The ability of a storm-resolving weather model to predict the growth of storms over central Argentina was evaluated with data from the Clouds, Aerosols, and Complex Terrain Interactions (CACTI) field campaign in central Argentina.

Researchers have developed the first coastal transport model for microplastics to understand how particles move in waterways and coastal currents.

Researchers from PNNL and Parallel Works, Inc., applied machine learning methods to predict how much oxygen and nutrients are used by microorganisms in river sediments.

Lakes are important sentinels of climate change and contribute significantly to the emissions of the second most important greenhouse gas—methane.

The rate of conversion of cloud droplets to precipitation, known as the autoconversion rate, remains a major source of uncertainty in characterizing aerosol’s cloud lifetime effects and precipitation in global and regional models.

To assess the impact of observation period and gauge location, model parameters were learned on scenarios using different chunks of streamflow observations.

PNNL's E-COMP initiative is helping unleash American energy innovation with advanced theories, models, and software tools to better operate power systems that rely heavily on high-speed power electronic control.

This study presents an automated method to detect and classify open- and closed-cell mesoscale cellular convection (MCC) using long-term ground-based radar observations.

PNNL's accomplishments in FY 2024 help address the remaining challenges the wind industry faces.

PNNL researchers are exploring the kinds of flicker waveforms that the eye and brain can detect, seeking to understand the different visual and non-visual effects that result.

GUV can reduce transmission of airborne disease while reducing energy use and carbon emissions. But fulfilling that promise depends on having accurate and verifiable performance data.

There are many ways that researchers at PNNL bring unique perspectives to the field of distributed wind. One is the fact that PNNL's distributed wind projects are all led by women.

Mandy Mahoney, director of the DOE Building Technologies Office, visited PNNL in late November. One key agenda item involved meeting with staff for a discussion of effective equity and justice integration in buildings-related research.

PNNL will lead support to one of six community teams chosen today by the U.S. Department of Energy to receive a total of up to $25 million.

The Distributed Wind Market Report provides market statistics and analysis, along with insights into market trends and characteristics of wind technologies used as distributed energy resources.

Staff at PNNL recently completed a report highlighting commercial products enabled through projects funded by the Department of Energy’s Building Technologies Office.

PNNL researchers launch a new DOE project focused on advancing GUV technology for improved public health outcomes and decarbonization benefits.

The Simple Building Calculator, developed at PNNL, meets a need for a quick, interactive, and economic method to evaluate energy use—and potential savings from efficiency measures—in simple commercial buildings.

An evaluation of models and prediction tools for distributed wind turbines has unearthed data that can help potential users make the most informed decisions on upfront investments.

Research organizations work toward compelling market-ready solutions for building operations.