The research presented in this article significantly enhances the ability to predict and prepare for compound flood events along the U.S. coastline.

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

This study provides a comprehensive analysis of isolated deep convection & mesoscale convective systems using self-organizing maps to categorize large-scale meteorological patterns and a tracking algorithm to monitor their life cycle.

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

This study explored the future effects of climate change and low-carbon energy transition (i.e., emission reduction) on Arctic offshore oil and gas production.

Hydropower could expand substantially during the 21st century in many regions of the world to meet rising or changing energy demands. However, this expansion might harm river ecosystems.

Three PNNL-supported projects are at the forefront of developing advanced data analytics technologies to enhance the U.S. power grid’s reliability, resilience, and affordability.

Mengqi Zhao and Chris Vernon were selected to serve in editorial roles at JOSS for Earth science and data science, respectively.

Using numerical simulations to reproduce the laboratory experiments, this study reveals that liquid droplets are present near the bottom surface, which warms and moistens the air in the chamber.

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

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

Tirthankar (TC) Chakraborty, an Earth scientist at PNNL, was recently selected as a 2024–2025 Levenick Resident Scholar in Sustainability Leadership at the University of Illinois, Urbana-Champaign.

Skillful predictions of tropical cyclone activity on subseasonal time scales may help mitigate their destructive impacts. This study investigates the combined impacts of atmospheric phenomena to better understand cyclone activity.

Topographic variations have substantial impacts on surface hydrologic processes. This study introduced a new subgrid structure and methods to increase model accuracy for snow water equivalent predictions.

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

New transmission lines and renewable energy projects would bring economic and climate change benefits to the Western United States’s electricity grid.

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

The results of this study reveal that the degree of Arctic amplification, despite being controlled by complicated interactions among multiple factors, can be analytically understood.

The Grid Storage Launchpad dedication event was attended by leaders in grid and transportation energy storage, battery innovation, and industry stakeholders working to transform America’s energy system.

Although climate change may bring increased precipitation to many parts of the United States, some areas may face drier conditions and lower streamflow, resulting in decreased hydropower generation.