Hi-C metagenomics-informed phage-host infection networks detected in soil pre- and post-drying.

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

Investigating the impact of global warming on mesoscale convective systems initiation and growth with a theoretical model.

Understanding the contrasting response in relative humidity at ocean and land surfaces under global warming.

The cross-equatorial surge enhances the southward development of the Madden–Julian oscillation because of increased moisture convergence.

The roles of the various environmental variables in the transition from suppressed to active tropical precipitation regimes are characterized using statistical analysis and machine learning.

Soil is a massive reservoir of carbon, holding three times the amount of carbon than in the atmosphere. Soil is a massive reservoir of carbon, holding three times the amount of carbon than in the atmosphere.

A new moist potential vorticity model helps researchers understand atmosphere–land moisture exchanges over the United States.

Metabolism metrics provide information about biological activity and carbon cycling in rivers. Conditions in large rivers differ from smaller rivers and require adjustments to existing methods.

A modeling study finds that multiple factors almost perfectly balance under anthropogenic greenhouse gas forcing, leaving no footprint on the dynamically induced ocean heat storage in the Southern Ocean.

Climate change and socioeconomic pressures are transforming passenger and freight transportation in the Arctic, producing effects that have yet to be fully understood.

Scientists developed a process (or pipeline) that combined molecular probes—a specific chemical that binds to microbes carrying out a particular function—with a method that isolated these cells from their complex community.

High fidelity simulations enabled by high-performance computing will allow for unprecedented predictive power of molecular level processes that are not amenable to experimental measurement.

Testing the assumption that different future socio-economic development patterns, which result in different land-use changes, can be paired with different future climate outcomes for risk assessments in a multi-model framework.

PNNL is honoring its postdoctoral researchers as part of the fourteenth annual National Postdoc Appreciation Week with seven profiles of postdocs from around the Laboratory.

The diversity and function of organic matter in rivers at a large scale are influenced by factors, such as the types of vegetation covering the land, the energy characteristics, and the breakdown potential of the molecules.

Harnessing machine learning to enhance plant coexistence in a vegetation demographic model.

PNNL energy storage experts express need for continued investment in developing and deploying long-duration energy storage.

A holistic evaluation of the uncertainty sources that arise from configuring the model to processing the output for global variable-resolution models.

A success story of applying convergence testing to detect and address issues of numerical discretization in nonlinear representations of turbulence and clouds.