Predicting and Mitigating Megafires under Climate Change, CASE project with WTW (JONES_UEA_ARIES26)
Key Details
- Application deadline
- 7 January 2026 (midnight UK time)
- Location
- UEA
- Funding type
- Competition funded project (Students worldwide)
- Start date
- 1 October 2026
- Mode of study
- Full or part time
- Programme type
- PhD
)
Welcome to Norwich
According to the Sunday Times, this city is one of the best places to live in the UK.
Project description
Primary Supervisor - Dr Matthew Jones
Scientific Background
Megafires, characterised by their extraordinary size, speed, and intensity, are increasingly threatening society, ecosystems, and ecosystem services such as carbon storage (1-4). Recent advances in satellite observations and machine learning provide novel opportunities to study extreme fires on a global scale. In a changing climate, megafire-prone conditions could become more prevalent (3-4). However, the key mechanisms that promote or inhibit megafires are under-studied for most regions globally.
This project addresses critical knowledge gaps by combining novel observations of individual fires globally (5) and climate datasets with machine learning to predict megafire occurrence. The successful candidate will contribute to a ground-breaking efforts to forecast megafire risk and identify land management or policy factors with potential to mitigate that risk.
Research Questions
● Are megafires becoming more frequent globally, and in which regions?
● Which weather, landscape and land use factors promote or inhibit megafire development?
● Has climate change increased megafire risk, and how could those risks evolve in the future?
Methodology
Supported by the supervisory team, the researcher will:
● Develop a comprehensive global dataset of individual fires, compiling meteorological and landscape variables with potential to influence megafire development, building on the Global Fire Atlas (4).
● Identify megafires: Regionally distinguish between megafires and more ‘typical’ fires with less potential for catastrophic impact.
● Diagnose megafire-prone conditions: Harness machine learning techniques to identify key factors promoting/inhibiting megafire. Disentangle the roles of weather, landscape, and human factors influencing ignition and suppression.
● Analyse regional trends in megafire potential: Study regional trends in observed megafire occurrence (since ~2000s) and megafire-prone weather (since ~1980s), with opportunity to contribute to major reports on the topic (2,4).
Training and Development
Training will maximise future employability in academia and industry:
● Programming and geospatial data analysis using Python/R.
● Machine/deep learning techniques.
● Communication of scientific findings through publications and conferences.
Person Specification
A highly motivated candidate with:
● A degree or equivalent in numerate, computational, or environmental subject areas.
● Experience with programming languages such as Python or R for scientific data analysis is desirable.
Further Information:
Entry requirements
At least UK equivalence Bachelors (Honours) 2:1. English Language requirement (Faculty of Science equivalent: IELTS 6.5 overall, 6 in each category).
Any quantitative and analytical subject area is acceptable but a passion for the topic area is critical. Examples include: Mathematics, Statistics, Physics, Data Science, Physical Geography, Environmental/Biological Sciences, Economics, Finance, Engineering, etc.
Funding
ARIES studentships are subject to UKRI terms and conditions. Successful candidates who meet UKRI’s eligibility criteria will be awarded a fully-funded studentship, which covers fees, maintenance stipend (£20,780 p.a. for 2025/26) and a research training and support grant (RTSG). A limited number of studentships are available for international applicants, with the difference between 'home' and 'international' fees being waived by the registering university. Please note, however, that ARIES funding does not cover additional costs associated with relocation to, and living in, the UK, such as visa costs or the health surcharge.
ARIES is committed to equality, diversity, widening participation and inclusion in all areas of its operation. We encourage applications from all sections of the community regardless of gender, ethnicity, disability, age, sexual orientation and transgender status. Projects have been developed with consideration of a safe, inclusive and appropriate research and fieldwork environment. Academic qualifications are considered alongside non-academic experience, with equal weighting given to experience and potential.
Please visit www.aries-dtp.ac.uk for further information.
References
Jones, M. W., Abatzoglou, J. T., Veraverbeke, S., Andela, N., Lasslop, G., Forkel, M., Smith, A. J. P., Burton, C., Betts, R. A., van der Werf, G. R., Sitch, S., Canadell, J. G., Santín, C., Kolden, C., Doerr, S. H., and Le Quéré, C.: Global and Regional Trends and Drivers of Fire Under Climate Change, Reviews of Geophysics, 60, e2020RG000726, https://doi.org/10.1029/2020RG000726, 2022.
Jones, M. W., Veraverbeke, S., Andela, N., Doerr, S. H., Kolden, C., Mataveli, G., Pettinari, M. L., Le Quéré, C., Rosan, T. M., van der Werf, G. R., van Wees, D., & Abatzoglou, J. T.: Global rise in forest fire emissions linked to climate change in the extratropics. Science, 386(6719), eadl5889. https://doi.org/10.1126/science.adl5889, 2024.
Jones, M. W., Kelley, D. I., Burton, C., Di Giuseppe, F., Barbosa, M. L. F., Brambleby, E., Hartley, A. J., Lombardi, A., Mataveli, G., McNorton, J. R., Spuler, F. R., Wessel, J. B., Abatzoglou, J. T., Anderson, L. O., Andela, N., Archibald, S., Armenteras, D., Burke, E., Carmenta, R., Chuvieco, E., Clarke, H., Doerr, S. H., Fernandes, P. M., Giglio, L., Hamilton, D. S., Hantson, S., Harris, S., Jain, P., Kolden, C. A., Kurvits, T., Lampe, S., Meier, S., New, S., Parrington, M., Ribeiro, N., Saharjo, B., San-Miguel-Ayanz, J., Shuman, J. K., Tanpipat, V., Van Der Werf, G. R., Veraverbeke, S., and Xanthopoulos, G.: State of Wildfires 2023-24, Earth System Science Data, https://doi.org/10.5194/essd-16-3601-2024, 2024.
United Nations Environment Programme [Co-authored by Burton and Kelley]: Spreading like Wildfire – The Rising Threat of Extraordinary Landscape Fires. A UNEP Rapid Response Assessment, available at: https://www.unep.org/resources/report/spreading-wildfire-rising-threat-extraordinary-landscape-fires, last access: 9 July 2024, Nairobi, Kenya, 2022.
Andela, N., Morton, D. C., Giglio, L., Paugam, R., Chen, Y., and Hantson, S.: The Global Fire Atlas of individual fire size, duration, speed and direction, Earth System Science Data, 11, 529–552, https://doi.org/10.5194/essd-11-529-2019, 2019. [Update at: Andela, N. and Jones, M. W.: Update of: The Global Fire Atlas of individual fire size, duration, speed and direction, https://doi.org/10.5281/zenodo.11400062, 2024.]