The practice of generating synthetic storms got its start with simple statistical models that civil engineers have used since the 1980s to design skyscrapers to resist extreme winds. But hurricanes are a lot more complicated, and they may change significantly in a warming climate. They create not only high winds but also rainfall and storm surges. And much about how hurricanes behave is still unknown. Associate professor Ning Lin in CEE has been applying numerically generated but physically possible synthetic hurricanes to assess hurricane wind, surge, and rainfall hazards and risk in a changing climate. With graduate student Renzhi Jing, Lin recently developed a new hurricane model based on machine learning methods to more efficiently and accurately generate synthetic hurricanes under observed or projected future climate conditions. The new model and Lin’s synthetic modeling approach for estimating hurricane storm surge risk under climate change are featured on the Princeton University homepage.    

Link to the Full Story featured on the Princeton University homepage.