Anika Halappanavar’s research into COVID-19 misinformation earned her recognition by the Washington State Academy of Sciences as one of the state’s top high school researchers.

Four research staff from PNNL are part of an international team that earned top honors for a journal paper focused on a new algorithm-evaluation approach for buildings.

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.

Researchers are developing an understanding of how either wet or dry soil patches change the sizes of atmospheric eddies and cloud clusters.

PNNL scientists reveal that climate change will increase lake evaporation most dramatically in the Mediterranean, Southeast China, and Tropical America.

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.

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

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.

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.

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.