In a new video series this fall, PNNL is highlighting six scientific and technical experts in the national security domain. Each was promoted to Scientist and Engineer Level 5, one of PNNL’s most senior research roles.
Five PNNL technologies were recently awarded six R&D 100 honors. The R&D 100 Awards, now in its 58th year, recognize pioneers in science and technology from industry, the federal government, and academia.
A team of researchers led by scientists from PNNL simulated carbon cycling and community composition during 100 years of forest regrowth following disturbance.
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.
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.
