From studying the multisector ripple effects of extreme events to exploring the chemical reactions that underlie life on Earth, two up-and-coming PNNL scientists were recognized for their scientific vision and prowess.

A theoretical index linking precipitation and atmospheric evaporative demand explains historical land humidity changes across observations, reanalyses, and climate models.

A 14-year comparison with satellite observations identified robust mesoscale convective cloud statistics and systematic precipitation biases in ERA5.

Observations, reanalysis, and E3SMv3 experiments linked inter-annual variability of Congo Basin surface temperature to the zonal position of precipitation over the Indo-Pacific maritime continent region.

Quasi-stationary Rossby waves shape North American temperature extremes, but higher model resolution does not always improve their modeled representation.

Watershed-based representation discretized into topographic subgrid units better captured small-scale land cover, precipitation, temperature, and snow variability across multiple spatial scales.

Numerical simulations reveal how well-controlled wall temperature and moisture can generate a stratocumulus-like cloud top in a laboratory cloud chamber.

A new tracer model tracked how May 2015 storm water re-entered the atmosphere and contributed to later rainfall.

Physics-informed and data-driven neural network models enhance Earth system models in simulating compound flooding at river-ocean interfaces.

Observations and models showed that tropical cyclone outer size increased in the western North Atlantic since 1979.

Global exercise advances nuclear forensic science and investigative capabilities.

Tracking water age using a new precipitation tagging method within a hydrologic model generates key information to support hydropower energy and other water-dependent systems.

More rain and less snow shorten how long water stays in watersheds.

​​Tests show which low-cost 3D method best matches field measurements to minimize errors in mapping headwaters.​

PNNL scientists were among the specialists keeping the crowds safe at the recent FIFA World Cup competition.

A research team from Pacific Northwest National Laboratory used machine reasoning to schedule scientific workflows while guaranteeing quality of service (QoS).

PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.

Through the Air Force Education with Industry program, PNNL is forging powerful connections between research, leadership, and industry.

Now, anyone can easily explore and access data from a nationwide map of data centers, the infrastructure that powers them, and projections of future data center locations.

The Scientific Discovery through Advanced Computing institute will focus on making scientific machine learning accessible to domain scientists.