Policy changes in power, energy, buildings, and more could help slow global temperature rise, according to a new report with co-authors from PNNL’s Joint Global Change Research Institute.

Beyond melting ice and higher temperatures: On Earth Day, scientists consider how climate change will affect national security.

PNNL researchers have used field campaign data to better understand clouds, aerosols, and the interactions between humans and the atmosphere.

Published in Nature Communications, Increased Asian Aerosols Drive a Slowdown of Atlantic Meridional Overturning Circulation, identifies the role aerosols over Asia is having on the AMOC, a complex system of currents in the Atlantic Ocean.

The use of disciplines in pure mathematics can increase the reliability and explainability of machine learning models that “transcend human intuition,” according to PNNL scientists.

Regional wind data helps utilities save money, plan for windy days.

By adding rain, snow, and rain-on-snow precipitation data to a background model, a new scheme pinpoints local flood risks in order to improve the design of small-scale hydrological infrastructure.

Scientists at PNNL are working to better prepare authorities, emergency responders, communities and the grid in the face of increasingly extreme hurricanes.

Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.

As wildfires grow increasingly severe, PNNL researchers are working to slow their spread and mitigate their harmful effects.

Focused research studies of advanced algorithms and materials are setting the stage for the next generation of quantum computers.

COVID-19 changed when and where we use electricity. Researchers showed that commonly available total demand data masked the actual changes.

Artificial intelligence-based decision tool enables grid operators to respond more quickly and effectively to grid emergencies.

Researchers to design their own computer accelerators for faster analysis of large datasets.

OpenCGRA expedites the design-prototype cycle of computer architecture development.

A research project that brings together mathematicians and atmospheric scientists has developed into a deep collaboration for improving atmospheric models.

Risk analysis on the plutonium-fueled power system that supplies electricity to the Mars rover answered the “what if” nuclear safety questions for NASA.

Marcel Baer is a computational scientist working in PNNL’s Physical Sciences Division with a prominent effort in materials science and physical bioscience.

PNNL has released the first version of ExaGO, an open-source grid modeling software that can take advantage of emerging heterogeneous computing architecture to help grid operators plan ahead for extreme events.

With quantum chemistry, researchers led by PNNL computational scientist Simone Raugei are discovering how enzymes such as nitrogenase serve as natural catalysts that efficiently break apart molecular bonds to control energy and matter.