Pasadena, Calif., June 12, 2023 – A California Institute of Technology researcher is revolutionizing the way we predict rare weather patterns in the face of increasing extreme weather events.
Robert Webber, a postdoctoral scholar in the Department of Computing and Mathematical Sciences, has developed a groundbreaking genetics algorithm that combines the power of mathematics and genetics to forecast future weather phenomena accurately.
With climate uncertainty on the rise, Webber’s pioneering work aims to enhance disaster preparedness by identifying high-risk areas and providing more precise predictions.
Webber’s research, featured in SIAM News, initially focuses on the prediction of category five hurricanes hitting major cities.
However, his methodology can be applied to a wide range of weather events, including floods, heatwaves, wildfires, and extreme cold temperatures caused by the polar vortex.
The innovative genetic algorithm, inspired by the principles of natural selection, stands as the first of its kind to generate precise weather forecasts using smaller sample sizes and fewer computing resources.
As an avid outdoorsman, Webber was motivated by the conflicting narratives surrounding climate change and decided to employ his expertise in mathematical modeling to tackle the issue.
His ultimate goal is to empower communities to prepare for the future by offering accurate predictions regarding the likelihood of various weather phenomena.
With his current breakthrough, Webber anticipates that genetic algorithms will become the mainstream approach for forecasting extreme weather probabilities within the next decade.
"Our aim is to determine the extent to which we can provide precise estimates for different climate change scenarios," stated Webber. "Climate change is a daunting challenge, and the future remains uncertain. However, as scientists, we can offer concrete evidence that demonstrates the potential outcomes if we continue emitting carbon at current levels. We can forecast the occurrence of category five hurricanes and other rare weather events over the next 20 years."
Webber explained that his rare event sampling technique yields impressive results even with as few as 100 or 1,000 sample simulations. In comparison, other predictive models require over 10,000 samples, making them both costly and time-consuming.
“We now have the capability to perform complex calculations that were previously beyond our reach,” he explained. “This empowers us to tackle problems that other researchers would not dare to approach.”
While genetic algorithms are commonly employed in fields such as biochemistry and finance, Webber has adapted these techniques to analyze geophysical situations.
By integrating Darwin’s concept of “survival of the fittest,” his algorithm generates more accurate predictions. Each weather simulation is treated as an organism, and the fittest events are those that closely align with the rare weather phenomenon being studied.
For instance, when modeling the likelihood of a future heatwave, the algorithm replicates and runs weather simulations that indicate high heat over an extended period.
By selectively keeping the models that forecast extreme weather and randomly “killing” those that do not, Webber’s algorithm achieves statistically correct estimates while utilizing fewer computing resources.
This groundbreaking approach enables scientists to determine the probability of hurricanes making landfall and even predict their intensity, whether as a category four or category five storm.
Researchers can also apply Webber’s algorithm to model the probability and geographic distribution of severe wet winters in California over the next decade, providing valuable insights for preparing against potential catastrophic landslides.
Moreover, it can be utilized to explore various climate change scenarios and assess the impact of different temperature changes on future weather events.
While Webber’s model has shown early success, one rare weather occurrence remains elusive to climate change researchers – earthquakes.
Unlike other weather events that follow predictable patterns, earthquakes emerge from the complex interactions of tectonic plates, defying our current modeling capabilities.
“Despite countless observations and time passed between earthquakes, we have yet to make significant progress in improving our predictions, leaving them shrouded in mystery,” Webber acknowledged.
Webber’s pioneering use of mathematics and genetics in weather prediction not only provides a glimpse into the future of forecasting but also offers hope in tackling the challenges posed by climate change.
With his groundbreaking work, communities can better prepare for extreme weather events, allocate resources effectively, and ultimately enhance overall disaster preparedness.
About Society for Industrial and Applied Mathematics (www.siam.org) Society for Industrial and Applied Mathematics (SIAM), headquartered in Philadelphia, Pennsylvania, is an international society of more than 14,000 individual, academic and corporate members from 85 countries. SIAM helps build cooperation between mathematics and the worlds of science and technology to solve real-world problems through publications, conferences, and communities like chapters, sections and activity groups. Learn more at siam.org.
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