Scientists develop a water tracer tool in an advanced hydrologic model to understand the importance of modeling lateral flow in hydrologic simulations.

Researchers develop new, weakly coupled land data assimilation system to make better climate predictions and projections.

Scientists use water vapor tracers incorporated in a climate model to tag moisture from local evapotranspiration and trace their evolution through different processes.

Researchers evaluate a new slab ocean capability in the Energy Exascale Earth System Model (E3SM) version 2 by comparing its climate simulation to that of the full version of E3SM that uses a dynamic ocean model.

Aerosol particles imbue climate models with uncertainty. New work by PNNL researchers reveals where in the world and under what conditions new particles are born.

Climate change is bringing more extreme summer weather, from heat waves to hurricanes, that can disrupt the flow of electricity. Here’s how PNNL scientists are working on solutions to protect the nation’s electric grid.

Accessing groundwater may become more difficult—and more expensive—as groundwater supplies become increasingly scarce and underground aquifer levels fall.

Robert Rallo discussed PNNL’s artificial intelligence research at the Seattle AI Investor Summit and Showcase

Researchers will explore climate, pathogens and energy-efficient microelectronics using 3 million node hours on the nation’s supercomputers.

Researchers developed a framework for representing aerosol particles in climate models.

Researchers demonstrate an AI that can be taught to recognize cloud types by looking at millions of satellite images of clouds without requiring human input.

Researchers measured ice nucleating particles composition at the Southern Great Plains atmospheric observatory, enabling them to identify sources of particles that make them effective ice nucleators.

National laboratory expertise was on display at the 2024 Department of Homeland Security Research, Development, Test, and Evaluation Summit.

A recent study suggests a higher global mean precipitation increase and narrows the uncertainty range.

James Koch, a data scientist, developed a technique that enables high-fidelity remote sensing with limited data.

PNNL hosted the inaugural Global Wildlife Data Sharing Conference on May 20-21, 2024.

Researchers find ultrafine particles abundant in smoke from Amazon forests fire may intensify storm clouds and heavy rain.

Using a refined Earth system model, researchers found that wetlands over North America will be significantly affected by climate change under future scenarios

Researchers use dataset combining observational data with advanced numerical simulations to investigate the characteristics, drivers, and trends of extreme heat events in the High Arctic over past four decades

Researchers develop framework that tracks the aerosol–cloud interactions along the trajectories of air parcels and embed framework into Weather Research Forecast model.