New work finds hurricanes are intensifying faster close to the coast—a trend that’s likely to ramp up in a warmer world.

With Earth system models running at higher resolutions, researchers evaluated the sensitivity of aerosol properties to horizontal grid spacing.

This study demonstrates a new model that integrates complex organic matter (OM) chemistry and multiple electron acceptors to predict kinetic rates of OM oxidation.

Study reviews the loss of carbon dioxide from soils and explores most compelling challenges and opportunities for the future.

New research informs the development of foundational models for computational chemistry through hardware-software co-design.

A set of papers combines surface science measurements on tiny particles with uncrewed aerial systems to better understand and model aerosols.

Study demonstrates that choosing more accurate numerical process coupling helps improve simulation of dust aerosol life cycle in a global climate model.

Study introduces a mathematically rigorous analysis framework that provides insight into the features and implications of coupling method choices.

PNNL researchers have used field campaign data to better understand clouds, aerosols, and the interactions between humans and the atmosphere.

A new model accounts for co-occurring environmental parameters to improve predictions of a hurricane’s intensification.

As new paradigms in advanced computing take shape, computational chemistry researchers are finding new ways to solve challenging chemistry problems.

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.

Research indicates shifts in two climate oscillations drive spatial differences in Arctic atmospheric river trends over the past four decades.

Researchers show that small-scale turbulent fluctuations lead to larger concentrations of cloud droplets than would be possible in conventional models of atmospheric clouds

Researchers investigated how stable nanoparticle suspensions form using facet engineering on hematite nanoparticles, demonstrating that controlling the faceting of nanoparticles can effectively maintain particle dispersity.

Researchers seeking to enhance a climate model’s predictive capability identify parameters that cause the largest sensitivities for several important cloud-related fidelity metrics.

Chemists Wilma Rishko and Samantha Johnson are set to receive an ACS Division of Inorganic Chemistry Award for Undergraduate Research as a mentor-mentee pair.

This study uses numerical simulations to explore various configurations of a convection‐cloud chamber that may intensify collision‐coalescence.

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.