Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.

PNNL-University of California, Berkeley scientist cited for ‘tireless dedication to the stewardship of catalysis.’

PNNL recognizes researchers during National Postdoc Appreciation Week.

A team of researchers led by scientists from PNNL simulated carbon cycling and community composition during 100 years of forest regrowth following disturbance.

PNNL quantum computing pioneer Nathan Wiebe contributed to a Google-led quantum computing landmark study published in the journal Science.

First-ever measurements provide evidence that supercooled water exists in two distinct structures that co-exist and vary in proportion dependent on temperature.

Mesoscale convective systems produce more intense rainfall than warm-season rain in this region.

This study by PNNL researchers provides an alternative explanation for why the Arctic warms more than the Antarctic.

This study examines the roles of the semi-annual variation of solar radiation and soil moisture on the Madden-Julian Oscillation (MJO) propagation across the Maritime Continent islands.

University of Maryland, NASA Goddard Space Flight Center, and PNNL scientists explored how radiation-cloud-convection-circulation interactions (RC3I) affect the Intertropical Convergence Zone (ITCZ) and circulation at the global scale.

A study led by scientists at PNNL points to a new frontier for understanding the coupled climate system from the perspective of a nonlinear dynamical system.

By quantifying the contribution of snowpack to runoff and extreme flooding in mountainous regions in the western United States, PNNL researchers provided a unified view of the interactions between snowpack and precipitation.

This study, led by by PNNL researchers, highlights the substantial role of soil erosion in the carbon cycle simulated by Earth system models.

DOE lab and university researchers used the Community Atmospheric Model 5.3 to investigate the power sea surface temperature has on the intensification or widening of the Hadley cell in the Northern and Southern hemispheres.

A team of researchers led by PNNL scientists have developed an open-source modeling platform, called Metis, that combines global human and Earth system dynamic tools with local datasets.

A study led by PNNL scientists reveals the influence of Arctic and midlatitude black carbon—or soot particles—on the frequency of extreme El Niño-Southern Oscillation (ENSO) events.

This study explores the relative role of temperature and humidity in extreme wet-bulb events and spurs further research into how these factors may change the frequency and intensity of life-threatening events in the future.

A team of researchers, including PNNL scientists, used 13 years of data to develop an automated algorithm that identifies seven different cloud types at the Atmospheric Radiation Measurement (ARM) site in the U.S. Southern Great Plains.

PNNL researchers used a new method for fingerprinting the sources of rainfall changes in tropical circulations. This new method was applied to the Asian Summer Monsoon (ASM) in DOE’s Energy Exascale Earth System Model.