The project received an Innovative and Novel Computational Impact on Theory and Experiment (INCITE) award, a highly competitive U.S. Department of Energy Office of Science program.

Researchers introduced a simulated carbon cycle to the Energy Exascale Earth System Model, broadening its utility and enabling new research directions.

Ecosystem feedback fire model opens new investigative pathways into impacts of fire on future climate.

Increased precipitation intensity and hydrologic extremes are associated with atmospheric rivers under warming temperatures.

Developing an R package for modeling land use and land cover change.

Hybrid land use model incorporates key factors to understanding agriculture’s potential response to climate change.

Researchers at Pacific Northwest National Laboratory (PNNL) are closer to understanding how iron may pave the way for sequestration of technetium-99 contaminants in the subsurface.

PNNL data scientists Ján Drgoňa and Draguna Vrabie are working to reduce deployment costs of advanced energy control systems for buildings.

Differences in the rainfall intensity of mesoscale convective systems and other types of warm—season rainfall in the central United States lead to differences in their impacts over land.

Researchers developed a new tool that combines artificial intelligence and microscopy data to rapidly test new materials for fusion reactor use.

PNNL and Microsoft Quantum partner to link quantum circuits to powerful government supercomputers.

Atmospheric rivers that make landfall on the U.S. West Coast show broad increases in size and intensity with warmer local sea surfaces.

Floodplain inundation simulations shed light on flood generation mechanisms and the increasing role of extreme rainfall.

Pacific Northwest National Laboratory researchers developed a graphical processing unit (GPU)-centered quantum computer simulator that can be 10 times faster than any other quantum computer simulator.

Researchers at PNNL have developed a bacteria testing system called OmniScreen that combines biological and synthetic chemistry with machine learning to hunt down pathogens before they strike.

Information extracted from a variety of atmospheric observations can correct the behavior of a model and improve simulated clouds.

A small collection of naturally interacting soil microbes could enable new studies of community interactions and metabolism.

PNNL’s new Smart Power Grid Simulator, or Smart-PGSim, combines high-performance computing and artificial intelligence to optimize power grid simulations without sacrificing accuracy.

Like a toxic Trojan horse, microplastics can act as hot pockets of contaminant transport. But, can microplastics get into plant cells? Recent research shows that they can't.

Community Land Model 5.0 can represent how irrigation influences water, carbon, and nitrogen budgets throughout a highly managed semiarid watershed.