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.
The results of this study reveal that the degree of Arctic amplification, despite being controlled by complicated interactions among multiple factors, can be analytically understood.
Neeraj Kumar discusses how AI can transform scientific research at the Platform for Advanced Scientific Computing Conference and Trillion Parameter Consortium European Workshop.
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.
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.
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.
Climate change is bringing more extreme summer weather, from heat waves to hurricanes, that can disrupt the flow of electricity. Here’s how PNNL scientists are working on solutions to protect the nation’s electric grid.
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.
