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.

A new iron-based aqueous flow battery shows promise for grid energy storage applications.

In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.

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.

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.

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.

Streamflow variability plays a crucial role in shaping the dynamics and sustainability of Earth's ecosystems, which can be simulated and projected by ESMs. However, the simulation of streamflow is subject to considerable uncertainties.

In this study, researchers used fire intensity data from satellites to map the distribution of aerosols into the atmosphere during a fire.

A new study uses direct numerical simulations to develop a near-surface turbulence model for thermal convection using interpretable and physics-aware neural networks, broadening the applications of numerical simulations.

PNNL scientists have put forth a new approach to protect the electric grid, creating an approach that sorts and prioritizes cyber threats on the fly.

Scientists have learned more about how to protect the insulin-producing cells that die in patients with Type 1 diabetes.

Models have identified a new source of anthropogenic emissions driving the observed weakening of the Atlantic Meridional Overturning Circulation.

A PNNL study developed a water management module for Xanthos that distinguishes between the operational characteristics of hydropower, irrigation, and flood control reservoirs.

Decreased snow cover observed over the past few decades and projected for the future suggest increasing snow droughts that threaten water security and management.

Using regional meteorological data from an atmosphere reanalysis product, scientists identified 12 unique winter weather systems in the Puget Sound area, featuring differing precipitation and temperature responses to climate variabilities.

ChatGrid™ is a practical application of the Department of Energy’s exascale computing efforts and offers a new experience in easy, intuitive, and interactive data interaction.