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.

Evaluating the relative roles of soil water stress and vapor pressure deficit at limiting canopy conductance in coupled land-atmosphere simulations.

Tailoring hydrogen-based energy storage solutions to specific real-world applications.

Understanding why the westerly jets shift poleward in certain seasons and regions but equatorward in others under global warming.

PNNL joint appointee Auroop Ganguly uses data science to study the impacts of climate change.

Across the United States, water moving between the river and riverbed sediments does not overcome localized processes that govern organic matter chemistry.

Two case studies of clouds evolving over the Arctic provide data that will help researchers evaluate cloud simulations.

Evaluating the accuracy of predicted plant aboveground biomass with different numerical solution options in a model of water transport in plants.

The presence of mMarine microorganisms may enhance cloud droplet formation, leading to brighter clouds that reflect more sunlight.

How hailstorms respond to human-created warming in the Great Plains depends on large-scale weather-producing systems.

Both the type and composition of landforms affect atmospheric properties and clouds in a state-of-the-art Earth system model.

Observational evidence shows that clouds strongly influence the seasonal heat exchange between Southern Ocean air and sea.

Anthropogenically forced evolution of the leading neutral mode explains historical trends in global surface temperature, lending confidence to regional projections related to modes.

Aerosols from sea-spray that are transported by atmospheric rivers enhance snow precipitation in the Sierra Nevada Mountains.

The initial conditions and setup influence how large-eddy simulations representation atmospheric properties important for larger-scale models.

Changes in land use and land cover have diverse and contrasting effects on different types of rain.

Metrics and diagnostics that improve connections between model errors and their sources can lead to better precipitation modeling.

A circumglobal circulation pattern related to natural climate variability influences the location of summertime hot spots.