With the help of the U.S. State Department, PNNL climate scientists assisted counterparts in Malaysia and Thailand in exploring carbon neutral goals.

Clustering wildfires into four types based on their land-atmosphere drivers can potentially improve regional wildfire predictions.

PNNL’s Center for the Remediation of Complex Sites convened attendees from around the world to discuss challenges associated with environmental contamination.

Pacific Northwest may face increase in summer heat-dome-like stationary waves.

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.

PNNL researchers comment on the “Adversarial Machine Learning” white paper from the National Institute of Standards and Technology.

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.

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.

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.