The world of weather and climate science is undergoing a significant transformation, driven by the rapid advancement of artificial intelligence and set against a challenging federal funding environment. In this story, we’ll talk about the changing landscape and how weather and climate data are aggregated, shared, and used.
Dr. Gan Zhang is not only an expert on weather extremes and their impacts, but also knows them firsthand. His childhood near the Huai River in East China, a region marked by distinct monsoon seasons and prone to flooding, inspired his career in weather and climate science.
He began his studies at the Ocean University of China, and completed his master’s and PhD in Atmospheric Sciences at the University of Illinois. After graduating in 2018, he moved to the East Coast and worked as a postdoctoral researcher at Princeton University. He was affiliated with and stationed at a federal lab that pioneered weather-climate modeling. In 2020, he joined the hedge fund, Citadel, as a weather analyst serving commodity trading and eventually returned to the U. of I. as a professor and leader of a research group.
Zhang’s work mainly focuses on physical and data-driven modeling, which can serve stakeholders in the public and private sectors. For instance, probabilistic predictions and risk assessment of high-impact extremes are increasingly used to inform risk management and investment decisions. At the razor’s edge of this science is the ever-improving quality of model technology, and now the combination of artificial intelligence with traditional physical models.