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.

COVID-19 infections at PNNL early in the pandemic were caused by a wide variety of viral sequences, according to a new analysis by Laboratory researchers.

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.

A project team at PNNL has been honored with the Project Management Achievement Award for 2022 from the Department of Energy.

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

Ann Lesperance has been invited to continue her role on the Domestic Preparedness advisory board, which convenes multidisciplinary subject matter experts to support the Domestic Preparedness Journal's editorial plan.

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

Based on the early success of CHIRP and the urgency to build the future cybersecurity workforce, the program recently received five million dollars in funding through the FY23 Defense Appropriations Bill, via SSC.

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

A combined experimental and theoretical study identified multiple interactions that affect the performance of redox-active metal oxides for potential electrochemical separation and quantum computing applications.

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.

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

Irradiated boehmite nanoplatelets form smaller aggregates and have a rougher surface than non-irradiated platelets.