Scientists at PNNL were awarded nearly $12 million to better understand pathogens, how they spread, and how to prepare the nation against future outbreaks.

Unveiling diverse scenarios and implications for water resource management in a rapidly changing world.

Computational chemistry libraries from NWChem, NWChemEX, SPEC, and more are now available on Azure Quantum Elements.

Quantifying the long-term destination of anthropogenic emissions and robustness of global carbon sinks.

New study identifies crucial factors for more accurate hydrological predictions in the Community Land Model version 5.

Groundwater modeling of irrigation return flow dynamics is important for improving estimates of water availability.

ExaGO, a power grid simulation and optimization platform developed at PNNL is the first of its kind to run on Frontier.

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.

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

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

Advances in understanding the nature of the chemical bond are featured in this special issue of The Journal of Chemical Physics.

Mesoscale convective systems that are clustered in time and space have broader impacts on flooding than individual systems.

A scenario approach was used to explore the potential future role of hydropower around the globe considering the multisectoral dynamics of regional energy systems and basin-specific water resources.

A new report, based on a community workshop and literature review, summarizes some of the biggest challenges in understanding and modeling Earth system and human–Earth system dynamics in the Puget Sound region of Washington State.

Building new climate outcome scenarios by stitching together pieces of existing ones.

Researchers found that specific landscape metrics consistently outperform traditional population downscaling methods.

A systematic, multiple scenario approach was used to analyze the compounding impacts of demands for land for biofuels with increased land scarcity under a diverse set of uncertainties.

rmap enables users with limited to no geographic information system knowledge use R to visualize simple tabular data.

The methods researchers use to estimate crop yield gaps determines the location of projected future agricultural “breadbasket” regions.