PNNL study explored multiple factors that could impact future snowpack—a critical source of water for communities, irrigation and energy generation.

An energy expert and economist who has played a leading role in formulating and coordinating U.S. climate policy is the new director of the Joint Global Change Research Institute in College Park, Maryland.

A 19-person, multi-institutional national laboratory team received the inaugural Gordon Bell Prize for Climate Modeling from the Association for Computing Machinery for their work on more accurately modeling deep convective clouds.

New research shows how cloud shapes affect the process of cloud evolution, resulting in better understanding of how clouds behave, improving weather forecasts, and enhancing comprehension of climate systems.

Earth Scientist Laura Fierce mentors Department of Energy Science Graduate Student Research program awardees.

From energy storage to cybersecurity, this 2023 wrap-up offers a glimpse of PNNL innovations with a seasonal twist.

As electricity grids incorporate renewables, several factors will constrain future output, according to a new paper.

If current warming trends continue, heat waves like Washington's deadliest could grow stronger and afflict the Pacific Northwest more often.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

Scientists recently developed a flow direction model which produces high-quality flow routing parameters on any mesh system.

1-propanol converts from a monomer into a trimer at aluminum sites within zeolite pores.

Investigating the impact of global warming on mesoscale convective systems initiation and growth with a theoretical model.

The cross-equatorial surge enhances the southward development of the Madden–Julian oscillation because of increased moisture convergence.

Understanding the contrasting response in relative humidity at ocean and land surfaces under global warming.

The roles of the various environmental variables in the transition from suppressed to active tropical precipitation regimes are characterized using statistical analysis and machine learning.

A new moist potential vorticity model helps researchers understand atmosphere–land moisture exchanges over the United States.

Robert Rallo from Pacific Northwest National Laboratory will direct a machine learning thrust for a new Department of Energy-funded project led by SLAC National Accelerator Laboratory.

A modeling study finds that multiple factors almost perfectly balance under anthropogenic greenhouse gas forcing, leaving no footprint on the dynamically induced ocean heat storage in the Southern Ocean.

Less pollution and the odd shapes of snow grains as they pack together should help cut the decline of snowpack later this century.

Claudia Tebaldi, a PNNL Earth scientist, has been named a Fellow of the American Geophysical Union. Tebaldi and others will be recognized at AGU23 in December.