Machine learning models help identify important environmental properties that influence how often extreme rain events occur with critical intensity and duration.

PNNL is working with the Port of Seattle and Seattle City Light to assess the risks of long-term hydrogen storage that can bring clean power for decarbonization.

A scenario approach was used to explore the potential future role of hydropower around the globe considering the multisectoral dynamics of regional energy systems and basin-specific water resources.

Report for the Oregon Public Utility Commission highlights innovations and best practices for resilience and utility planning could be helpful to other states as well.

A new report, based on a community workshop and literature review, summarizes some of the biggest challenges in understanding and modeling Earth system and human–Earth system dynamics in the Puget Sound region of Washington State.

Improving a snow albedo model to account for non-spherical snow grain shapes and the mixing of dust inside snowflakes in an Earth system model.

Building new climate outcome scenarios by stitching together pieces of existing ones.

Researchers found that specific landscape metrics consistently outperform traditional population downscaling methods.

The flux of carbon dioxide from forest soil may acclimate to some aspects of climate change.

Identifying links between large-scale and local-scale model biases in tropical precipitation.

Harnessing the sea for decarbonized energy is the focus of a new collaboration between PNNL and the University of Guam.

A systematic, multiple scenario approach was used to analyze the compounding impacts of demands for land for biofuels with increased land scarcity under a diverse set of uncertainties.

Interactive freshwater flux works to prolong density anomalies over deep water formation areas in the North Atlantic.

A collaborative effort led by PNNL researchers analyzed decarbonization pathways for Argentina, Chile, Egypt, Indonesia, and Nigeria.

rmap enables users with limited to no geographic information system knowledge use R to visualize simple tabular data.

The methods researchers use to estimate crop yield gaps determines the location of projected future agricultural “breadbasket” regions.

Interactions between fronts and the land-sea breeze lead to strong vertical exchange in the northern Gulf of Mexico.

A PNNL team developed and used a model framework to understand the performance and structural reliability of a state-of-the-art solid oxide electrolysis cell design.

Data-driven experiments can help determine best practices for Random Forest machine learning to predict water quality, particularly nitrate levels.

When wildfires burn in the west, the heat and airborne particles they release inflict stronger rain and larger hail upon central states.