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UMD Joins Consortium to Improve Accuracy of Weather Forecasts

Atmospheric and Oceanic Science Researchers to Lend Expertise to $6.6M Initiative

By Emily C. Nunez

satellite image of Hurricane Otis

Hurricane Otis approaches Mexico's Pacific coast in October 2023. The storm, which intensified unexpectedly, illustrates the need for more accurate weather modeling, researchers say.

Photo by NOAA via AP

The University of Maryland joined a $6.6 million consortium to improve weather predictions and train the next generation of atmospheric scientists as climate change progresses and wild weather surges around the world.

The National Oceanic and Atmospheric Administration’s (NOAA) new Consortium for Advanced Data Assimilation Research and Education (CADRE) will focus on improving data assimilation—the science of using observations to improve model predictions of natural systems like Earth’s atmosphere. The initiative will also bring students up to speed on a complex area of study that few people have mastered, creating a high demand for data assimilation specialists.

“The U.S. has a massive shortage of students coming from grad schools to fill positions at places like NOAA and push the boundaries of what we can do with our current models,” said Jonathan Poterjoy, an assistant professor in the Department of Atmospheric and Oceanic Science (AOSC) who studies data assimilation and was named UMD’s principal investigator for this collaboration. AOSC Associate Professor Kayo Ide, a data assimilation expert, also joined the UMD team participating in CADRE.

Although weather forecasts have vastly improved in the last several decades, the computer models used to create them need to be continuously upgraded to reflect new mathematical and technological developments. A recent example underscoring these shortcomings was the sudden onset of Hurricane Otis, which struck Mexico’s southern Pacific coast near Acapulco last fall and caused catastrophic damage.

“The storm went from virtually nothing to a major hurricane in less than a day, and none of the models got it right,” Poterjoy said. “That’s something that shouldn’t happen.”

Extreme weather events are also becoming more common, creating an urgent need for more accurate forecasts.

“The U.S. is experiencing nearly six times more major weather and climate disasters per year than it did 40 years ago, and the Biden-Harris administration is committed to ensuring we have the most accurate data possible to mitigate the impact of these disasters and fight climate change,” said U.S. Secretary of Commerce Gina Raimondo. “This investment, made possible thanks to President Biden’s Inflation Reduction Act, will upgrade and improve NOAA’s technology for numerical weather prediction capabilities to ensure accurate and timely information is available to the public and public safety officials in the face of extreme weather and climate events, making our communities more climate-resilient.”

In addition to UMD, the CADRE collaboration includes Colorado State University, Howard University, Pennsylvania State University, the University of Oklahoma and the University of Utah. Most of these institutions will focus on land surface or atmospheric applications, but Poterjoy and Ide will explore ways to improve data assimilation for two lesser-studied parts of global weather systems: the ocean and cryosphere, otherwise known as the Earth’s ice.

Data assimilation can help paint a better picture of what’s happening in a weather system and can lead to more accurate predictions of tropical cyclone intensity, rainfall, snow depth, thunderstorm wind speeds, and more. It corrects a weather model in real time by taking new observations into account, and models such as the Global Forecast System—used by NOAA to produce weather forecasts—rely on these constant updates.

Poterjoy said he’s most excited to involve UMD graduate students and postdocs in this collaboration, saying, “You’re going to end up with students graduating from our program with a better understanding of data assimilation as well as some of these outstanding issues with modeling. And if you’re graduating from our program with expertise in data assimilation, you’re going to have excellent job prospects.”

This article is adapted from text provided by NOAA.



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