PhD opportunity: Climate change impacts on wildfire risk in seasonally dry forests

Monday, 28 November, 2022

Project Focus and Aims

This PhD project will focus on using observations of lightning to understand how fire weather and lightning have interacted to influence wildfire ignition in seasonally dry forests during recent decades. The student will then work with fire weather and lightning projections from climate models to quantify synchronous future increases in fire weather and lightning.

With the support of an international supervisory team of leading fire and climate scientists, the student will:

  • Identify lightning-ignited wildfires using observations of lightning and fire from satellites and ground-based sensors.
  • Study the regional impact of lightning strikes on spatial and temporal patterns of wildfire.
  • Examine the climatic thresholds that determine whether a lightning strike ignites a wildfire.
  • Predict future trends in fire-prone weather and lightning using climate model simulations, and use these predictions to study compound impacts on fire risk.

Beyond this project, the new insights generated will feed into the improved mechanistic modelling of lightning ignitions in climate models, enabling future changes in wildfire risk to be modelled more accurately under changing fire weather and lightning frequency.

Supervisors

Dr Matthew Jones (School of Environmental Sciences, University of East Anglia)

Professor Sander Veraverbeke (VU Amsterdam, Faculty of Science (Earth and Climate))

Professor John Abatzoglou (University of California Merced, School of Engineering)

Professor Manoj Joshi (School of Environmental Sciences, University of East Anglia)

 

Person Specification

  • A minimum 2:1 BSc or international equivalent in any quantitative or natural sciences discipline (e.g. Physics, Mathematics, Computer Science, Environmental Sciences, Meteorology, Chemistry).
  • We particularly welcome applicants with a track record of using code to undertake geospatial and statistical analyses.
  • Familiarity with Python or R would be preferable.
  • A passion for studying the environment and knowledge surrounding the issue of climate change is an advantage.

 

More information here: https://mattwjones.co.uk/climate-change-impacts-on-wildfire-risk-in-seasonally-dry-forests/

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