Quantifying uncertainty and outlining plausible futures for compound heat-health risks
Background
Climate change is driving more frequent and severe heat extremes worldwide, creating urgent challenges for public health. In the UK, record-breaking hot summers have already caused thousands of excess deaths. Health risks are not explained by temperature alone but by complex compounding factors, such as multi-day heatwaves, persistent night-time heat, indoor/outdoor temperature, and other meteorological factors like humidity. These combinations reduce the body’s ability to recover, disrupt sleep, and compromise thermoregulation. Climate projections for the UK suggest these compound events will become more common, with rising humidity adding further strain. Understanding how these climate risks interact with health, who is most affected, and how future risks may evolve is critical. This research area brings together climate science, public health, and statistical modelling to quantify uncertainties and outline plausible futures, guiding effective public health/policy responses.
PhD opportunity
This PhD project investigates compounding heat extremes and how risks may evolve under climate change. While isolated heat episodes are well studied, less is known about the health burden of complex, multi-dimensional events that are projected to intensify in a warming climate.
The student will use the UK Biobank cohort (half a million participants with rich health and lifestyle data) with high-resolution meteorological datasets from UKCP18 and other sources. Heat-health relationships will be derived from historical weather data and then applied with climate models to project future health outcomes. Using scenario-based modelling, they will assess how uncertainties in climate projections and demographic change shape future health risks. Analyses will go beyond mortality to include morbidity, such as cardiovascular and respiratory conditions, for a fuller picture of disease burden.
A central challenge is quantifying uncertainty. Climate models differ in how they simulate extremes; demographic and socioeconomic futures are uncertain; mitigation depends on behaviour and policy. Rather than producing a single forecast, the project will quantify uncertainty and outline plausible risk futures, fully aligning with UNRISK’s mission to deliver decision-relevant knowledge.
The project also offers opportunities to connect with the UK Health Security Agency (UKHSA), whose remit includes developing national health risk assessments and resilience planning. Findings could directly inform UKHSA’s climate-health risk assessments and strengthen evidence for public health interventions.
The supervisory team combines expertise in epidemiology and environmental health modelling (Dr Yuchen Li), climate extremes and modelling (Professor Cathryn Birch), and statistical and cohort-based methods, with UKB data expertise (Dr Zihao An). Together, the team ensures interdisciplinary guidance spanning climate science, epidemiology, statistics, and spatial analysis.
Applicant Profile
This project is suited to students with a background in climate science, statistics, geography, epidemiology, maths, physics, or engineering who are keen to apply quantitative methods to pressing climate – health questions. Experience in statistical modelling, machine learning, or spatial analysis would be valuable, though training will be provided. An interest in working across disciplines – linking climate projections, health data, and policy applications – will be essential.
Other information
Supervisor profile:
https://environment.leeds.ac.uk/staff/12888/dr-yuchen-li
https://environment.leeds.ac.uk/see/staff/1162/dr-cathryn-birch
https://environment.leeds.ac.uk/transport/staff/10106/dr-zihao-an
Key readings:
Wu, X., Wang, J., Ge, Y., Lai, S., Zhang, D., Ren, Z., & Wang, J. (2025). Future heat-related mortality in Europe driven by compound day-night heatwaves and demographic shifts. Nature Communications, 16(1), 7420.
Cole, R., Wan, K., Murage, P., Macintyre, H. L., Hajat, S., & Heaviside, C. (2025). Projections of heat related mortality under combined climate and socioeconomic adaptation scenarios for England and Wales. PLoS Climate, 4(7), e0000553.
Jackson, L. S., Birch, C. E., Chagnaud, G., Marsham, J. H., & Taylor, C. M. (2025). Daily rainfall variability controls humid heatwaves in the global tropics and subtropics. Nature Communications, 16(1), 3461.
