Topographic variations have substantial impacts on surface hydrologic processes. This study introduced a new subgrid structure and methods to increase model accuracy for snow water equivalent predictions.
In a recent publication in Nature Communications, a team of researchers present a mathematical theory to address the challenge of barren plateaus in quantum machine learning.
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.
PNNL researchers earned five Papers of Note, 17 Superior Papers, and one poster award for their environmental remediation, radioactive waste, and nuclear energy-related presentations.
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
