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.

Flexible, high-throughput proteomics approach identifies protein modifications related to pancreatic stress and insulin production.

A new study led by PNNL researcher TC Chakraborty provides some answers about how irrigated agricultural land near cities affects urban heat stress.

Scientists map how transitions from day to night control gene regulatory networks in cyanobacteria, revealing key orchestrators of metabolic switching.

Scientists uncover how cyanobacteria's circadian cycle controls carbon and energy metabolism, increasing carbon dioxide-to-bioproducts yields.

PNNL is hosting a scientific conference focused directly on understanding and predicting the collection of an organism’s traits.

Circadian rhythms of blue-green microbes offer new window into predictive phenomics—how to predict and control the traits of an organism.

This week at AAAS, PNNL scientists discuss phenomics and the factors that influence DNA instructions to bring about the world around us.

Andrew Gettelman at PNNL elected as president of the Atmospheric Sciences section of the American Geophysical Union.

A potential quantum advantage for fluid dynamics simulations from molecular to atmospheric scales with a new formula for success.

Several Earth system components are at a high risk of undergoing rapid, irreversible qualitative changes or ‘tipping’ with increasing climate warming.

Seawater threatens to intrude into coastal freshwater aquifers that millions of people depend on for drinking water and irrigation. This study investigates sea-level rise impacts on the global coastal groundwater table.

New datasets delineating global urban land support scientific research, application, and policy, but they can produce different results when applied to the same problem making it difficult for researchers to decide which to use.

A tethered balloon system was used at the Southern Great Plains atmospheric observatory in Oklahoma to collect atmospheric particles from ground and aloft levels. Samples were later analyzed for their organic molecular composition.

Better understanding how clouds mix with surrounding dry air is crucial for accurate weather and climate predictions.

A new analysis shows how renewable energy sources like solar, wind and hydropower respond to climate patterns, and how utilities can use this data to save money and invest in energy storage.

A recent paper published in Science sheds light on how aerosols—tiny particles in the air—released by industrial activities can trigger downstream snowfall events.

Knowing future snow levels is key for managing the recovery of endangered bighorn sheep. PNNL scientists help to forecast how the sheep could fare.

His expertise in data science and commitment to open science will drive dataset dissemination and advance collaborative global research efforts.