This study used historical data, remote sensing, and aquatic sensors to measure how far wildfire impacts propagated through the watershed after the 2022 Hermit’s Peak/Calf Canyon fire, New Mexico’s largest wildfire in history.
The Coastal Observations, Mechanisms, and Predictions Across Systems and Scales: Field, Measurements, and Experiments project established a network of observational field sites across Chesapeake Bay and western Lake Erie.
Over the next four years, PNNL and University of Arizona will develop open-source computational tools to better identify and characterize the viruses associated with the human microbiome.
Armed with some of the world’s most advanced instrumentation, researchers at PNNL are working to analyze huge amounts of data and uncover hidden biological connections.
Alicia Amerson's passion for science communication, expertise in marine mammal research, and experience in wildlife photography provide a robust foundation for her new role with the Clallam County Marine Resources Committee.
A new digital twin platform can help hydropower dam operators by providing accurate and predictive models of physical turbines that improve facilities and enhance reliability.
Neeraj Kumar discusses how AI can transform scientific research at the Platform for Advanced Scientific Computing Conference and Trillion Parameter Consortium European Workshop.
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.
A compilation of soil viral genomes provides a comprehensive description of the soil virosphere, its potential to impact global biogeochemistry, and an open database for future investigations of soil viral ecology.
Researchers devised a quantitative and predictive understanding of the cloud chemistry of biomass-burning organic gases helping increase the understanding of wildfires.
