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.

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.

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

The Earth System Model Aerosol–Cloud Diagnostics package version 2 uses aircraft, ship, ground, and satellite measurements to evaluate detailed physical processes in aerosols, clouds, and aerosol–cloud interactions.

Pacific Northwest may face increase in summer heat-dome-like stationary waves.

New research shows how cloud shapes affect the process of cloud evolution, resulting in better understanding of how clouds behave, improving weather forecasts, and enhancing comprehension of climate systems.

Scientists recently developed a flow direction model which produces high-quality flow routing parameters on any mesh system.

A multi-omics analysis provides the framework for gaining insights into the structure and function of microbial communities across multiple habitats on a planetary scale

To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.

Data-driven experiments can help determine best practices for Random Forest machine learning to predict water quality, particularly nitrate levels.

Across the United States, water moving between the river and riverbed sediments does not overcome localized processes that govern organic matter chemistry.

New work developed a methodology to generate building temperature setpoint schedules for use by modelers in large-scale building energy simulations.

COVID-19 had multiple impacts on the electric sector and the nature of those impacts varied on the scale analyzed.

PNNL paper in Nuclear Technology journal unveils modeling possibilities for TRISO used fuel, implications for reactor planning, and resulting carbon-free nuclear energy.

Hypergraphs can more faithfully identify important genes in complex immune responses.

New mathematical tools developed at PNNL hold promise to transform the way we operate and defend complex cyber-physical systems, such as the power grid.

Geophysical modeling and inversion software meets DOE and nuclear industry standards for use in decision-making for radiologically contaminated sites.