Unexpected Pairings Week 3: Climate
February 7, 2026
001 Chemical and Biomedical Engineering Building
11:00 a.m. to 12:30 p.m.
"Forecasting Without Data: Rethinking Weather Observations for Disaster Response"
Helen Greatrex, assistant professor of geography and statistics
We’re used to weather apps disagreeing, but in disaster response, choosing the wrong forecast can have real consequences. Normally, models are validated using weather station data, but in much of the world that data is limited or missing. This talk explores how Penn State researchers are finding creative ways to work around these gaps. From using newspaper archives to reconstruct flood histories in India, to combining humanitarian narratives with satellite rainfall estimates in Somalia, to co-designing drought insurance tools with farmers, the talk will look at how unconventional data sources can make forecasts more useful and trustworthy where they’re needed most.
Speaker Bio:
Helen Greatrex is an assistant professor of remote sensing and geospatial analysis, split between the departments of Geography and Statistics. She is also a co-hire of the Institute of Computational Data Science. Greatrex earned a doctoral degree in meteorology at the University of Reading in the UK, in 2012. She earned a post-graduate diploma in atmosphere and ocean science in 2007 at Reading and an master’s degree in physics with astrophysics at the University of Manchester in the UK, in 2006. Her research interests include geo-statistics and end-user driven weather statistics within the field of weather risk and international development. Specifically, her focus is on how we can better use products such as satellite rainfall to make better decisions, for example improving validation metrics, mechanistic crop/soil/health/insurance modelling and historical burn analysis. Current projects include assessing the impact of rainfall on the disease hydrocephalus, designing livelihood-based weather risk metrics in Somalia and assessing the impact of flash floods. Greatrex joined Penn State in 2019 after working in climate adaptation consultancy and as an associate research scientist at the International Research Institute for Climate and Society at Columbia University. She has also contributed the University of Reading's TAMSAT rainfall research group as a scientist since 2007. She works closely with the American Meteorological Society (AMS), recently chairing a Presidential Forum on the gulf between meteorologists and the humanitarian sector. Greatrex is a member of AMS, the Royal Meteorological Society and the Royal Anthropological Society.
"The role of mathematics in modeling and prediction in the era of AI"
John Harlim, professor of mathematics
The rapid rise of artificial intelligence (AI) has transformed many aspects of daily life, from performing routine tasks such as generating dinner menus to addressing complex scientific problems such as predicting weather. Despite their remarkable empirical success, AI-driven approaches continue to face fundamental challenges related to reliability, interpretability, and long-term predictive fidelity. In this talk, Harlim will illustrate these challenges with examples drawn from aerospace engineering and climate prediction and highlight how his research group contributes to addressing these issues. In particular, Harlim will focus on the basic problem of identifying mathematical representations that enable reliable long-term prediction from noisy observational data. He will demonstrate structure-aware mathematically grounded methods that can either significantly outperform or enhance the prediction skill of AI-based models.
Speaker Bio:
John Harlim is a professor of mathematics at Penn State. He earned a doctoral degree in applied mathematics and scientific computation at the University of Maryland in 2006. His research contribution covers a wide area in applied and computational mathematics, including topics that are relevant to modeling and prediction of real-world problems arising in engineering and earth and climate sciences. He was the recipient of the inaugural Frontier of Computational Physics award in 2012. He has mentored 20 postdoctoral researchers and students with support from the National Science Foundations and the Office of Naval Research.