The Co-Optimization of Fuels & Engines initiative recently outlined six years of research in a findings and impact report.

Researchers at PNNL are developing a better model of the soil, better representing the atmosphere, and identifying sources of record high rainfall within a model of the Earth system.

An improved model captures the interactions between the U.S. economy, energy, water, and land systems with increased spatial and temporal detail.

Recalibrating both cloud and subgrid representations improves model projections of the base climate, aerosol-cloud interactions, and cloud feedbacks.

Three PNNL bioenergy experts have received adjunct appointments at Washington State University (WSU), working closely with the WSU-PNNL Bioproducts Institute and students.

A climate change study co-authored by PNNL scientist Hailong Wang inspired an artist to create an exhibit based on the research.

A newly developed tool helps researchers analyze process-level relationships within atmospheric models.

In an invited review article, PNNL researchers examined the literature surrounding modeling and measuring the ice-nucleating particles that help form clouds.

Scientists from PNNL and the U.S. Department of Agriculture-Forest Services’ Pacific Northwest Research Station have partnered to evaluate potential climate and wildfire adaptation scenarios and resulting benefits from restoration forestry.

A global warming-induced poleward shift of the westerly jet affects the hydroclimate of the U.S. Midwest differently in the spring and summer.

The COVID-19 pandemic massively disrupted human activities, which caused additional turmoil through regional record rainfall and floods.

The climate models best at simulating current precipitation and its drivers show more consensus in projecting future precipitation.

Examining the vast scientific literature about the urban impact on weather and climate enabled researchers to synthesize current understanding and to inform future work.

PNNL bioenergy expert Karthikeyan Ramasamy was a co-guest editor in an American Chemical Society Energy & Fuels virtual special issue on advances in biomass and wastes thermochemical processing.

State-of-the-art numerical models can better simulate the convective clouds that produce most of the Amazon’s wet season rainfall.

Researchers used ground-based and remote-sensed datasets to comprehensively validate a tool for simulating land surface processes.

A new hexagonal framework helps more accurately model watersheds at a range of scales.

Study reveals importance of accounting for micrometer scale distribution of substrates to predict carbon emissions from soil.

PNNL scientist Brian O’Neill led the compilation of an IPCC chapter about climate-related risks.

Developing a model for global soil erosion and sediment flux to advance understanding of land, river, and ocean geomorphology and biogeochemistry.