Lai Builds Location-Specific Climate Forecasting Tools for Engineers

Yuchuan Lai recently completed his PhD studies and published his second paper, co-written with his advisor Professor Dave Dzombak,  Use of the Autoregressive Integrated Moving Average (ARIMA) Model to Forecast Near-Term Regional Temperature and Precipitation, was in the AMS Journal of Weather and Forecasting.

Lai began working on the project in 2017, expanding previous research on historical climate change in different cities. Lai then created 20-year, city-specific climate projections for engineers. The ARIMA-based statistical forecasting model may be utilized to create location-specific temperature and precipitation forecasts for use in civil and environmental engineering applications.

His focus on climate change started during graduate school—as a civil engineering undergrad, Lai focused on more traditional engineering problems but his master’s degree coursework at Carnegie Mellon shifted his direction.

“Classes including Climate Change Adaptation for Infrastructure with Costa Samaras and Climate Change Science and Solutions with Parth Vashinav allowed me to think outside the views of a traditional engineering student. These courses enabled me to learn more about climate science and to frame the problems by combining civil and environmental engineering and climate science.”