The Department of Energy’s Vehicle Technologies Office recently issued two awards to researchers at PNNL for their contributions to areas that are crucial for the expansion of electric vehicles.

Summer is for science! PNNL’s interns are diving into science and technology and getting a front-row view of the research and development of a national laboratory.

Different sources of low-level moisture perturbation can result in differences in the timing and location of a large, modeled storm.

Regional wind data helps utilities save money, plan for windy days.

Randomly constructed neural networks can learn how to represent light interacting with atmospheric aerosols accurately at a low computational cost and improve climate modeling capabilities.

A success story of applying convergence testing to detect and address issues of numerical discretization in nonlinear representations of turbulence and clouds.

A holistic evaluation of the uncertainty sources that arise from configuring the model to processing the output for global variable-resolution models.

Researchers found a 150-day period in Antarctic circulation, something that many current climate models do not represent accurately.

Four PNNL researchers received highly competitive DOE Early Career Research Program awards, providing five continuous years of funding for their projects.

A new open-source feature tracking package is now available to facilitate advanced model evaluation, model development efforts, and scientific discovery.

PNNL welcomes six Department of Energy Office of Science Graduate Student Research awardees from across the nation.

ACMD staff contributed to 30 years of atmospheric data collection for the Department of Energy’s Atmospheric Radiation Measurement user facility.

Two researchers at PNNL have been named fellows of the American Chemical Society: Karthikeyan Ramasamy and Yuyan Shao.

Algae can collect and concentrate rare earth metals from seawater—an alternative to imported sources mined from the ground.

Models show that in a warmer climate, the 2012 North American derecho would shrink and decay earlier in Mid-Atlantic coastal areas.

By adding rain, snow, and rain-on-snow precipitation data to a background model, a new scheme pinpoints local flood risks in order to improve the design of small-scale hydrological infrastructure.

Developed a data-assimilation method based on physics-informed deep learning to resolve downscaled flow fields within a large-scale river model.

Chemical Engineer Yong Wang explains the influence and opportunity for joint appointments. Wang maintains one of the longest joint appointment tenures at PNNL.

Unveiling diverse scenarios and implications for water resource management in a rapidly changing world.

DOE gives Hydrogen Program Special Award to PNNL's Hydrogen Safety Panel at department's 2023 Annual Merit Review and Peer Evaluation Meeting.