This project sought to assure that research activities centered around different sampling and monitoring efforts in northwest Ohio would not disturb any historical cultural resources.

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.

With the help of the U.S. State Department, PNNL climate scientists assisted counterparts in Malaysia and Thailand in exploring carbon neutral goals.

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

PNNL’s Climate Network with MSIs and HBCUs aims to bring opportunities to diverse populations.

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.

Earth Scientist Laura Fierce mentors Department of Energy Science Graduate Student Research program awardees.

As electricity grids incorporate renewables, several factors will constrain future output, according to a new paper.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

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

This study demonstrated that a large-scale flooding experiment in coastal Maryland, USA, aiming to understand how freshwater and saltwater floods may alter soil biogeochemical cycles and vegetation in a deciduous coastal forest.

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

Microbes that were previously frozen in soils are becoming more active. This study demonstrates the diverse RNA viral communities found in thawed permafrost.

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

Organismal contribution and community interaction drive soil organic matter breakdown by microbes.

PNNL joint appointee Auroop Ganguly uses data science to study the impacts of climate change.

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

Proteins from “auxiliary” genes in soil viruses play a role in the carbon cycle and climate, scientists have found.