PNNL postdoc Pengfei Shi won first place in the Early Career Researcher Poster Competition at the recently concluded NOAA Subseasonal and Seasonal Applications Workshop.
Data-gathering instruments will be positioned on commercial, ocean-going ships in a Department of Energy-funded project that is expected to improve understanding of marine atmosphere and aerosol–cloud interactions.
Skillful predictions of tropical cyclone activity on subseasonal time scales may help mitigate their destructive impacts. This study investigates the combined impacts of atmospheric phenomena to better understand cyclone activity.
To gain a mechanistic understanding of the physical processes responsible for the enhanced hurricane cold wakes near the Southeast United States, investigators used ocean reanalysis datasets.
Cloud and its radiative effect are among the determining processes for the energy balance of the global climate; they are also the most challenging processes for the climate models to simulate.
Researchers found that in a future where the Great Plains are 4 to 6 degrees Celsius (°C) warmer as projected in a high-emission scenario, these storms could bring three times more intense rainfall.
Researchers develop comprehensive framework for the Energy Exascale Earth System Model, incorporating advanced river and ocean models that improve how such interactions are simulated
Researchers use observations and numerical models to examine changes in tropical cyclone intensification rates and their environment in global coastal regions
Scientists develop a water tracer tool in an advanced hydrologic model to understand the importance of modeling lateral flow in hydrologic simulations.
Scientists use water vapor tracers incorporated in a climate model to tag moisture from local evapotranspiration and trace their evolution through different processes.
Researchers evaluate a new slab ocean capability in the Energy Exascale Earth System Model (E3SM) version 2 by comparing its climate simulation to that of the full version of E3SM that uses a dynamic ocean model.
Aerosol particles imbue climate models with uncertainty. New work by PNNL researchers reveals where in the world and under what conditions new particles are born.
Accessing groundwater may become more difficult—and more expensive—as groundwater supplies become increasingly scarce and underground aquifer levels fall.
Researchers demonstrate an AI that can be taught to recognize cloud types by looking at millions of satellite images of clouds without requiring human input.
Researchers measured ice nucleating particles composition at the Southern Great Plains atmospheric observatory, enabling them to identify sources of particles that make them effective ice nucleators.
