Researchers use dataset combining observational data with advanced numerical simulations to investigate the characteristics, drivers, and trends of extreme heat events in the High Arctic over past four decades

Researchers develop framework that tracks the aerosol–cloud interactions along the trajectories of air parcels and embed framework into Weather Research Forecast model.

Study develops high-resolution land surface data for 2001 to 2020, including parameters of land use, vegetation, soil, and topography and demonstrated its use in k-scale simulation using the Energy Exascale Earth System Model.

Researchers show how satellite observations from the MODerate Resolution Imaging Spectroradiometer and CloudSat radar can be used to constrain the ACI radiative forcing that is linked to droplet collection in marine liquid clouds.

Researchers provide clear evidence to show that the fourfold Arctic Amplification over recent decades is an anomaly caused by dominant modes of natural variability.

Researchers synthesize molecular-level laboratory experiments to develop comprehensive model representations of new particle formation and the chemical transformation of precursor gases.

Researchers introduce revised emission treatment that conserves mass and preserves the original heterogeneity.

Researchers show application of a causal model better identifies direct and indirect causal relations compared to correlation and random forest analyses performed over the same dataset.

Study explores Exploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments, a consortium of scientists interested in the exchange between water and land in coastal systems.

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.

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.

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

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

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