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.

Researchers at PNNL studied the effects of high temperatures and ionizing radiation on tungsten heavy alloys.

PNNL's accomplishments in FY 2024 help address the remaining challenges the wind industry faces.

PNNL researchers co-organized a workshop on fusion commercialization with partners from industry and academia

PNNL researchers will pursue both fundamental and applied projects with this support from the Department of Energy

Combining cold spray deposition and friction stir processing for a more efficient route to oxide dispersion strengthened steel.

PNNL researchers studied the microstructure of lithium silicates under emulated fusion conditions.

With the launch of a large research barge, PNNL and collaborators took another significant step to improve offshore wind forecasting that will lower risk and cost associated with offshore wind energy development.

Researchers studied the boundary precipitation of tungsten heavy alloys in an extended high temperature irradiation environment

The Department of Energy Office of Nuclear Energy acting assistant secretary makes his first visit to a national laboratory in his new role, touring PNNL's Radiochemical Processing Laboratory.

Researchers seek to bring down costs, address potential environmental risks and maximize the benefits of harnessing wind energy above the deep waters of the Pacific.

PNNL research exploring tungsten heavy alloys for use in advanced nuclear fusion reactors makes Scientific Reports Top 100 Collection.

The nation is closer to its offshore wind energy goals than ever before, but better wind forecasting is still needed. To address this challenge, PNNL and collaborators are charting a new course with help from novel technology.