PhD Studentship: Predicting and Mitigating Megafires under Climate Change

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). 

Entry Requirements

The minimum entry requirement is 2:1 in a Bachelor’s degree.

A minimum degree or equivalent in numerate, computational, or environmental subject areas.

Start date: 1 October 2024

Funding Details

Additional Funding Information

ARIES is awaiting confirmation of funding under the BBSRC-NERC DLA award scheme, which is expected shortly. Funding for this studentship is subject to this confirmation and UKRI terms and conditions. Successful candidates who meet UKRI’s eligibility criteria will be awarded a fully-funded ARIES studentship of fees, maintenance stipend (£19,237 p.a. for 2024/25) and research costs. 

A limited number of ARIES studentships are available to International applicants. Please note however that ARIES funding does not cover additional costs associated with relocation to, and living in, the UK. 

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. 

For further information, please visit www.aries-dtp.ac.uk

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