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

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

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.

A new generation of microelectronics research begins at PNNL.

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

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

A new study reveals just how costly Earth's tipping points can be.

Through a detailed examination of historical data supported by mechanistic analysis and model experiments, researchers unveil that a large-scale climate system intensifies heat extremes and wildfire risks in the PNW.

This study shows that dry dynamics alone is not enough to understand jet stream persistence. Instead, clouds and precipitation are more important contributors than internal “dry” mechanisms to this memory of the Southern Hemisphere jet.

The research presented in this article enhances the ability to predict and prepare for compound flood events along the U.S. coastline.

Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.

This study provides a comprehensive analysis of isolated deep convection & mesoscale convective systems using self-organizing maps to categorize large-scale meteorological patterns and a tracking algorithm to monitor their life cycle.

The speed and agility of cloud computing opens doors to completing advanced computational chemistry workflows in days instead of months.

This study explored the future effects of climate change and low-carbon energy transition (i.e., emission reduction) on Arctic offshore oil and gas production.

Using numerical simulations to reproduce the laboratory experiments, this study reveals that liquid droplets are present near the bottom surface, which warms and moistens the air in the chamber.

This work shows that linear pattern scaling is an effective means of obtaining global-to-local relationships for CMIP6 models, as it has been in past model eras.

Researchers discussed this topic at the 2024 Analog Computing for Science Workshop co-led by Antonino Tumeo.

This study examined the role of river sinuosity using computer models to understand what drives hyporheic exchange, a process that significantly affects water quality and ecosystem health.