Extreme meteoclimatic events such as prolonged droughts, intense heat waves, and catastrophic floods have far-reaching impacts on global food production systems. These events can damage crops, reduce yields, and destabilize supply chains, especially when they occur simultaneously across major agricultural regions, known as global 'breadbaskets.' The consequences of such co-occurring extremes extend beyond local economies, posing significant risks to global food security, increasing market volatility, and potentially triggering geopolitical tensions due to resource scarcity and trade disruptions.

This PhD project at the University of Reading's Department of Mathematics and Statistics aims to investigate the underlying stressors affecting crop production by analyzing the statistical properties of persistent and hazardous fluctuations in weather conditions under different climate scenarios. The research will leverage advanced statistical and probabilistic methodologies, including spatio-temporal extreme value theory, large deviation theory, and rare event simulation methods. These approaches enable the quantification of the likelihood and severity of rare climatic extremes using both observational datasets and outputs from the latest generation of Earth System Models (CMIP6).

The project will involve extensive data analysis, applying novel protocols and objectives that position the research at the forefront of climate risk assessment. The successful applicant will receive comprehensive training in statistical extreme value and time series modeling, advanced data analysis techniques for large climate datasets, and Monte Carlo methods, including rare event simulation approaches. This training will equip you with expertise in cutting-edge computational and statistical techniques, as well as a deep understanding of climatic extremes and their implications for global food systems.

Funding is provided through a full UKRI stipend and home-level PhD tuition fees, supported by the EPSRC Centre for Doctoral Training in the Mathematics for our Future Climate. Applicants should have a strong background in mathematics, statistics, physics, meteorology, environmental science, or a closely related discipline, with experience in statistical modeling and data analysis highly desirable. Proficiency in programming and quantitative skills are advantageous, and international applicants may need to meet English language requirements.

Applications are accepted year-round. To apply, visit the University of Reading's online application portal and indicate your interest in the EPSRC Centre for Doctoral Training in the Mathematics for our Future Climate. For further details, contact the Department of Mathematics and Statistics. This project offers a unique opportunity to contribute to climate risk research and develop skills relevant for both academic and policy careers.