Researchers have knitted together three large databases of information to help cybersecurity experts detect and prevent attacks.

PNNL researchers explore the feasibility of using low-flying drones to survey sites for low levels of radiation.

Assessing observed weather conditions that support or suppress the growth of clouds into deep precipitating storms during the Cloud, Aerosol, and Complex Terrain Interactions experiment.

Multiple concurrent single-particle measurements help develop a quantitative and predictive understanding of secondary organic aerosols.

Applying a novel framework to a climate model reveals new characteristics about how elevated concentrations of aerosols affect clouds.

A review describes the latest techniques for simulating hydropower at large scales to inform power grid planning and operations.

Hydropower generation estimated using water proxy data leads to a revision of the nation’s historical seasonal hydropower output.

PNNL researchers teamed up with marine energy developers to test a new wave energy conversion device through the TEAMER program.

Three PNNL authored papers were accepted as posters to the ICLR 2023 Workshop on Physics for Machine Learning and Workshop on Mathematical and Empirical Understanding of Foundation Models.

As the world races to discover solutions for reaching net zero carbon emissions, a PNNL analysis quantifies the economic value of the existing nuclear power fleet and its carbon-free energy contributions.

A deep learning model overcomes persistent challenges in emulating long-term simulations of secondary organic aerosols.

The frequency and intensity of storms affecting U.S. coastal areas will likely increase in a warming world.

Researchers investigated the impact of using constant versus spatially varying crop parameters on carbon and energy fluxes in a realistic crop rotation scenario.

A new model uses machine learning to project electricity loads across the United States.

Under Secretary for Science and Innovation at the Department of Energy Geri Richmond visited PNNL.

Watershed hydrological responses are sensitive to the spatial and temporal resolution of the gridded meteorological forcing used in simulations.

Physicist Emily Mace will share her science journey and an interactive presentation about her current research with middle school and high school students from across the country at the National Science Bowl.

Research.com ranked PNNL joint appointee George Karniadakis as one of the top mathematicians in the world.

Future global warming-induced changes to watershed and coastal processes can significantly affect the magnitude of fluvial-coastal compound flooding.

Information encoded in streamflow reveals how the water-storage capacity of thawed ground changes as permafrost thaws.