Our team 

Ioana Colfescu 

Climate System Dynamics and Prediction

Atlantic Multidecadal Variability (AMV)

Extreme events statistics and attribution

Digital Technology for Atmospheric Science  Strategy

Matt Patterson

Interests: Climate dynamics, sub-seasonal to decadal prediction, climate modelling, jet streams, extreme events

Chen Lu

Interests: Extreme event attribution, climate modeling, climate change impact assessment

Visiting for 12 months from the Chinese Meteorological Administration

While here in St Andrews, Siyan will be working on machine learning for down-scaling of regional climate variability

PhD Candidate (2025-)

Supervisors: Simon Lee (SEES), Ioana Colfescu & Chen Lu

My project focuses on Compound Extremes, when multiple hazards occur together, often leading to enhanced impacts. The aim is to use advanced Machine Learning methods to better understand these compound extremes and their future impacts. This includes characterising them and identifying their physical drivers, but also exploring the relative contribution of internal climate variability and anthropogenic climate change to the occurrence of these events. 

PhD Candidate (2026-)

Supervisor: Eva Stüeken (SEES) and Ioana Colfescu

Lucie's project uses statistical and machine-learning methods to reconstruct deep-time climate and Earth system sensitivity, and spans mathematics and Earth science. 

PhD Candidate (2025-)

Supervisor: Simon Lee (SEES), Jean Reinaud (Maths), & Matt Patterson

My project explores cross-scale interactions in the climate system, focusing on the North Atlantic region. I am investigating how processes at small scales (like sub-daily weather events) influence and are influenced by larger-scale seasonal and inter-annual variability. By using advanced machine learning and climate model simulations, I aim to understand how these interactions shape atmospheric circulation patterns, affect predictability, and respond to long-term climate change. 

Summer 2025 Research Intern

Supervisor: Ioana Colfescu

Permanent Organisation: The Centre for Environmental Data Analysis