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.
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.
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.
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.
This work shows that linear pattern scaling is an effective means of obtaining global-to-local relationships for CMIP6 models, as it has been in past model eras.
Operators of critical infrastructure are trained to respond to cyberattacks using scale models of water treatment plants, freight rail yards, and more.
Sergei Kalinin honored with the David Adler Lectureship Award for contributions to materials physics through automated experimentation and ferroelectric materials work.
International compliance analyst Madalina Man highlighted the history of international safeguards on a podcast by the United Arab Emirates Federal Authority for Nuclear Regulation.