Modeling climate variability to understand predictability

Hi! I am an Earth System Scientist at the Atmospheric, Oceanic and Planetary Physics (AOPP), University of Oxford. My research focuses on understanding climate variability and predictability across timescales, from sub-seasonal to seasonal and decadal, with a particular interest in interactions between tropical ocean basins and their influence on climate around the globe. I use climate modelling and observations to investigate the role of air–sea interactions in shaping climate variability and predictability. A central theme of my research is understanding how interactions between the tropical Indian, Pacific and Atlantic Oceans influence atmospheric circulation and climate extremes, particularly in the extratropics.

My research has shown that an inter-basin perspective provides a useful framework for understanding the changing pathways and impacts of El Nino-Southern Oscillation (ENSO) teleconnections within a season. For example, ENSO influences European climate through different pathways during winter: its influence in early winter is mediated strongly through the Indian Ocean, while more direct ENSO pathways become more important later in winter. I have also demonstrated that the co-occurrence of the Indian Ocean Dipole (IOD) and ENSO plays an important role in shaping the early-winter North Atlantic Oscillation (NAO). More broadly, my research seeks to understand how interactions between different ocean basins can shape regional climate variability and contribute to extreme climate events. By identifying these inter-basin pathways, I aim to improve our understanding of climate predictability and our ability to attribute and anticipate climate risks across different regions and timescales.

I have a research interest in seamless climate prediction and its application to climate risk. As part of the EU Horizon ASPECT project, I am developing seamless climate information across different timescales, with the aim of bridging the gap between climate prediction and impacts-relevant information for decision-making.