the research project please contact the lead Supervisor via s.siegert@exeter.ac.uk

Project Aims and Methods

Numerical Weather Prediction (NWP) models have much improved at representing small-scale atmospheric features through the increased usage of convective-scale models. However, errors in the resulting forecasts remain with the NWP models unable to adequately represent complex orographies, land-sea processes and urban features. Post-processing techniques can help alleviate these issues by correcting spatial and temporal errors in the forecast, and hence producing more useful forecasts. 

This project will develop and explore statistical and machine learning approaches to post-process Met Office (MO) weather forecasts, using official as well as crowdsourced observation data. The spatial and temporal evolution of forecast errors at local scales will be investigated to inform the development of novel post-processing techniques for using local information, particularly for high impact temperature, wind speed and precipitation events. Correlations between local scale forecast errors and uncertainty in the synoptic scale weather patterns will be explored for further improvements. Forecast performance will be assessed with focus on high impact events in urban areas. 

This project builds on existing relationships between the MO and the University of Exeter. There are opportunities to collaborate with MO scientists and contribute to production of weather forecasts. 

Project partners

The Met Office will make available forecast data from state-of-the-art NWP models and high-resolution observation data. Support in obtaining, managing and interpreting data. Scientific supervision and advisory in regular (c bi-weekly) meetings. Contributing in kind towards necessary materials whilst the student is based at the Met Office. 

Training

The DTP offers funding to undertake specialist training relating to the student’s specialist area of research. 

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