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.

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

A PNNL-developed computational framework accurately predicts the thermomechanical history and microstructure evolution of materials designed using solid phase processing, allowing scientists to custom design metals with desired properties.

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.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

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.

Research published in Journal of Manufacturing Processes demonstrates innovative single-step method to manufacture oxide dispersion strengthened copper materials from powder.

Better representing electric capacity markets, economic retirements, and power-plant age structure provides a more robust understanding of the future evolution of the electric sector.

MSD-LIVE, a cloud-based data and code management system, will be released in summer 2022 for hundreds of scientists.

An improved model captures the interactions between the U.S. economy, energy, water, and land systems with increased spatial and temporal detail.

A climate change study co-authored by PNNL scientist Hailong Wang inspired an artist to create an exhibit based on the research.

PNNL contributes to 30 years of data on clouds, radiation, and other climate-making factors as part of field campaigns and analysis conducted by DOE's Atmospheric Radiation Measurement user facility.

New work developed a methodology to generate building temperature setpoint schedules for use by modelers in large-scale building energy simulations.