This study examined the role of river sinuosity using computer models to understand what drives hyporheic exchange, a process that significantly affects water quality and ecosystem health.
PNNL biodefense experts seek to identify, understand and mitigate the risks of biological pathogens—whether naturally occurring or intentionally created—so steps can be taken to prepare and respond.
PNNL postdoc Pengfei Shi won first place in the Early Career Researcher Poster Competition at the recently concluded NOAA Subseasonal and Seasonal Applications Workshop.
Data-gathering instruments will be positioned on commercial, ocean-going ships in a Department of Energy-funded project that is expected to improve understanding of marine atmosphere and aerosol–cloud interactions.
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.
Ultra-thin layers of silk deposited on graphene in perfect alignment represent a key advance for the control needed in microelectronics and advanced neural network development.
In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.
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.
To gain a mechanistic understanding of the physical processes responsible for the enhanced hurricane cold wakes near the Southeast United States, investigators used ocean reanalysis datasets.
