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.

By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.

PNNL teamed up with multiple agencies to install a battery energy storage system at a South Dakota Air Force base.

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

Senior Advisor Isabella van Rooyen shares her journey from child to internationally recognized scientist in nuclear materials and manufacturing.

This is the first time a flow battery with 24-hour discharge capacity will be deployed and tested in a field environment.

For her most recent efforts, Bruckner-Lea, a senior technical advisor at PNNL, received the Secretary’s Appreciation Award from the U.S. Secretary of Energy Jennifer Granholm in July.

PNNL receives a 2023 Federal Laboratory Consortium Far West Regional Award for a technological innovation that could help make the U.S. a producer of critical minerals used in electronics and energy production.

PNNL’s Katie Arkema was selected to be on NASEM committee focused on public health and conservation.

For a second year in a row, doctoral intern Jack Watson was awarded the Student Merit Award by the Society for Risk Analysis and the Resilience Analysis Specialty group.

Five staff members from PNNL received awards from the Department of Energy’s Federal Energy Management Program for contributions to projects for the U.S. Army.

A new version of the Department of Energy’s Technical Resilience Navigator allows users to prioritize resilience solutions based on both risk reduction and emissions impact.

Researchers studied water cycling to assess the achievability of net-zero water usage at military installations in the Pacific Islands.