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.

The Generator Scorecard, developed by PNNL in partnership with BPA, automates generator evaluations, reducing engineering workloads and improving grid reliability.

EGRASS wins in the software/services category and is awarded a gold medal as special recognition in corporate social responsibility.

The National Transmission Planning Study presents several transmission expansion scenarios that would reliably support the growing demand for energy across the nation.

Three PNNL technologies have been named 2024 R&D 100 Award winners.

PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.

ChatGrid™ is a practical application of the Department of Energy’s exascale computing efforts and offers a new experience in easy, intuitive, and interactive data interaction.

Results of the PR100 study outline near- and short-term strategies for Puerto Rico to achieve a renewable power grid by 2050.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

Battery energy storage systems are being proposed in municipalities across the U.S. PNNL researchers can help community planners guide safe siting and operations.

Recovery Simulator and Analysis tool further strengthens PNNL’s short-term resilience planning efforts for Puerto Rico.

ExaGO, a power grid simulation and optimization platform developed at PNNL is the first of its kind to run on Frontier.

Findings in a new PNNL report show long-duration energy storage will be a necessity in decarbonizing the grid and recommends the planning and procurement process to identify those needs start immediately.