PNNL’s Climate Network with MSIs and HBCUs aims to bring opportunities to diverse populations.

Atmospheric rivers, filaments of intense moisture transport in the atmosphere, can now be automatically detected in satellite observations.

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.

PNNL researchers have found that as the shape of a cloud evolves, it demonstrates predictable patterns.

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

PNNL research unlocks key findings needed for potential commercial deployment of carbon mineralization technology.

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

A team of scientists at PNNL developed new computational models to predict the behavior of these impurities and reduce the expense and risk related to actinide metal production.

Researchers designed ultra-low radiation cables to reduce background noise for highly sensitive neutrino and dark matter detectors.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

PNNL’s DataLife tool analyzes and identifies bottlenecks in scientific workflows.

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

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

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

Ripples demonstration will take place at the DOE booth at the International Conference for High Performance Computing, Networking, Storage, and Analysis.

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.

This study revealed that fresh organic vapors are soluble in particulate organics that are actively growing in size. However, if the particulate matter ages, fresh organic vapors can no longer mix with the organic matter.

Leaders from the DOE Office of Energy Efficiency and Renewable Energy visited PNNL October 19–20 for a firsthand look at capabilities and research progress.

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