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 have developed the first coastal transport model for microplastics to understand how particles move in waterways and coastal currents.

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.

PNNL's E-COMP initiative is helping unleash American energy innovation with advanced theories, models, and software tools to better operate power systems that rely heavily on high-speed power electronic control.

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.

For PNNL’s Jonathan Evarts, Hope Lackey, and Erik Reinhart, this partnership with WSU opened doors and provided opportunities for their scientific careers to flourish.

A new report details the potential for floating offshore wind to lower energy costs and enhance the resilience of the nation’s western grid.

PNNL’s year in review includes highlights ranging from advancing soil science to understanding Earth systems, expanding electricity transmission, detecting fentanyl, and applying artificial intelligence to aid scientific discovery.

A new analysis shows how renewable energy sources like solar, wind and hydropower respond to climate patterns, and how utilities can use this data to save money and invest in energy storage.

A new digital twin platform can help hydropower dam operators by providing accurate and predictive models of physical turbines that improve facilities and enhance reliability.

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

Staff at PNNL recently traveled to Cyprus to facilitate a multilateral workshop on chemical forensics investigations hosted by the U.S. Department of State, Office of Weapons of Mass Destruction Terrorism.

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

Staff at PNNL recently visited the University of Texas at San Antonio to deliver lectures on international law, arms control, and nuclear nonproliferation during Nuclear Policy Week.

Although climate change may bring increased precipitation to many parts of the United States, some areas may face drier conditions and lower streamflow, resulting in decreased hydropower generation.

PNNL staff scientist selected as a guest editor for a special issue titled “Ligand-Metal Complementarity in Rare Earth and Actinide Chemistry,” in the well-known journal Inorganic Chemistry.

New methodological approach demonstrates how to assess the economic value, including non-traditional value streams, of converting non-powered dams to hydroelectric facilities.