PNNL scientist Gokul Iyer was co-lead author of an award-winning paper that assessed the impact of pledges of more than 100 nations to reduce greenhouse gas emissions
Study demonstrates that choosing more accurate numerical process coupling helps improve simulation of dust aerosol life cycle in a global climate model.
Researchers seek to bring down costs, address potential environmental risks and maximize the benefits of harnessing wind energy above the deep waters of the Pacific.
Researchers show that small-scale turbulent fluctuations lead to larger concentrations of cloud droplets than would be possible in conventional models of atmospheric clouds
A new AI model developed at PNNL can identify patterns in electron microscope images of materials without requiring human intervention, allowing for more accurate and consistent materials science.
Published in Nature Communications, Increased Asian Aerosols Drive a Slowdown of Atlantic Meridional Overturning Circulation, identifies the role aerosols over Asia is having on the AMOC, a complex system of currents in the Atlantic Ocean.
Researchers seeking to enhance a climate model’s predictive capability identify parameters that cause the largest sensitivities for several important cloud-related fidelity metrics.
Researchers developed a groundbreaking database that includes 40,000 synthetic tropical cyclones, crafted using the Risk Analysis Framework for Tropical Cyclones and pioneering the application of advanced artificial intelligence.
Researchers developed a natural gas trade infrastructure capability within a computer planning model that includes representations of energy, agriculture and land use, economy, water, and climate systems in 32 regions of the world.
Researchers devised a quantitative and predictive understanding of the cloud chemistry of biomass-burning organic gases helping increase the understanding of wildfires.