The ability of a storm-resolving weather model to predict the growth of storms over central Argentina was evaluated with data from the Clouds, Aerosols, and Complex Terrain Interactions (CACTI) field campaign in central Argentina.

Researchers from PNNL and Parallel Works, Inc., applied machine learning methods to predict how much oxygen and nutrients are used by microorganisms in river sediments.

Lakes are important sentinels of climate change and contribute significantly to the emissions of the second most important greenhouse gas—methane.

The rate of conversion of cloud droplets to precipitation, known as the autoconversion rate, remains a major source of uncertainty in characterizing aerosol’s cloud lifetime effects and precipitation in global and regional models.

To assess the impact of observation period and gauge location, model parameters were learned on scenarios using different chunks of streamflow observations.

This study presents an automated method to detect and classify open- and closed-cell mesoscale cellular convection (MCC) using long-term ground-based radar observations.

The National Transmission Planning Study presents several transmission expansion scenarios that would reliably support the growing demand for energy across the nation.

New transmission lines and renewable energy projects would bring economic and climate change benefits to the Western United States’s electricity grid.

The Federal Laboratory Consortium for Technology Transfer has given three national awards to PNNL technology teams.

A new PNNL report says the western U.S. power system can handle large-scale vehicle electrification up to 24 million vehicles through 2028, but more than that and cities could start feeling the squeeze.

Grid modernization, improved energy storage goals of agreement between PNNL and East Coast energy company.

PNNL chief engineer, Jeff Dagle, helps roll out National Academies report on grid resilience.