Multi-university collaboration will use data science to find the next El Nino

The El Nino and La Nina patterns in the Pacific Ocean are notorious for their long-distance effects on weather as far away as Africa and the Midwestern United States. But climate experts also know of several other such patterns, known as teleconnections, and believe that there are many more to be discovered.

The new TRIPODS+Climate project, a collaboration among the University of Wisconsin–Madison, the University of Chicago, and the University of California, Irvine, will develop novel data science tools to sniff out these hidden patterns, improving weather forecasts and scientific understanding of global climate.

The TRIPODS+Climate project will receive $300,000 over three years, part of $8.5 million in grants the National Science Foundation announced today, Sept. 11, to 19 interdisciplinary TRIPODS+X proposals at 23 institutions.

The collaboration is an expansion of the NSF’s TRIPODS program, which funded several research centers in 2017 to explore the fundamentals of data science — the modern intersection of mathematics, statistics, and computer science. Stephen Wright, Professor of Computer Sciences at UW–Madison and the Wisconsin Institute for Discovery, and Rebecca Willett, Professor of Statistics and Computer Science at the University of Chicago, lead one of the TRIPODS Institutes. With TRIPODS+Climate, they will work with a team of climate scientists to apply data science methods such as machine learning, network analysis, and predictive modeling to the growing flood of climate data.

Read all about it in the University Communications story by Noel Lendved.

Photo: Hurricane Harvey, 2017, NASA/NOAA