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

Secondary organic aerosol formation from monoterpenes is more strongly influenced by oxidant and monoterpene structure than by nitric oxides and hydroperoxy radical concentrations.

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.

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

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

Better representing electric capacity markets, economic retirements, and power-plant age structure provides a more robust understanding of the future evolution of the electric sector.

Newly developed deep learning models can estimate 3-D permeability fields from time-lapse geophysical electrical imaging.

Repeated aircraft measurements over central Oklahoma allow researchers to better understand the spatial variability of aerosol properties that affect cloud evolution.

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

Developing a new method to identify the fraction of green vegetation from satellite data at high spatial resolution.

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

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.

Increasing amounts of atmospheric carbon dioxide change when in the day tropical forest rainfall occurs.