Researchers from PNNL and Parallel Works, Inc., applied machine learning methods to predict how much oxygen and nutrients are used by microorganisms in river sediments.
The rate of conversion of cloud droplets to precipitation, known as the autoconversion rate, remains a major source of uncertainty in characterizing aerosol’s cloud lifetime effects and precipitation in global and regional models.
To assess the impact of observation period and gauge location, model parameters were learned on scenarios using different chunks of streamflow observations.
This study presents an automated method to detect and classify open- and closed-cell mesoscale cellular convection (MCC) using long-term ground-based radar observations.
PNNL had a significant presence at October’s North American Wind Energy Academy/WindTech 2023 Conference in Denver, Colorado. Thirteen PNNL wind experts participated in various capacities.
A research buoy managed by PNNL has been deployed in Hawai’ian waters, collecting oceanographic and meteorological measurements off the coast of O’ahu.
Rey Suarez is a nuclear nonproliferation researcher who is working on equipment that can detect radionuclides emitted from a nuclear explosion as part of treaty monitoring.
A paper by PNNL scientists on nuclear explosion monitoring technology is among top articles in nuclear instruments journal to draw most social media “buzz.”
PNNL deployed two research buoys in waters off the West Coast for the first time in deep water, supporting a DOE and Bureau of Ocean Energy Management effort to gather measurements that support offshore wind locations and technologies.