Research provides overview of the consequences of a new set of future scenarios based on Earth system model simulations.

One year ago, Verizon announced a partnership that made PNNL the U.S. Department of Energy’s first national laboratory with Verizon 5G ultra-wideband wireless technology.

Quantifying the future energy requirements of agricultural, industrial, and municipal water sector use.

Calculating the multi-region and multisector effects of water scarcity for thousands of possible future socioeconomic, climate, and hydrologic scenarios.

Explainable artificial intelligence—understanding and explaining the reasoning behind AI decisions—is a necessity for national security.

An overview of the Energy Exascale Earth System Model project describing its goals, science drivers, and development and highlighting its key findings.

Michael Henry, a senior data scientist at PNNL, has accepted a joint appointment at the Texas A&M University RELLIS Center for Applied Research and Experiential Learning.

Scientists used the strength of land-atmosphere coupling to improve predictions of East Asian summer monsoon rainfall.

A new type of ice chamber allows researchers to understand how ice forms on atmospheric aerosol particles.

Explainable AI helps scientists understand and untangle the threads of information that the system uses to make choices or recommendations.

PNNL data scientists Henry Kvinge and Ted Fujimoto presented their research on few-shot learning and reinforcement learning, respectively, at workshops during the 2021 AAAI Conference on Artificial Intelligence.

Current representations of shallow clouds in climate models have biases that lead to inaccuracies in models.

A new process-oriented diagnostic approach provides new insights into simulated storms and their environments.

New approach allows nonexperts to optimize control of a building's energy systems without adding computing power or proprietary software.

Demonstrating methods for using a portable optical particle spectrometer, a miniaturized and highly sensitive instrument, to measure atmospheric aerosol size distributions.

Satellite observations provide insight into the processes that control the spatial distributions of dust in global climate models.

Scientists discovered that a warming climate delays monsoonal rain, but only over land.

Regional climate models reveal irrigation’s role in strong precipitation and low-level winds across the Central United States.

The partnership to apply artificial intelligence to improve complex systems is part of a U.S. Department of Energy Office of Science $4.2 million, three-year grant.

PNNL scientists joined international leaders in artificial intelligence research to discuss the latest advances, opportunities, and challenges for neural information processing—the foundation for AI.