A new study uses direct numerical simulations to develop a near-surface turbulence model for thermal convection using interpretable and physics-aware neural networks, broadening the applications of numerical simulations.
PNNL’s Chris Chini has been named a guest editor of Environmental Research: Infrastructure and Sustainability’s special issue examining energy infrastructure vulnerabilities from physical and natural threats.
Decreased snow cover observed over the past few decades and projected for the future suggest increasing snow droughts that threaten water security and management.
Using regional meteorological data from an atmosphere reanalysis product, scientists identified 12 unique winter weather systems in the Puget Sound area, featuring differing precipitation and temperature responses to climate variabilities.
The Emissions Model Intercomparison Project examined how selected emissions-related properties affected results in 11 global chemistry and Earth-system models.
The Earth System Model Aerosol–Cloud Diagnostics package version 2 uses aircraft, ship, ground, and satellite measurements to evaluate detailed physical processes in aerosols, clouds, and aerosol–cloud interactions.
In soil, microbes produce and consume methane. Using a technique called pool dilution, researchers can separate the rate of methane production and consumption from the net rate.
PNNL scientists developed a new method to map exactly how a fungus works with leafcutter ants in a complex microbial community to degrade plant material at the molecular level. The team’s insights are important for biofuels development.
