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Media Contacts
A multi-institutional team of researchers led by the King Abdullah University of Science and Technology, or KAUST, Saudi Arabia, has been nominated for the Association for Computing Machinery’s 2024 Gordon Bell Prize for Climate Modelling.
Plants the world over are absorbing about 31% more carbon dioxide than previously thought. The research, detailed in the journal Nature, is expected to improve Earth system simulations that scientists use to predict the future climate, and spotlights the importance of natural carbon sequestration for greenhouse gas mitigation.
Prasanna Balprakash, director of AI programs for ORNL, discussed advancing climate and weather research through high performance computing and artificial intelligence as part of a September 18 panel for the United States Senate.
Karly Harrod, recipient of the Early Career Competition Laboratory Directed Research and Development award at ORNL, is focused on extracting disease data from reports. Passionate about global health, she looks forward to applying her expertise to climate data within the geospatial science and human security division.
Daryl Yang is coupling his science and engineering expertise to devise new ways to measure significant changes going on in the Arctic, a region that’s warming nearly four times faster than other parts of the planet. The remote sensing technologies and modeling tools he develops and leverages for the Next-Generation Ecosystem Experiments in the Arctic project, or NGEE Arctic, help improve models of the ecosystem to better inform decision-making as the landscape changes.
Scientists using high-resolution aerial scans and computational modeling concluded that wildfires, storms and selective logging have become key drivers behind rainforest carbon emissions, outpacing clear-cutting practices.
ORNL’s Joshua New was named the 2024 Researcher of the Year by R&D World magazine as part of its R&D 100 Professional Award winners.
A study found that beaches with manmade fortifications recover more slowly from hurricanes than natural beaches, losing more sand and vegetation. The researchers used satellite images and light detection and ranging data, or LIDAR, to measure elevation changes and vegetation coverage. Changes in elevation showed how much sand was depleted during the storm and how much sand returned throughout the following year.
Researchers at ORNL have demonstrated that small molecular tweaks to surfaces can improve absorption technology for direct air capture of carbon dioxide. The team added a charged polymer layer to an amino acid solution, and then, through spectroscopy and simulation, found that the charged layer can hold amino acids at its surface.
To better predict long-term flooding risk, scientists at the Department of Energy’s Oak Ridge National Laboratory developed a 3D modeling framework that captures the complex dynamics of water as it flows across the landscape. The framework seeks to provide valuable insights into which communities are most vulnerable as the climate changes, and was developed for a project that’s assessing climate risk and mitigation pathways for an urban area along the Southeast Texas coast.