Predicting and Mitigating Megafires under Climate Change

JONES_UENV25ARIES CASE project with BeZero Carbon Ltd

Predicting and Mitigating Megafires under Climate Change

JONES_UENV25ARIES CASE project with BeZero Carbon Ltd

Project Description

Supervisors

Dr Matthew Jones, Environmental Sciences, University of East Anglia – contact me

Professor Timothy Osborn, UEA ENV

Professor Stephen Sitch, University of Exeter Geography

Dr Chantelle Burton, Met Office Hadley Centre

 

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:

http://mattwjones.co.uk/research-team-and-open-positions

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., 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.
  • Cunningham, C. X., Williamson, G. J., and Bowman, D. M. J. S.: Increasing frequency and intensity of the most extreme wildfires on Earth, Nat Ecol Evol, 1–6, https://doi.org/10.1038/s41559-024-02452-2, 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.]

Key Information

  • This studentship has been shortlisted for funding under the UKRI NERC DLA funding scheme and will commence on 1 October 2025. The closing date for applications is 23:59 on 8th January 2025.
  • Successful candidates who meet UKRI’s eligibility criteria will be awarded a fully-funded studentship, which covers fees, maintenance stipend (£19,237 p.a. for 2024/25) and research funding. 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 postgradute researcher (PGRs) benefit from bespoke graduate training and ARIES provides £2,500 to every student for access to external training, travel and conferences, on top of all Research Costs associated with the project. Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for an additional 3-month stipend to take advanced-level courses.
  • ARIES is committed to equality, diversity, widening participation and inclusion in all areas of its operation. We encourage enquiries and applications from all sections of the community regardless of gender, ethnicity, disability, age, sexual orientation and transgender status. Academic qualifications are considered alongside non-academic experience, and our recruitment process considers potential with the same weighting as past experience.
  • All ARIES studentships may be undertaken on a part-time or full-time basis. International applicants should check whether there are any conditions of visa or imigration permission that preclude part-time study. All advertised project proposals have been developed with consideration of a safe, inclusive, and appropriate research and fieldwork environment with respect to protected characteristics. If you have any concerns please contact us.
  • For further information, please contact the supervisor. To apply for this Studentship follow the instructions at the bottom of the page or click the 'apply now' link.
  • ARIES is required by our funders to collect Equality and Diversity Information from all of our applicants. The information you provide will be used solely for monitoring and statistical purposes; it will remain confidential, and will be stored on the UEA sharepoint server. Data will not be shared with those involved in making decisions on the award of Studentships, and will have no influence on the success of your application. It will only be shared outside of this group in an anonymised and aggregated form. You will be ask to complete the form by the University to which you apply.
  • If funded under the BBSRC-NERC DLA scheme, ARIES studentships will be subject to UKRI terms and conditions. Postgraduate Researchers are expected to live within reasonable distance of their host organisation for the duration of their studentship. See https://www.ukri.org/publications/terms-and-conditions-for-training-funding/ for more information

Apply Now

Apply via the  University of East Anglia application portal