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.

Delivering an integrated quantum-mechanical and experimental perspective on the effects of both intrinsic and externally applied electric fields at atomic-scale interfaces.

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.

Isotopically layered water films and slow heating enable diffusion tracking.

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.

A team combined experiments and theory to predict the collective properties of electrolyte solutions.

The first measurement of the proton diffusion constant at cryogenic temperatures provides insights into the mechanism of proton movement in supercooled water.

RemPlex and IAEA convene international leaders to tackle recruitment and retention in complex environmental cleanup efforts.

Pacific Northwest National Laboratory researchers developed a new theoretical method for studying highly correlated systems.

Researchers found that in a future where the Great Plains are 4 to 6 degrees Celsius (°C) warmer as projected in a high-emission scenario, these storms could bring three times more intense rainfall.

A recent study suggests a higher global mean precipitation increase and narrows the uncertainty range.

Researchers investigated how stable nanoparticle suspensions form using facet engineering on hematite nanoparticles, demonstrating that controlling the faceting of nanoparticles can effectively maintain particle dispersity.

With the help of the U.S. State Department, PNNL climate scientists assisted counterparts in Malaysia and Thailand in exploring carbon neutral goals.

PNNL’s Center for the Remediation of Complex Sites convened attendees from around the world to discuss challenges associated with environmental contamination.

A team of scientists at PNNL developed new computational models to predict the behavior of these impurities and reduce the expense and risk related to actinide metal production.