Moving toward a deeper understanding of the influence of large marine biogenic particles on cloud ice formation by combining modeling and observational data.

COVID-19 had multiple impacts on the electric sector and the nature of those impacts varied on the scale analyzed.

The overlooked impact of regional hydroclimate changes on lake evaporation implies more robust regional lake volume changes around the globe.

To improve the study of human-Earth interactions, a 10-year vision report by the MultiSector Dynamics community of practice encourages the use of emerging human systems datasets, embedded intelligence in modeling, and workforce diversity.

PNNL chief chemical engineer Carlos Fernandez is a guest editor for a set of collection papers in Scientific Reports focusing on natural fibers.

Steven Spurgeon, a materials scientist and microscopy researcher at PNNL, has accepted an affiliate associate professorship at the University of Washington Department of Physics.

Improving predictability of water quality and nutrient cycling in large river systems.

Developing conceptual models for microbial-environmental–ecosystem interactions is key to enhancing the ability of models to predict future ecosystem function.

The rapid growth of urban nanoparticles via the condensation of organic vapors substantially alters shallow cloud formation and suppresses precipitation.

AMS Hydrologic Sciences Medal is presented to researchers who make outstanding contributions to scientific knowledge in hydrology, hydrometeorology, and/or hydroclimatology, including interactions between land surface and the atmosphere.

COMPASS points to understanding nature’s transition zones—areas that can be dry land at times and under water at others.

Research from the PNNL-led WHONDRS consortium reveals chemistry and spatial gradients of metabolomes from river water and sediments around the globe.

Changes in the downward flow of infrared energy in clear skies are a key factor influencing recent rapid wintertime Arctic warming.

Ensembles of 20–25 members, notably smaller than traditional large ensembles, can accurately represent changes in extremes of temperature and precipitation.

From water purification, to better batteries and tools to foil a cyberattack—a look back at how PNNL helped to invent a brighter and better future over the last year.

Researchers developed a new model to understand the initiation of summer-time mesoscale convective systems over the central United States.

Researchers have been investigating if machine learning techniques could be used to help create novel beers.

Using a novel settlement-related dataset produced more accurate population downscaling than using other, more traditional datasets.

Implementing and evaluating a new radiative transfer scheme that accounts for various topographic effects on solar radiation in an Earth system model.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.