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.

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.

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

New datasets delineating global urban land support scientific research, application, and policy, but they can produce different results when applied to the same problem making it difficult for researchers to decide which to use.

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

The demand for energy is growing—and so is the technology supporting it. However, future development of power generation technologies could be affected by a key factor: material supply.

The Delaware River Basin is projected to experience a regional increase in flood severity under future climate scenarios.

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.

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

Earth Scientist Laura Fierce mentors Department of Energy Science Graduate Student Research program awardees.

Variations in the level of market globalization can greatly affect the amount of water required to meet future global demand for agricultural commodities.