Researchers at the FAMU-FSU College of Engineering have created a new hybrid statistical technique for predicting extreme heat and heavy rainfall in South Florida.
According to the research, published in the American Geophysical Union’s Earth’s Future journal, the technique promises more accurate climate predictions for local communities and infrastructure planning.
“Many of the techniques used in climate downscaling and bias correction research are limited in prediction of extreme weather events,” said Ebrahim Ahmadisharaf, lead researcher at the joint college’s Resilient Infrastructure & Disaster Response (RIDER) Center. “They use methods that give us the big picture but have limitations.” 
Advancing weather prediction models
The study reveals that while current bias correction techniques effectively predict light and moderate rainfall and average temperatures, they fall short when forecasting extreme weather events. To address this gap, researchers developed a technique called EQM-LIN (empirical quantile mapping with linear correction).
Using data from 20 weather stations across South Florida, the new method combines two statistical approaches to provide more precise climate projections than existing global climate models.
“We found the hybrid technique is especially good at predicting extreme climate variables, namely precipitation and air temperature,” Ahmadisharaf said. “Our projection shows that in the future, South Florida will likely experience slight decreases in precipitation in the summer and an increase in the fall.”
Practical applications
The research has immediate practical value for infrastructure planning and community protection. The technique helps stakeholders identify areas vulnerable to potential flooding and assess at-risk infrastructure.
“The results can bolster the resilience of our infrastructure and local communities against climate-related hazards,” Ahmadisharaf said.
Future directions
The multi-station analysis approach offers a promising framework for understanding and preparing for future climatic challenges, but researchers acknowledged that ongoing refinement of the statistical bias correction technique is necessary. Future studies may incorporate regional climate models for even more precise local projections.
“Further improving the bias correction of extreme events and investigating the structure of compound climatic events under future climate remains a priority,” said lead author and postdoctoral researcher Leila Rahimi.
The project, partially funded by an Everglades Foundation fellowship, will expand beyond South Florida with support from the Pensacola and Perdido Bays Estuary Program (PPBEP) and the National Academies of Sciences, Engineering and Medicine (NASEM).
Collaborative research effort
The study brought together experts from multiple institutions, including FAMU-FSU Engineering’s Civil and Environmental Engineering Department; Florida State University’s Department of Earth, Ocean, and Atmospheric Science; the University of California, Irvine; Oak Ridge National Laboratory; Jackson State University; and the South Florida Water Management District.
In related news, India’s Ministry of Earth Sciences (MoES) has recently begun exploring the integration of AI technologies into weather and climate forecasting systems and physics-based numerical models. Click here to read the full story.
