Topographic variations have substantial impacts on surface hydrologic processes. This study introduced a new subgrid structure and methods to increase model accuracy for snow water equivalent predictions.

To gain a mechanistic understanding of the physical processes responsible for the enhanced hurricane cold wakes near the Southeast United States, investigators used ocean reanalysis datasets.

The Delaware River Basin is projected to experience a regional increase in flood severity under future climate scenarios.

Vijay Murugesan highlights how AI can accelerate materials discovery at the Volta Foundation’s Battery Forum.

At the 2024 Aviation Futures Workshop, researchers from PNNL joined other subject matter experts and representatives from the stakeholder community in reimagining the passenger experience.

Three PNNL researchers will receive five continuous years of funding for projects through highly competitive DOE Early Career Research Program awards.

Cloud and its radiative effect are among the determining processes for the energy balance of the global climate; they are also the most challenging processes for the climate models to simulate.

Researchers develop a diagnostic framework to identify the sources of global monsoon simulation biases from an energy transport perspective.

Bylaska and team will aim to make computational design of functional materials more targeted, impactful, and user friendly through this award.

Three PNNL technologies have been named 2024 R&D 100 Award winners.

The results of this study reveal that the degree of Arctic amplification, despite being controlled by complicated interactions among multiple factors, can be analytically understood.

Neeraj Kumar discusses how AI can transform scientific research at the Platform for Advanced Scientific Computing Conference and Trillion Parameter Consortium European Workshop.

Lauren Charles, a chief data scientist at PNNL, will be presenting at the Forum on Microbial Threats for the National Academies of Sciences, Engineering, and Medicine.   

ChemReasoner combines decades of chemistry knowledge with large language models to propose strategies for effective new catalysts.

PNNL staff in the Artificial Intelligence and Data Analytics division were recognized by the TSA’s Innovation Task Force (ITF) for their contributions to cloud capabilities, development strategies, and smart management of cloud resources.

Researchers are planning for an electric grid that deploys machine learning to think ahead, plan for the worst, anticipate demand, and meet consumer needs safely and securely.

Researchers found that in a future where the Great Plains are 4 to 6 degrees Celsius (°C) warmer as projected in a high-emission scenario, these storms could bring three times more intense rainfall.

At the National Homeland Security Conference, researchers shared how partnerships and emerging technologies like artificial intelligence can play a key role in emergency management preparedness and response.

Researchers develop comprehensive framework for the Energy Exascale Earth System Model, incorporating advanced river and ocean models that improve how such interactions are simulated

New findings document fewer ship tracks, reduced cloud cover, and boosted warming after ship emissions regulations took effect in 2020.