Atmospheric rivers are increasingly reaching the Arctic in winter, slowing sea ice recovery and accounting for a third of winter sea ice decline from 1979-2021.
Performing closure studies using aerosol size, aerosol composition, and cloud condensation nuclei measurements of mixed aerosol from the Southern Great Plains region.
A newly developed basin-scale river corridor model can quantify how riverbed microbes drive respiration and the generation of carbon dioxide in the Columbia River Basin.
Bobbie-Jo Webb-Robertson is a leader with a PhD in decision sciences & engineering systems from Rensselaer Polytechnic Institute and experience in managing complex scientific programs and line organizations. She assumed the role 3/13/23.
With future warming, storms in the Western U.S. will be larger and produce more intense precipitation, particularly near the storm center, and increase flood risks.
PNNL welcomes new joint appointments to expand the research productivity and scientific impact of both PNNL and the university partners, broadening the base of expertise at each institution and helping to build interdisciplinary teams.
A new nano-optical bioimaging technology in development at PNNL enables researchers to watch climate-bellwether microbes exchange metabolites and other essential signals.
A multi-omics analysis provides the framework for gaining insights into the structure and function of microbial communities across multiple habitats on a planetary scale
In new work, PNNL researchers find that 10 gigatons of carbon dioxide may need to be pulled from Earth's atmosphere and oceans annually to limit global warming to 1.5 degrees. A diverse suite of carbon dioxide removal methods will be key.
Machine learning models help identify important environmental properties that influence how often extreme rain events occur with critical intensity and duration.
Hailong Wang is a non-federal co-lead for the Arctic Systems Interactions Collaboration Team that will explore the Arctic’s dynamic interconnected systems.
Gosline works to develop computational algorithms that are uniquely targeted for rare disease work by doing foundational research in model system development. This work can be expanded to all model systems in human disease.