Researchers who explore the interactions between human and natural systems will now have the ability to generate thousands of scenarios that can include different kinds of extreme events to study.

PNNL researchers explored the impacts of short-term shocks on both long-term electric capacity investment and on sub-annual power system operations.

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.

Pacific Northwest marsh carbon stocks are twice the global average. Long-term sea-level rise impacts will likely decrease ecosystem carbon stocks.

The results of this study provide an analysis of the ice nucleation efficiency of bare and acid coated loess from the Columbia Plateau region of the northwestern United States.

PNNL researchers performed and analyzed a large set of sensitivity experiments carried out with the Energy Exascale Earth System Model (E3SM) atmosphere model to identify implementations of a technique called nudging.

Researchers at PNNL tested an alternative approach to determining the mean size of atmospheric particles from remote sensing instruments.

Using machine learning, PNNL researchers identified four types of environments with favorable circulation patterns for spring mesoscale convective systems (MCSs) to form.

PNNL and University of Arizona researchers evaluated the performance of the Weather Research and Forecasting (WRF) model in simulating precipitation under different weather patterns.

A research team, led by scientists at PNNL, analyzed aerosols’ physical, chemical, and optical properties collected by a suite of airborne instruments during winter as part of a year-long measurement campaign in Cape Cod, Massachusetts.

Using two ice nucleation chambers, PNNL researchers found that ice particles, once nucleated, are more efficient at forming ice in the next ice nucleation event.

This research provides the first description of incremental water-electricity resilience in the U.S. that considers multiple scales of system inter-dependencies and associated ranges of system decision making.

Researchers developed a high-resolution mesoscale convective systems database by synthesizing satellite and radar network observations available from 2004 to 2016.

Cloud and precipitation characteristics observed by the Global Precipitation Measurement spaceborne radar allowed researchers to establish, for the first time, a global map of mesoscale convective systems in mid- and high-latitude regions.

As the planet has warmed during recent history, summer sea ice extent has been decreasing in the Arctic but expanding in the Antarctic at modest but significant rates. This study helps explain why the hemispheres are behaving differently.

A new version of the E3SM Atmosphere Model (EAM) has been released to the community. This study provides an overview of the model and the science behind it, describing advances made to address E3SM science challenges.

A study led by researchers at PNNL reveals physical mechanisms that link declining Arctic sea ice to increasing winter air stagnation and pollution extremes in China based on Earth system modeling results.

Researchers performed controlled laboratory experiments using river sediment to test organic matter thermodynamics as a mechanism of metabolic control in areas where groundwater and surface water mix.

Researchers performed a combined analysis of metabolic and gene co-expression networks to explore how the soil microbiome responds to changes in moisture and nutrient conditions.

Researchers trained deep neural networks to accurately predict microbial interactions captured by fluorescence microscopy.