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.
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.
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.
To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.
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.
PNNL researchers developed a new model to help power system operators and planners better evaluate how grid-forming, inverter-based resources could affect the system stability.