The effects of too much CO2 can cause clouds covering the oceans to dissipate and be unable to reform.

Hector, a reduced complexity climate model, can be calibrated to emulate 30 different complex, computationally expensive Earth System Models.

Using public data from the entire 1,500-square-mile Los Angeles metropolitan area, PNNL researchers reduced the time needed to create a traffic congestion model by an order of magnitude, from hours to minutes.

New experiments show organic aerosol can be lost from the atmosphere faster than most models predict.

PNNL researchers have shown an improved binarized neural network can deliver a low-cost and low-energy computation to help the performance of smart devices and the power grid.

Historical weather data informs projections of global yields of economically important crops.

To accurately model future U.S. agricultural production, changes in international crop yields cannot be ignored.

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.

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

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.