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.

Continued studies will deepen scientists’ understanding of virus-host interactions at the molecular level and also pave the way for developing better drugs to fight emerging viruses.

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 new study led by PNNL researcher TC Chakraborty provides some answers about how irrigated agricultural land near cities affects urban heat stress.

Ampcera has an exclusive licensing agreement with PNNL to commercially develop and license a new battery material for applications such as vehicles and personal electronics.

CACTUS provides AI-powered cheminformatics for autonomous science.

PNNL's new energy storage facility now houses the Lab's vehicle battery research programs, which have more lab space and a slew of new capabilities.

PNNL scientists use proteomics to unveil how high-density lipoproteins protect against cholesterol accumulation in the artery wall.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

Early life exposure to polycyclic aromatic hydrocarbons (PAHs), found in smoke, has been linked to developmental problems. To study the impacts of these pollutants, PAH metabolism in infants and adults were compared.

PMedIC, the PNNL and OHSU joint research collaboration, contributes to student success and impact in biomedicine.

Discovering and measuring the spatial organization of proteins within cells allows scientists to map complex proteoforms across tissues with near-cellular resolution.

Data reveals mechanisms in our bodies that can help us fight viral pathogenesis.

Models have identified a new source of anthropogenic emissions driving the observed weakening of the Atlantic Meridional Overturning Circulation.

Pacific Northwest may face increase in summer heat-dome-like stationary waves.