About the Project
Background
Forests absorb ~30% of the carbon dioxide (CO2) humans emit each year, making them one of the most important natural brakes on climate change. But this depends on forests continuing to take up carbon as effectively as they have in the past, and climate change itself is threatening that: heatwaves and droughts are becoming more frequent, and can reduce how much carbon a forest absorbs. If this weakens the forest carbon sink, more CO2 stays in the atmosphere, driving further warming and extremes –…
a feedback loop that could make climate change worse than current projections assume. Satellites now allows us to monitor forests continuously across the globe, offering an unprecedented view of how they are actually responding to a changing climate. Combining these observations with statistical methods and the computer models used to project future climate is essential to understanding how much we can rely on forests to keep absorbing carbon, and where our current models may be falling short.
PhD project
This project investigates why forests do not always respond in the same way to a heatwave or drought, and what that means for how reliably they will keep absorbing carbon dioxide in the future. Using decades of satellite records of forest photosynthesis and carbon stocks, the student will characterise how quickly forests are affected by a climate extreme and how long they take to recover, testing whether forests still recovering from one event become more vulnerable to the next. A key question is whether an early-warning signal in forest photosynthesis can predict a longer-term loss of forest carbon. These patterns will then be compared against the JULES land surface model, one of the models used to compile the international Global Carbon Budget, and isolate how well the model captures changing forest vulnerability. Where the model’s behaviour differs from the satellite record, this points to specific, actionable improvements in how climate risk to the land carbon sink is represented and projected. Dr Thais Rosan will supervise the identification and preparation of satellite data on forest productivity, carbon stocks and climate hazards. Prof Theo Economou will supervise the statistical modelling of forest vulnerability and recovery, bringing expertise in modelling environmental risk and extreme events. Dr Michael O’Sullivan will supervise the JULES model-evaluation component and its relevance to global carbon budget uncertainty. The student will develop skills in satellite data analysis, statistical risk modelling and climate model evaluation, shaped around their own background and interests.
Applicant Profile
Students with a strong background in mathematics or statistics, climate science, or remote sensing are encouraged to apply.
Funding Notes
This project is part of the UNRISK CDT, which offers 15-18 fully-funded NERC studentships, covering full university tuition fees; a personal stipend at standard UKRI rates; £6000 individual research and training costs; £5000 (per student) of cohort-level training; and a ‘Flexible Fund’ for special projects.
International applicants will need to cover costs related to applying for a student visa and the international health surcharge (IHS)
Applications are open to UK and international applicants. The number of awards for international applicants is limited by UKRI rules.
More information is available on the UNRISK website: View Website
References
Dr Mike O’Sullivan (Exeter Maths & Stats): http://emps.exeter.ac.uk/mathematics/staff/mo339
Global Carbon Budget 2025 (Friedlingstein, O’Sullivan et al., Earth System Science Data): https://essd.copernicus.org/articles/18/3211/2026/
Global Carbon Budget website (Global Carbon Project): https://www.globalcarbonproject.org/carbonbudget/
Effects of climate extremes on the terrestrial carbon cycle (Frank et al., Global Change Biology, 2015): https://doi.org/10.1111/gcb.12916
