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.
By using the new reservoir storage-area depth dataset, PNNL researchers were able to improve surface temperature simulation for ~70% of validated reservoirs compared to using simplified reservoir geometry as in previously available models.
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.
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.
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.
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.
In this study, researchers probed the ice nucleation ability of different aerosol types by combining 11-year observations from multiple satellites and cloud-resolving model simulations.
