2025 Internship Project Overview

Tropical cyclones (TCs) and hurricanes (HUs) that form in the North Atlantic are responsible for major socio-economic impacts every year. Hence, seasonal forecasts of these storms months in advance can help communities prepare and respond more effectively. There are several metrics for quantifying storm activity and potential destructiveness, including annual frequency, as well as the Power Dissipation Index (PDI) and Accumulated Cyclone Energy (ACE), which reflect duration and intensity. Numerous studies have highlighted the role of the tropical Atlantic and tropical mean sea surface temperature (SST) as predictors for statistical models that can describe the interannual variability in North Atlantic TC and HU activity. These statistical models exhibited significant forecasting skill by using forecasts of SSTs several months ahead. The primary objective was to develop a website that automatically gathers forecasted SSTs from various sources, uses forecast verification techniques to evaluate the models and predicts storm activity. This tool can help improve accessibility and accuracy of seasonal hurricane forecasting.

ORGANIZATION/RESEARCH GROUP

Villarini Research Group, Department of Civil and Environmental Engineering, Princeton University

LOCATION

Princeton, New Jersey

 

Interns

Joy Jiang ’28
Major: Operations Research and Financial Engineering
"In addition to building a forecasting tool, I gained experience working with large climate datasets, refining statistical approaches for tropical cyclone prediction, and translating scientific insights into an accessible platform. The experience was especially rewarding because it showed how computational tools can directly support disaster preparedness, and it has inspired me to further explore the intersection of quantitative modeling, climate risk, and resilience in my future academic and career pursuits."
Timothy Sim ’26
Major: Computer Science
"As I analyzed and predicted metrics for hurricanes and cyclones, I found myself immersed in learning and employing new forecast verification techniques. I thoroughly enjoyed analyzing and interpreting meaningful real-life data to create a helpful and powerful resource for future researchers, and am excited to pursue these newfound interests."

Click to view the end-of-project presentation

 

Gabriele Villarini
Professor of Civil and Environmental Engineering and the High Meadows Environmental Institute