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 demonstrates the statistical uncertainty in estimating a threshold from small datasets is sufficient to compromise many types of drought analysis.
This research provides the first set of national-scale estimates of the contribution inflow forecasts make on the seasonally varying release and storage operations of a large sample of dams.
To study the impact of accelerated dryland expansion and degradation on global dryland gross primary production (GPP,) PNNL and Washington State University researchers assessed GPP data from 2000-2014 and the CMIP5 aridity index (AI).
Radiation from natural sources in the environment can limit the performance of superconducting quantum bits, known as qubits. The discovery has implications for quantum computing and for the search for dark matter.
A cadre of physical scientists, engineers and computing experts at Pacific Northwest National Laboratory is poised to participate in the launch of three new DOE Office of Science-sponsored quantum information science research centers.
Contributions from researchers across Pacific Northwest National Laboratory (PNNL) were recently recognized in the preliminary findings of a Secretary of Energy Advisory Board (SEAB) report.
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.
